Index

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

A

abortExperiment() - Method in class weka.experiment.RemoteExperiment: Set the abort flag
AbstractAssociator - Class in weka.associations: Abstract scheme for learning associations.
AbstractAssociator() - Constructor for class weka.associations.AbstractAssociator
AbstractClassifier - Class in weka.classifiers: Abstract classifier.
AbstractClassifier() - Constructor for class weka.classifiers.AbstractClassifier
AbstractClusterer - Class in weka.clusterers: Abstract clusterer.
AbstractClusterer() - Constructor for class weka.clusterers.AbstractClusterer
AbstractCommand - Class in weka.gui.simplecli: Ancestor for command.
AbstractCommand() - Constructor for class weka.gui.simplecli.AbstractCommand
AbstractDataSink - Class in weka.gui.beans: Abstract class for objects that store instances to some destination.
AbstractDataSink() - Constructor for class weka.gui.beans.AbstractDataSink
AbstractDataSinkBeanInfo - Class in weka.gui.beans: Bean info class for the AbstractDataSink
AbstractDataSinkBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSinkBeanInfo
AbstractDataSource - Class in weka.gui.beans: Abstract class for objects that can provide instances from some source
AbstractDataSource() - Constructor for class weka.gui.beans.AbstractDataSource: Creates a new AbstractDataSource instance.
AbstractDataSourceBeanInfo - Class in weka.gui.beans: Bean info class for AbstractDataSource.
AbstractDataSourceBeanInfo() - Constructor for class weka.gui.beans.AbstractDataSourceBeanInfo
AbstractDensityBasedClusterer - Class in weka.clusterers: Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie.
AbstractDensityBasedClusterer() - Constructor for class weka.clusterers.AbstractDensityBasedClusterer
AbstractEvaluationMetric - Class in weka.classifiers.evaluation: Abstract base class for pluggable classification/regression evaluation metrics.
AbstractEvaluationMetric() - Constructor for class weka.classifiers.evaluation.AbstractEvaluationMetric
AbstractEvaluationMetric.UnknownStatisticException - Exception in weka.classifiers.evaluation: Exception for subclasses to throw if asked for a statistic that is not part of their implementation
AbstractEvaluator - Class in weka.gui.beans: Abstract class for objects that can provide some kind of evaluation for classifier, clusterers etc.
AbstractEvaluator() - Constructor for class weka.gui.beans.AbstractEvaluator: Constructor
AbstractFileBasedStopwords - Class in weka.core.stopwords: Ancestor for file-based stopword schemes.
AbstractFileBasedStopwords() - Constructor for class weka.core.stopwords.AbstractFileBasedStopwords
AbstractFileLoader - Class in weka.core.converters: Abstract superclass for all file loaders.
AbstractFileLoader() - Constructor for class weka.core.converters.AbstractFileLoader
AbstractFileSaver - Class in weka.core.converters: Abstract class for Savers that save to a file Valid options are: -i input arff file
The input filw in arff format.
AbstractFileSaver() - Constructor for class weka.core.converters.AbstractFileSaver
AbstractGraphicalCommand - Class in weka.gui.knowledgeflow: Base class for a graphical command
AbstractGraphicalCommand() - Constructor for class weka.gui.knowledgeflow.AbstractGraphicalCommand
AbstractGUIApplication - Class in weka.gui: Base class for GUI applications in Weka
AbstractGUIApplication() - Constructor for class weka.gui.AbstractGUIApplication: Default constructor
AbstractGUIApplication(boolean, String[], String[]) - Constructor for class weka.gui.AbstractGUIApplication: Constructor
AbstractGUIApplication(boolean, String...) - Constructor for class weka.gui.AbstractGUIApplication: Constructor
AbstractInstance - Class in weka.core: Abstract class providing common functionality for the original instance implementations.
AbstractInstance() - Constructor for class weka.core.AbstractInstance
AbstractLoader - Class in weka.core.converters: Abstract class gives default implementation of setSource methods.
AbstractLoader() - Constructor for class weka.core.converters.AbstractLoader
AbstractOffscreenChartRenderer - Class in weka.gui.beans: Abstract base class for offscreen chart renderers.
AbstractOffscreenChartRenderer() - Constructor for class weka.gui.beans.AbstractOffscreenChartRenderer
AbstractOutput - Class in weka.classifiers.evaluation.output.prediction: A superclass for outputting the classifications of a classifier.
AbstractOutput() - Constructor for class weka.classifiers.evaluation.output.prediction.AbstractOutput: Initializes the output class.
AbstractPerspective - Class in weka.gui: Base classes for GUI perspectives to extend.
AbstractPerspective() - Constructor for class weka.gui.AbstractPerspective: Constructor
AbstractPerspective(String, String) - Constructor for class weka.gui.AbstractPerspective: Constructor
AbstractPlotInstances - Class in weka.gui.explorer: Abstract superclass for generating plottable instances.
AbstractPlotInstances() - Constructor for class weka.gui.explorer.AbstractPlotInstances: Initializes the container.
AbstractPMMLProducerHelper - Class in weka.classifiers.pmml.producer: Abstract base class for PMMLProducer helper classes to extend.
AbstractPMMLProducerHelper() - Constructor for class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper
AbstractSaver - Class in weka.core.converters: Abstract class for Saver
AbstractSaver() - Constructor for class weka.core.converters.AbstractSaver
AbstractSetupPanel - Class in weka.gui.experiment: Ancestor for setup panels for experiments.
AbstractSetupPanel() - Constructor for class weka.gui.experiment.AbstractSetupPanel
AbstractStopwords - Class in weka.core.stopwords: Ancestor for stopwords classes.
AbstractStopwords() - Constructor for class weka.core.stopwords.AbstractStopwords
AbstractTestSetProducer - Class in weka.gui.beans: Abstract class for TestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTestSetProducer() - Constructor for class weka.gui.beans.AbstractTestSetProducer: Creates a new AbstractTestSetProducer instance.
AbstractTestSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTestSetProducer
AbstractTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTestSetProducerBeanInfo
AbstractTimeSeries - Class in weka.filters.unsupervised.attribute: An abstract instance filter that assumes instances form time-series data and performs some merging of attribute values in the current instance with attribute attribute values of some previous (or future) instance.
AbstractTimeSeries() - Constructor for class weka.filters.unsupervised.attribute.AbstractTimeSeries
AbstractTrainAndTestSetProducer - Class in weka.gui.beans: Abstract base class for TrainAndTestSetProducers that contains default implementations of add/remove listener methods and defualt visual representation.
AbstractTrainAndTestSetProducer() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducer: Creates a new AbstractTrainAndTestSetProducer instance.
AbstractTrainAndTestSetProducerBeanInfo - Class in weka.gui.beans: Bean info class for AbstractTrainAndTestSetProducers
AbstractTrainAndTestSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
AbstractTrainingSetProducer - Class in weka.gui.beans: Abstract class for TrainingSetProducers that contains default implementations of add/remove listener methods and default visual representation
AbstractTrainingSetProducer() - Constructor for class weka.gui.beans.AbstractTrainingSetProducer: Creates a new AbstractTrainingSetProducer instance.
AbstractTrainingSetProducerBeanInfo - Class in weka.gui.beans: BeanInfo class for AbstractTrainingSetProducer
AbstractTrainingSetProducerBeanInfo() - Constructor for class weka.gui.beans.AbstractTrainingSetProducerBeanInfo
accept(File) - Method in class weka.core.ClassCache.ClassFileFilter: Checks whether the file is a class.
accept(File) - Method in class weka.core.ClassCache.DirectoryFilter: Checks whether the file is a directory.
accept(File) - Method in class weka.gui.ExtensionFileFilter: Returns true if the supplied file should be accepted (i.e.: if it has the required extension or is a directory).
accept(File, String) - Method in class weka.gui.ExtensionFileFilter: Returns true if the file in the given directory with the given name should be accepted.
ACCEPT - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: States that the user has accepted the tree.
acceptAssociationRules(BatchAssociationRulesEvent) - Method in interface weka.gui.beans.BatchAssociationRulesListener: Accept a BatchAssociationRulesEvent
acceptClassifier(BatchClassifierEvent) - Method in interface weka.gui.beans.BatchClassifierListener: Accept a BatchClassifierEvent
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Accept a classifier to be evaluated.
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Accepts and processes a classifier encapsulated in an incremental classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in interface weka.gui.beans.IncrementalClassifierListener: Accept the event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process an incremental classifier event
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch classifier event
acceptClassifier(IncrementalClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save an incrementally trained classifier.
acceptClassifier(BatchClassifierEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained classifier.
acceptClusterer(BatchClustererEvent) - Method in interface weka.gui.beans.BatchClustererListener: Accept a BatchClustererEvent
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Accept a clusterer to be evaluated
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.PredictionAppender: Accept and process a batch clusterer event
acceptClusterer(BatchClustererEvent) - Method in class weka.gui.beans.SerializedModelSaver: Accept and save a batch trained clusterer.
acceptConfiguration(ConfigurationEvent) - Method in interface weka.gui.beans.ConfigurationListener: Implementers do not have to do anything in this method (see the above documentation).
acceptDataPoint(ChartEvent) - Method in interface weka.gui.beans.ChartListener
acceptDataPoint(ChartEvent) - Method in class weka.gui.beans.StripChart: Accept a data point (encapsulated in a chart event) to plot
acceptDataPoint(double[]) - Method in class weka.gui.beans.StripChart: Accept a data point to plot
acceptDataPoint(double[]) - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Accept and process a data point
acceptDataPoint(double[]) - Method in interface weka.knowledgeflow.steps.StripChart.PlotNotificationListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a threshold data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Subclass must implement
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Associator
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.ClassValuePicker
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.CostBenefitAnalysis: Accept a threshold data event and set up the visualization.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in interface weka.gui.beans.DataSourceListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Filter: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Join: Accept and process a data set
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a threshold curve.
acceptDataSet(VisualizableErrorEvent) - Method in class weka.gui.beans.ModelPerformanceChart: Display a scheme error plot.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a dataset event and starts the writing process in batch mode
acceptDataSet(ThresholdDataEvent) - Method in class weka.gui.beans.Saver: Method reacts to a threshold data event ans starts the writing process in batch mode.
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TestSetMaker: Accepts and processes a data set event
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a data set for displaying as text
acceptDataSet(ThresholdDataEvent) - Method in interface weka.gui.beans.ThresholdDataListener
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainingSetMaker: Accept a data set
acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a data set
acceptDataSet(VisualizableErrorEvent) - Method in interface weka.gui.beans.VisualizableErrorListener
acceptGraph(GraphEvent) - Method in interface weka.gui.beans.GraphListener: Describe acceptGraph method here.
acceptGraph(GraphEvent) - Method in class weka.gui.beans.GraphViewer: Accept a graph
acceptImage(ImageEvent) - Method in interface weka.gui.beans.ImageListener: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageSaver: Accept and process an ImageEvent
acceptImage(ImageEvent) - Method in class weka.gui.beans.ImageViewer
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept an instance
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Appender: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.ClassAssigner
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Classifier: Accepts an instance for incremental processing.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Filter: Accept an instance for processing by StreamableFilters only
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.FlowByExpression
acceptInstance(InstanceEvent) - Method in interface weka.gui.beans.InstanceListener: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Accept an instance to add to the batch.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Join
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Saver: Methods reacts to instance events and saves instances incrementally.
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.Sorter: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.StripChart
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process an instance event
acceptInstance(InstanceEvent) - Method in class weka.gui.beans.SubstringReplacer: Accept and process an instance event
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.AveragingResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.CSVResultListener: Just prints out each result as it is received.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultListener: Submit the result to the appropriate table of the database
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.InstancesResultListener: Collects each instance and adjusts the header information.
acceptResult(ResultProducer, Object[], Object[]) - Method in class weka.experiment.LearningRateResultProducer: Accepts results from a ResultProducer.
acceptResult(ResultProducer, Object[], Object[]) - Method in interface weka.experiment.ResultListener: Accepts results from a ResultProducer.
acceptsInstances() - Method in class weka.gui.AbstractPerspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.beans.AttributeSummarizer: Returns true if this perspective accepts instances
acceptsInstances() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
acceptsInstances() - Method in class weka.gui.beans.ScatterPlotMatrix: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.beans.SQLViewerPerspective: Returns true if this perspective accepts instances
acceptsInstances() - Method in class weka.gui.explorer.AssociationsPanel
acceptsInstances() - Method in class weka.gui.explorer.AttributeSelectionPanel
acceptsInstances() - Method in class weka.gui.explorer.ClassifierPanel
acceptsInstances() - Method in class weka.gui.explorer.ClustererPanel
acceptsInstances() - Method in class weka.gui.explorer.PreprocessPanel: We can accept instances
acceptsInstances() - Method in class weka.gui.explorer.VisualizePanel: This perspective processes instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Returns true, as this perspective does accept instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Returns true - we accept instances.
acceptsInstances() - Method in interface weka.gui.Perspective: Returns true if this perspective can do something meaningful with a set of instances
acceptsInstances() - Method in class weka.gui.SimpleCLIPanel
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a test set for a batch trained classifier
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a test set for a batch trained clusterer
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Filter: Accept a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Join: Accept and process a test set
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a test set event and starts the writing process in batch mode
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in interface weka.gui.beans.TestSetListener: Accept and process a test set event
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a test set for displaying as text
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainingSetMaker
acceptTestSet(TestSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a test set
acceptText(TextEvent) - Method in interface weka.gui.beans.TextListener: Accept and process a text event
acceptText(TextEvent) - Method in class weka.gui.beans.TextSaver: Accept and process an TextEvent
acceptText(TextEvent) - Method in class weka.gui.beans.TextViewer: Accept some text
acceptTextResult(String, String) - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Accept a new text result and add it to the result list
acceptTextResult(String, String) - Method in interface weka.knowledgeflow.steps.TextViewer.TextNotificationListener: Accept a new textual result
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.AbstractDataSink: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Appender: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Associator: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.ClassAssigner
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Classifier: Accepts a training set and builds batch classifier
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Clusterer: Accepts a training set and builds batch clusterer
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.CrossValidationFoldMaker: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.DataVisualizer: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Filter: Accept a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.FlowByExpression
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Join: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Saver: Method reacts to a training set event and starts the writing process in batch mode
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.Sorter: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.SubstringLabeler: Accept and process a training set event
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TestSetMaker
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TextViewer: Accept a training set for displaying as text
acceptTrainingSet(TrainingSetEvent) - Method in interface weka.gui.beans.TrainingSetListener: Accept and process a training set
acceptTrainingSet(TrainingSetEvent) - Method in class weka.gui.beans.TrainTestSplitMaker: Accept a training set
actEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the actual entropy
action_table() - Method in class weka.core.expressionlanguage.parser.Parser: Access to parse-action table.
action_table() - Method in class weka.core.json.Parser: Access to parse-action table.
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: invoked when an action occurs
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.AlgorithmListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.DatasetListPanel: Handle actions when buttons get pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Handles the various button clicking type activities.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.HostListPanel: Handle actions when text is entered into the host field or the delete button is pressed.
actionPerformed(ActionEvent) - Method in class weka.gui.experiment.RunPanel: Controls starting and stopping the experiment.
actionPerformed(ActionEvent) - Method in class weka.gui.SimpleCLIPanel: Only gets called when return is pressed in the input area, which starts the command running.
actionPerformed(ActionEvent) - Method in class weka.gui.streams.InstanceLoader
actionPerformed(ActionEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs the action associated with the ActionEvent.
activateFilter(boolean) - Method in class weka.gui.knowledgeflow.InvisibleTreeModel: Activate/deactivate the visibility filter
ACTIVATIONFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for ACTIVATION-FUNCTION.
ActiveHNode - Class in weka.classifiers.trees.ht: Node that is "active" (i.e.
ActiveHNode() - Constructor for class weka.classifiers.trees.ht.ActiveHNode
actual() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the actual class value.
actual() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the actual class value.
actual() - Method in interface weka.classifiers.evaluation.Prediction: Gets the actual class value.
actualNumBags() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of non-empty bags of distribution.
actualNumClasses() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in distribution.
actualNumClasses(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes actually occuring in given bag.
acuityTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
AdaBoostM1 - Class in weka.classifiers.meta: Class for boosting a nominal class classifier using the Adaboost M1 method.
AdaBoostM1() - Constructor for class weka.classifiers.meta.AdaBoostM1: Constructor.
add(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to given bag.
add(int, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds counts to given bag.
add(AlgVector) - Method in class weka.core.AlgVector: Returns the sum of this vector with another.
add(String) - Method in class weka.core.ClassCache: Adds the classname to the cache.
add(Defaults) - Method in class weka.core.Defaults: Add the supplied defaults to this one.
add(Instance) - Method in class weka.core.Instances: Adds one instance to the end of the set.
add(int, Instance) - Method in class weka.core.Instances: Adds one instance at the given position in the list.
add(Matrix) - Method in class weka.core.Matrix: Deprecated.

Returns the sum of this matrix with another.
add(String) - Method in class weka.core.Stopwords: adds the given word to the stopword list (is automatically converted to lower case and trimmed)
add(TechnicalInformation) - Method in class weka.core.TechnicalInformation: adds the given information to the list of additional technical informations
add(TechnicalInformation.Type) - Method in class weka.core.TechnicalInformation: Adds an empty technical information with the given type to the list of additional informations and returns the instance.
add(PrintStream) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO timestamp and NO prefix.
add(PrintStream, boolean) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams, with NO prefix.
add(PrintStream, boolean, String) - Method in class weka.core.Tee: adds the given PrintStream to the list of streams.
add(String) - Method in class weka.core.Trie: Ensures that this collection contains the specified element.
add(String) - Method in class weka.core.Trie.TrieNode: adds the given string to its children (creates children if necessary)
add(String, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the property with the given displayname to its internal list.
add(Class<?>, Method) - Method in class weka.core.xml.MethodHandler: adds the specified method for the given class to its internal list.
add(double, double) - Method in class weka.experiment.PairedStats: Add an observed pair of values.
add(double[], double[]) - Method in class weka.experiment.PairedStats: Adds an array of observed pair of values.
add(double) - Method in class weka.experiment.Stats: Adds a value to the observed values
add(double, double) - Method in class weka.experiment.Stats: Adds a weighted value to the observed values
Add - Class in weka.filters.unsupervised.attribute: An instance filter that adds a new attribute to the dataset.
Add() - Constructor for class weka.filters.unsupervised.attribute.Add
add(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Inserts the specified element at the specified position in this list.
add(Object) - Method in class weka.gui.GenericObjectEditorHistory: Adds the object to the history.
add(String) - Method in class weka.gui.HierarchyPropertyParser: Add the given item of property to the tree
ADD_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
addActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Register a listener to be notified when plotting completes
addActionListener(ActionListener) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Add a listener interested in kowing about editor status changes
addActionListener(ActionListener) - Method in class weka.gui.visualize.ClassPanel: Add an action listener that will be notified if the user changes the colour of a label
addActionListener(ActionListener) - Method in class weka.gui.visualize.VisualizePanel: Add a listener for this visualize panel
addAll(Collection<? extends T>) - Method in class weka.core.neighboursearch.covertrees.Stack: Adds all the given elements in the stack.
addAll(Collection<? extends String>) - Method in class weka.core.Trie: Adds all of the elements in the specified collection to this collection
addAll(List<StepManagerImpl>) - Method in class weka.knowledgeflow.Flow: All all steps in the supplied list to this Flow
addAllBeansToContainer(JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance: Adds all beans to the supplied component
addAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given property (display name) to the list of allowed properties for the specified class.
addAllResults(Map<String, LinkedHashSet<Data>>) - Method in class weka.knowledgeflow.JobEnvironment: Add all the results from the supplied map to this environment's results
addAndUpdate(Rule) - Method in class weka.classifiers.rules.RuleStats: Add a rule to the ruleset and update the stats
addArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between two nodes Distributions are updated by duplication for every value of the parent node.
addArc(String, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add arc between parent node and each of the nodes in a given list.
addArray(String) - Method in class weka.core.json.JSONNode: Adds an array child to the object.
addArrayElement(Object) - Method in class weka.core.json.JSONNode: Adds an array element child to the array.
addAssociationModelOrBaselineModelOrClusteringModes(Object) - Method in class weka.core.pmml.jaxbbindings.PMML
addAttributePanelListener(AttributePanelListener) - Method in class weka.gui.visualize.AttributePanel: Add a listener to the list of things listening to this panel
addAttributeSpec(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Add an attribute spec to the list
addBatchAssociationRulesListener(BatchAssociationRulesListener) - Method in class weka.gui.beans.Associator: Add a batch association rules listener
addBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier: Add a batch classifier listener
addBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer: Add a batch clusterer listener
addBean(JComponent, Integer...) - Method in class weka.gui.beans.BeanInstance: Adds this bean to the global list of beans and to the supplied container.
addBeanInstances(Vector<Object>, JComponent) - Static method in class weka.gui.beans.BeanInstance: Adds the supplied collection of beans to the end of the list of collections and to the JComponent container (if not null)
addBoolean(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a boolean variable
addButton(JButton) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Adds a button to the bottom of the window.
addCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the cancel button.
addCapabilities(String) - Method in class weka.core.Capabilities: generates a string from the capabilities, suitable to add to the help text.
addCapabilities(String, Capabilities) - Static method in class weka.core.CapabilitiesUtils: generates a string from the capabilities, suitable to add to the help text.
addCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer: adds the listener to the list of objects that listen for changes of the CapabilitiesFilter
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel: Adds a ChangeListener to the panel
addChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable: Adds a ChangeListener to the panel
addChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a chart listener
addCheckBoxActionListener(ActionListener) - Method in class weka.gui.experiment.DistributeExperimentPanel: Enable objects to listen for changes to the check box
addChild(Edge) - Method in class weka.gui.treevisualizer.Node: Set the value of children.
addChild(FlowByExpression.ExpressionNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode: Add a child to this bracket node
addChildClique(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
addChildFrame(Container) - Method in class weka.gui.GUIChooserApp: adds the given child frame to the list of frames.
addChildFrame(Container) - Method in class weka.gui.Main: adds the given child frame to the list of frames.
AddClassification - Class in weka.filters.supervised.attribute: A filter for adding the classification, the class distribution and an error flag to a dataset with a classifier.
AddClassification() - Constructor for class weka.filters.supervised.attribute.AddClassification
AddCluster - Class in weka.filters.unsupervised.attribute: A filter that adds a new nominal attribute representing the cluster assigned to each instance by the specified clustering algorithm.
Either the clustering algorithm gets built with the first batch of data or one specifies are serialized clusterer model file to use instead.
AddCluster() - Constructor for class weka.filters.unsupervised.attribute.AddCluster
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addConnections(Vector<BeanConnection>) - Static method in class weka.gui.beans.BeanConnection: Add the supplied collection of connections to the end of the list.
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel
addContent(Object) - Method in class weka.core.pmml.jaxbbindings.RegressionModel
addCVParameter(String) - Method in class weka.classifiers.meta.CVParameterSelection: Adds a scheme parameter to the list of parameters to be set by cross-validation
addDataDictionary(Instances, PMML) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Adds a data dictionary to the supplied PMML object.
addDataField(DataField) - Method in class weka.core.pmml.jaxbbindings.DataDictionary
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
addDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Appender: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
addDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.FlowByExpression
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Join: Add a data source listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader: Add a listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Sorter: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringLabeler: Add a datasource listener
addDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringReplacer: Add a data source listener
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.LocalTransformations
addDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary
addDouble(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a double variable
addElement(E) - Method in class weka.core.FastVector: Deprecated.

Adds an element to this vector.
addElement(int, int, double) - Method in class weka.core.Matrix: Deprecated.

Add a value to an element.
addElement(double) - Method in class weka.core.matrix.DoubleVector: Adds an element into the vector
addElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Adds the specified component to the end of this list.
addEmptyRow() - Method in class weka.gui.InteractiveTableModel: Adds an empty row to the model
addErrs(double, double, float) - Static method in class weka.classifiers.trees.j48.Stats: Computes estimated extra error for given total number of instances and error using normal approximation to binomial distribution (and continuity correction).
addExecutionFinishedCallback(ExecutionFinishedCallback) - Method in interface weka.knowledgeflow.FlowExecutor: Add a callback to notify when execution finishes
addExecutionFinishedCallback(ExecutionFinishedCallback) - Method in class weka.knowledgeflow.FlowRunner: Set a callback to notify when flow execution finishes
AddExpression - Class in weka.filters.unsupervised.attribute: An instance filter that creates a new attribute by applying a mathematical expression to existing attributes.
AddExpression() - Constructor for class weka.filters.unsupervised.attribute.AddExpression
addFile(String) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFile(File) - Static method in class weka.core.ClassloaderUtil: Add file to CLASSPATH
addFileFilter(FileFilter) - Method in class weka.gui.beans.FileEnvironmentField: Deprecated.

Add a file filter to use
addFileFilter(FileFilter) - Method in class weka.gui.FileEnvironmentField: Add a file filter to use
addFromProperties(File) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(String, File) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(File, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(String, File, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied property file
addFromProperties(InputStream) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(String, InputStream) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(InputStream, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(String, InputStream, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties stream
addFromProperties(Properties) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(String, Properties) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(Properties, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(String, Properties, boolean) - Static method in class weka.core.PluginManager: Add all key value pairs from the supplied properties object
addFromProperties(File) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied property file
addFromProperties(File, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied property file
addFromProperties(InputStream) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties stream
addFromProperties(InputStream, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties stream
addFromProperties(Properties) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties object
addFromProperties(Properties, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add all key value pairs from the supplied properties object
addGraphListener(GraphListener) - Method in class weka.gui.beans.Associator: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier: Add a graph listener
addGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer: Add a graph listener
addHeader(String, String) - Method in class weka.experiment.ResultMatrix: adds the key-value pair to the header.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
AddID - Class in weka.filters.unsupervised.attribute: An instance filter that adds an ID attribute to the dataset.
AddID() - Constructor for class weka.filters.unsupervised.attribute.AddID
addIgnored(String) - Method in class weka.core.xml.PropertyHandler: adds the given display name of a property to the ignore list.
addIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: adds the given class with the display name of a property to the ignore list.
addImageListener(ImageListener) - Method in class weka.gui.beans.DataVisualizer: Add an image listener
addImageListener(ImageListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add an image listener
addIncomingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Add an incoming connection (comprising of the type of connection and associated step component) to this step of the specified type
addIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier: Add an incremental classifier listener
addIndexedValueToNamedStore(String, Integer, Object) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Adds a value to a named store with the given index.
addInstance(Instance) - Method in class weka.clusterers.Cobweb: Deprecated.
updateClusterer(Instance) should be used instead
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Adds an instance to the ball tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Adds an instance to the tree.
addInstance(BallNode, Instance) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Adds an instance to the ball tree.
addInstance() - Method in class weka.gui.arffviewer.ArffPanel: Add an instance at the currently selected index.
addInstanceAtEnd() - Method in class weka.gui.arffviewer.ArffPanel: Add an instance at the end of the dataset
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.BallTree: Adds the given instance's info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.CoverTree: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Updates the instance info in the underlying search method, once the instance has been filtered.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.KDTree: Adds one instance to KDTree loosly.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Adds the given instance info.
addInstanceInfo(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Adds information from the given instance without modifying the datastructure a lot.
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Appender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
addInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.FlowByExpression
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Join: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.Sorter: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringLabeler: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringReplacer: Add an instance listener
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
addInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
addInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
addInstanceNumberAttribute() - Method in class weka.gui.visualize.PlotData2D: Adds an instance number attribute to the plottable instances,
addInstWithUnknown(Instances, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances with unknown values for given attribute, weighted according to frequency of instances in each bag.
additional() - Method in class weka.core.TechnicalInformation: returns an enumeration of all the additional technical informations (if there are any)
AdditionalMeasureProducer - Interface in weka.core: Interface to something that can produce measures other than those calculated by evaluation modules.
AdditiveRegression - Class in weka.classifiers.meta: Meta classifier that enhances the performance of a regression base classifier.
AdditiveRegression() - Constructor for class weka.classifiers.meta.AdditiveRegression: Default constructor specifying DecisionStump as the classifier
AdditiveRegression(Classifier) - Constructor for class weka.classifiers.meta.AdditiveRegression: Constructor which takes base classifier as argument.
addKeyword(String, MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates a keyword with a particular formatting style.
addKeywords(String[], MutableAttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Associates the keywords with a particular formatting style.
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Method to add a LayoutCompleteEventListener
addLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method adds a LayoutCompleteEventListener to the LayoutEngine.
addMiningFields(MiningField) - Method in class weka.core.pmml.jaxbbindings.MiningSchema
addModel(SimpleLinearRegression) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Takes the given simple linear regression model and adds it to this one.
addMouseListener(MouseListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a mouse listener.
addMouseListenerToHeader(JTable) - Method in class weka.gui.SortedTableModel: Adds a mouselistener to the header: left-click on the header sorts in ascending manner, using shift-left-click in descending manner.
addNode(String, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add new node to the network, initializing instances, parentsets, distributions.
addNode(String, int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node to network at a given position, initializing instances, parentsets, distributions.
addNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Add node value to a node.
AddNoise - Class in weka.filters.unsupervised.attribute: An instance filter that changes a percentage of a given attribute's values.
AddNoise() - Constructor for class weka.filters.unsupervised.attribute.AddNoise
addNoise(Instances, int, int, int, boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise: add noise to the dataset a given percentage of the instances are changed in the way that a set of instances are randomly selected using seed.
addNull(String) - Method in class weka.core.json.JSONNode: Adds a "null" child to the object.
addNullArrayElement() - Method in class weka.core.json.JSONNode: Adds a null array element child to the array.
addNumericPredictor(NumericPredictor) - Method in class weka.core.pmml.jaxbbindings.RegressionTable
addObject(String) - Method in class weka.core.json.JSONNode: Adds an object child to the object.
addObject(String, Object) - Method in class weka.gui.ResultHistoryPanel: Adds an object to the results list.
addObjectArrayElement() - Method in class weka.core.json.JSONNode: Add a key-value object child into the array
addOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to hook an action listener to the ok button.
addOrOverwriteObject(String, Object) - Method in class weka.gui.ResultHistoryPanel: Adds an object to the result list.
addOutgoingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Add an outgoing connection (comprising of the type of connection and associated target step) to this step of the specified type.
addOutgoingConnection(String, StepManagerImpl, boolean) - Method in class weka.knowledgeflow.StepManagerImpl: Add an outgoing connection (comprising of the type of connection and associated target step) to this step of the specified type.
addOutputField(OutputField) - Method in class weka.core.pmml.jaxbbindings.Output
addPackageToClassLoader(File) - Method in class weka.core.WekaPackageClassLoaderManager: Create a class loader for the given package directory
addParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set and update internals (specifically the cardinality of the parent set)
addParent(int, int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Add parent to parent set at specific location and update internals (specifically the cardinality of the parent set)
addPCell(PCell) - Method in class weka.core.pmml.jaxbbindings.ParamMatrix
addPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D: Add a plot to the list of plots to display
addPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel: Set a new plot to the visualize panel
addPlotNotificationListener(StripChart.PlotNotificationListener) - Method in class weka.knowledgeflow.steps.StripChart: Add a plot notification listener
addPlugin(String, String, String) - Static method in class weka.core.PluginManager: Add a plugin.
addPlugin(String, String, String, boolean) - Static method in class weka.core.PluginManager: Add a plugin.
addPlugin(String, String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a plugin.
addPlugin(String, String, String, boolean) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a plugin.
addPluginResource(String, String, String) - Static method in class weka.core.PluginManager: Add a resource.
addPluginResource(String, String, String, String) - Static method in class weka.core.PluginManager: Add a resource.
addPluginResource(String, String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add a resource.
addPluginResourcesFromProperty(String) - Static method in class weka.core.PluginManager: Add resources from a list.
addPreBuiltClassifier(Classifier) - Method in class weka.classifiers.meta.Vote: Add a prebuilt classifier to the list for use in the ensemble
addPrediction(NominalPrediction) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a prediction in the confusion matrix.
addPredictions(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Includes a whole bunch of predictions in the confusion matrix.
addPrimitive(String, Boolean) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Integer) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, Double) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPrimitive(String, String) - Method in class weka.core.json.JSONNode: Adds a key-value child to the object.
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual: Add a listener for property change events
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer: Add a property change listener
addPropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer: Add a property change listener to this bean
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer: Add a property change listener
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.ColorEditor
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor: Adds an object to the list of those that wish to be informed when the cost matrix changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.EnvironmentField
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.AbstractSetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PasswordField
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel: Adds a PropertyChangeListener.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel: Adds a PropertyChangeListener who will be notified of value changes.
addPropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor: Adds an object to the list of those that wish to be informed when the date format changes.
addPropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
addPSFontReplacement(String, String) - Static method in class weka.gui.visualize.PostscriptGraphics: adds the PS font name to replace and its replacement in the replacement hashtable
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel: adds the given listener to the list of listeners.
addQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Adds all instances in given range to given bag.
addRelation(Instances) - Method in class weka.core.Attribute: Adds a relation to a relation-valued attribute.
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.experiment.RemoteExperiment: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteExperimentListener(RemoteExperimentListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Add an object to the list of those interested in recieving update information from the RemoteExperiment
addRemoteHost(String) - Method in class weka.experiment.RemoteExperiment: Add a host name to the list of remote hosts
addRenderingHints(Map<?, ?>) - Method in class weka.gui.visualize.PostscriptGraphics
addRepaintNotify(Component) - Method in class weka.gui.visualize.ClassPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
addRepaintNotify(Component) - Method in class weka.gui.visualize.LegendPanel: Adds a component that will need to be repainted if the user changes the colour of a label.
addResult(String, StringBuffer) - Method in class weka.gui.ResultHistoryPanel: Adds a new result to the result list.
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel: adds the given listener to the list of listeners
addResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer: adds the given listener to the list of listeners.
addScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script: Adds the given listener to its internal list.
addSettingsMenuItemToProgramMenu(Settings) - Method in class weka.gui.PerspectiveManager: Applications can call this to allow access to the settings editor from the program menu (in addition to the toolbar widget that pops up the settings editor)
addStartupListener(StartUpListener) - Static method in class weka.gui.beans.KnowledgeFlowApp: Add a listener to be notified when startup is complete
addStartupListener(StartUpListener) - Static method in class weka.gui.Main: Add a listener to be notified when startup is complete.
addStep(StepManagerImpl) - Method in class weka.knowledgeflow.Flow: Add the given Step to this flow
addStepOutputListener(StepOutputListener, String) - Method in class weka.knowledgeflow.StepManagerImpl: Register non-step third party to receive data from the managed step for the specified outgoing connection type.
addString(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Adds a variable declaration for a string variable
addStringValue(String) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addStringValue(Attribute, int) - Method in class weka.core.Attribute: Adds a string value to the list of valid strings for attributes of type STRING and returns the index of the string.
addTab(String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
addTab(String) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Add a new titled tab to the UI
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel: adds a listener to the list that is notified each time a change to data model occurs
addTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel: adds a listener to the list that is notified each time a change to data model occurs.
addTarget(Target) - Method in class weka.core.pmml.jaxbbindings.Targets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer: Add a listener for test sets
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter: Add a test set listener
addTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a test set listener
addTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer: Add a listener for test set events
addTextListener(TextListener) - Method in class weka.gui.beans.Associator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Classifier: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.Clusterer: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Add a text listener
addTextListener(TextListener) - Method in class weka.gui.beans.TextViewer: Add a text listener
addThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a threshold data listener
addTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel: Adds the listener to the internal list.
addToDisabledList(List<String>) - Static method in class weka.core.PluginManager: Add the supplied list of fully qualified class names to the disabled list
addToDisabledList(String) - Static method in class weka.core.PluginManager: Add the supplied fully qualified class name to the list of disabled plugins
addToDisabledList(List<String>) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add the supplied list of fully qualified class names to the disabled list
addToDisabledList(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Add the supplied fully qualified class name to the list of disabled plugins
addToHistory() - Method in class weka.gui.PropertyPanel: Adds the current editor value to the history.
addToHistory(Object) - Method in class weka.gui.PropertyPanel: Adds the specified value to the history.
addToList(Object[], double) - Method in class weka.attributeSelection.BestFirst.LinkedList2: adds an element (Link) to the list.
addToPluginBeanProps(File) - Static method in class weka.gui.beans.BeansProperties
addToPluginBeanProps(File) - Static method in class weka.gui.beans.KnowledgeFlowApp: Add a plugin bean props file
addToResult(Data) - Method in class weka.knowledgeflow.JobEnvironment: Add a non-incremental data object to the result
addToStepProperties(Map<String, Map<String, String>>) - Method in class weka.knowledgeflow.JobEnvironment: Add the supplied map of step properties.
addTrainingInstance(Instance) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to the visualization dataset.
addTrainingInstanceFromMouseLocation(int, int, int, double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Adds a training instance to our dataset, based on the coordinates of the mouse on the panel.
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender: Add a training set listener
addTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer: Add a training set listener
addUndoPoint() - Method in interface weka.core.Undoable: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffPanel: adds the current state of the instances to the undolist
addUndoPoint() - Method in class weka.gui.arffviewer.ArffSortedTableModel: adds an undo point to the undo history
addUndoPoint() - Method in class weka.gui.arffviewer.ArffTableModel: adds an undo point to the undo history, if the undo support is enabled
addUndoPoint() - Method in class weka.gui.explorer.PreprocessPanel: Backs up the current state of the dataset, so the changes can be undone.
addUntitledTab() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Add a new untitled tab to the UI
addURL(URL) - Static method in class weka.core.ClassloaderUtil: Add URL to CLASSPATH
AddUserFields - Class in weka.filters.unsupervised.attribute: A filter that adds new attributes with user specified type and constant value.
AddUserFields() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields: Constructs a new AddUserFields
AddUserFields.AttributeSpec - Class in weka.filters.unsupervised.attribute: Inner class encapsulating a new user-specified attribute to create.
AddUserFieldsBeanInfo - Class in weka.filters.unsupervised.attribute: Bean info class for the AddUserFields filter.
AddUserFieldsBeanInfo() - Constructor for class weka.filters.unsupervised.attribute.AddUserFieldsBeanInfo
AddUserFieldsCustomizer - Class in weka.gui.filters: Customizer for the AddUserFields filter.
AddUserFieldsCustomizer() - Constructor for class weka.gui.filters.AddUserFieldsCustomizer: Constructor
addValue(double, double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Add a new data value to the current estimator.
addValue(Value) - Method in class weka.core.pmml.jaxbbindings.DataField
addValue(double, double, double) - Method in interface weka.estimators.ConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.DiscreteEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.DNConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.Estimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.IncrementalEstimator: Add one value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.KernelEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.KKConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.MahalanobisEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NDConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double, double) - Method in class weka.estimators.NNConditionalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.NormalEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in class weka.estimators.PoissonEstimator: Add a new data value to the current estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateDensityEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateIntervalEstimator: Adds a value to the interval estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateKernelEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateMixtureEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in class weka.estimators.UnivariateNormalEstimator: Adds a value to the density estimator.
addValue(double, double) - Method in interface weka.estimators.UnivariateQuantileEstimator: Adds a value to the interval estimator.
addValues(Instances, int) - Method in class weka.estimators.Estimator: Initialize the estimator with a new dataset.
addValues(Instances, int, double, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator with all values of one attribute of a dataset.
addValues(Instances, int, int, int) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instances of one class.
addValues(Instances, int, int, int, double, double) - Method in class weka.estimators.Estimator: Initialize the estimator using only the instances of one class.
AddValues - Class in weka.filters.unsupervised.attribute: Adds the labels from the given list to an attribute if they are missing.
AddValues() - Constructor for class weka.filters.unsupervised.attribute.AddValues
addVariable(String, String) - Method in class weka.core.Environment: Add a variable to the internal map of this properties object.
addVariableSystemWide(String, String) - Method in class weka.core.Environment: Add a a variable to the internal map of this properties object and to the global system-wide environment;
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.CostBenefitAnalysis
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Add a vetoable change listener to this bean
addVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer: Add a vetoable change listener to this bean
addVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Add a visualizable error listener
addWeights(Instance, double[]) - Method in class weka.classifiers.trees.j48.Distribution: Adds given instance to all bags weighting it according to given weights.
adjustCenter(double) - Method in class weka.gui.treevisualizer.Node: Will increase or decrease the postion of center.
adjustWeightsTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
ADNode - Class in weka.classifiers.bayes.net: The ADNode class implements the ADTree datastructure which increases the speed with which sub-contingency tables can be constructed from a data set in an Instances object.
ADNode() - Constructor for class weka.classifiers.bayes.net.ADNode: Creates new ADNode
advanceCounters() - Method in class weka.experiment.Experiment: Increments iteration counters appropriately.
advanceCounters() - Method in class weka.experiment.RemoteExperiment: overides the one in Experiment
aggregate(Evaluation) - Method in class weka.classifiers.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(NaiveBayes) - Method in class weka.classifiers.bayes.NaiveBayes
aggregate(NaiveBayesMultinomialText) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
aggregate(Evaluation) - Method in class weka.classifiers.evaluation.AggregateableEvaluation: Adds the statistics encapsulated in the supplied Evaluation object into this one.
aggregate(Logistic) - Method in class weka.classifiers.functions.Logistic: Aggregate an object with this one
aggregate(SGD) - Method in class weka.classifiers.functions.SGD: Aggregate an object with this one
aggregate(SGDText) - Method in class weka.classifiers.functions.SGDText: Aggregate an object with this one
aggregate(Bagging) - Method in class weka.classifiers.meta.Bagging: Aggregate an object with this one
aggregate(Classifier) - Method in class weka.classifiers.meta.Vote: Aggregate an object with this one
aggregate(E) - Method in interface weka.core.Aggregateable: Aggregate an object with this one
aggregate(DictionaryBuilder) - Method in class weka.core.DictionaryBuilder
Aggregate - Class in weka.core.pmml.jaxbbindings: Java class for Aggregate element declaration.
Aggregate() - Constructor for class weka.core.pmml.jaxbbindings.Aggregate
aggregate(DiscreteEstimator) - Method in class weka.estimators.DiscreteEstimator
aggregate(KernelEstimator) - Method in class weka.estimators.KernelEstimator
aggregate(NormalEstimator) - Method in class weka.estimators.NormalEstimator
Aggregateable<E> - Interface in weka.core: Interface to something that can aggregate an object of the same type with itself.
AggregateableEvaluation - Class in weka.classifiers: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
AggregateableEvaluation - Class in weka.classifiers.evaluation: Subclass of Evaluation that provides a method for aggregating the results stored in another Evaluation object.
AggregateableEvaluation(Instances) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object
AggregateableEvaluation(Evaluation) - Constructor for class weka.classifiers.evaluation.AggregateableEvaluation: Constructs a new AggregateableEvaluation object based on an Evaluation object
aggregateCanopies(List<Canopy>, double, double, NormalizableDistance, Filter, int) - Static method in class weka.clusterers.Canopy: Aggregate the canopies from a list of Canopy clusterers together into one final model.
Agrawal - Class in weka.datagenerators.classifiers.classification: Generates a people database and is based on the paper by Agrawal et al.:
R.
Agrawal() - Constructor for class weka.datagenerators.classifiers.classification.Agrawal: initializes the generator with default values
AIC - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
AlgorithmListPanel - Class in weka.gui.experiment: This panel controls setting a list of algorithms for an experiment to iterate over.
AlgorithmListPanel(Experiment) - Constructor for class weka.gui.experiment.AlgorithmListPanel: Creates the algorithm list panel with the given experiment.
AlgorithmListPanel() - Constructor for class weka.gui.experiment.AlgorithmListPanel: Create the algorithm list panel initially disabled.
AlgorithmListPanel.ObjectCellRenderer - Class in weka.gui.experiment: Class required to show the Classifiers nicely in the list
AlgVector - Class in weka.core: Class for performing operations on an algebraic vector of floating-point values.
AlgVector(int) - Constructor for class weka.core.AlgVector: Constructs a vector and initializes it with default values.
AlgVector(double[]) - Constructor for class weka.core.AlgVector: Constructs a vector using a given array.
AlgVector(Instances, Random) - Constructor for class weka.core.AlgVector: Constructs a vector using a given data format.
AlgVector(Instance) - Constructor for class weka.core.AlgVector: Constructs a vector using an instance.
alignBottom(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the bottom most node in the list
alignLeft(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the left most node in the list
alignRight(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the right most node in the list
alignTop(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: align set of nodes with the top most node in the list
ALL - Static variable in class weka.core.Debug: the log level All
allAttributeWeightsIdentical() - Method in class weka.core.Instances: Returns true if all attribute weights are the same and false otherwise.
AllFilter - Class in weka.filters: A simple instance filter that passes all instances directly through.
AllFilter() - Constructor for class weka.filters.AllFilter
allInstanceWeightsIdentical() - Method in class weka.core.Instances: Returns true if all instance weights are the same and false otherwise.
AllJavadoc - Class in weka.core: Applies all known Javadoc-derived classes to a source file.
AllJavadoc() - Constructor for class weka.core.AllJavadoc
allowAccessToFullInputFormat() - Method in class weka.filters.SimpleBatchFilter: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowAccessToFullInputFormat() - Method in class weka.filters.supervised.attribute.MergeNominalValues: We need access to the full input data in determineOutputFormat.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: We need access to the full input data in determineOutputFormat.
allowAccessToFullInputFormat() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns whether to allow the determineOutputFormat(Instances) method access to the full dataset rather than just the header.
allowed() - Method in class weka.core.xml.PropertyHandler: returns an enumeration of the classnames for which only certain properties (display names) are allowed
allowUnclassifiedInstancesTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
AlphabeticTokenizer - Class in weka.core.tokenizers: Alphabetic string tokenizer, tokens are to be formed only from contiguous alphabetic sequences.
AlphabeticTokenizer() - Constructor for class weka.core.tokenizers.AlphabeticTokenizer
alphaTipText() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator
Alternate - Class in weka.core.pmml.jaxbbindings: Java class for Alternate element declaration.
Alternate() - Constructor for class weka.core.pmml.jaxbbindings.Alternate
AlterRelationName - Class in weka.knowledgeflow.steps: Step that alters the relation name for data received via instance, dataSet, trainingSet and testSet connections
AlterRelationName() - Constructor for class weka.knowledgeflow.steps.AlterRelationName
ALWAYS_SEND_INSTANCES_TO_ALL - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
ALWAYS_SEND_INSTANCES_TO_ALL_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the tip text for this property
amplitudeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
and(Capabilities) - Method in class weka.core.Capabilities: performs an AND conjunction with the capabilities of the given Capabilities object and updates itself
and(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '&' or 'and' logical and operator
AND - Static variable in interface weka.core.expressionlanguage.parser.sym
Annotation - Class in weka.core.pmml.jaxbbindings: Java class for Annotation element declaration.
Annotation() - Constructor for class weka.core.pmml.jaxbbindings.Annotation
Anova - Class in weka.core.pmml.jaxbbindings: Java class for Anova element declaration.
Anova() - Constructor for class weka.core.pmml.jaxbbindings.Anova
AnovaRow - Class in weka.core.pmml.jaxbbindings: Java class for AnovaRow element declaration.
AnovaRow() - Constructor for class weka.core.pmml.jaxbbindings.AnovaRow
Antd(Attribute) - Constructor for class weka.classifiers.rules.JRip.Antd: Constructor
AntecedentSequence - Class in weka.core.pmml.jaxbbindings: Java class for AntecedentSequence element declaration.
AntecedentSequence() - Constructor for class weka.core.pmml.jaxbbindings.AntecedentSequence
AnyDistribution - Class in weka.core.pmml.jaxbbindings: Java class for AnyDistribution element declaration.
AnyDistribution() - Constructor for class weka.core.pmml.jaxbbindings.AnyDistribution
APP_ID - Static variable in class weka.gui.GUIChooserApp.GUIChooserDefaults: ID
APP_ID - Static variable in class weka.gui.WorkbenchDefaults
APP_ID - Static variable in class weka.knowledgeflow.KFDefaults
APP_NAME - Static variable in class weka.gui.GUIChooserApp.GUIChooserDefaults: APP name (GUIChooser isn't really an "app" as such
APP_NAME - Static variable in class weka.gui.WorkbenchDefaults
APP_NAME - Static variable in class weka.knowledgeflow.KFDefaults
append(CharSequence, int, int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends a subsequence of the specified character sequence to this output stream.
append(CharSequence) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends the specified character sequence to this output stream.
append(char) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Appends the specified character to this output stream.
append(char) - Method in class weka.core.Tee: Appends the specified character to this output stream.
append(CharSequence) - Method in class weka.core.Tee: Appends the specified character sequence to this output stream.
append(CharSequence, int, int) - Method in class weka.core.Tee: Appends a subsequence of the specified character sequence to this output stream.
append(String, String) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list (with the associated icon at the beginning)
append(Object) - Method in class weka.gui.sql.InfoPanel: adds the given message to the end of the list
appendBeans(JComponent, Vector<Object>, int) - Static method in class weka.gui.beans.BeanInstance
appendConnections(Vector<BeanConnection>, int) - Static method in class weka.gui.beans.BeanConnection: Append the supplied connections to the list for the given tab index
appendElements(Collection<? extends E>) - Method in class weka.core.FastVector: Deprecated.

Appends all elements of the supplied vector to this vector.
Appender - Class in weka.gui.beans: A bean that appends multiple incoming data connections into a single data set.
Appender() - Constructor for class weka.gui.beans.Appender: Constructs a new Appender.
Appender - Class in weka.knowledgeflow.steps: A bean that appends multiple incoming data connections into a single data set.
Appender() - Constructor for class weka.knowledgeflow.steps.Appender
AppenderBeanInfo - Class in weka.gui.beans: Bean info class for the appender bean
AppenderBeanInfo() - Constructor for class weka.gui.beans.AppenderBeanInfo
appendPredictedProbabilitiesTipText() - Method in class weka.gui.beans.PredictionAppender: Return a tip text suitable for displaying in a GUI
Application - Class in weka.core.pmml.jaxbbindings: Java class for Application element declaration.
Application() - Constructor for class weka.core.pmml.jaxbbindings.Application
Application(String, String) - Constructor for class weka.core.pmml.jaxbbindings.Application
appliesToNominalClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is nominal
appliesToNumericClass() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Return true if this evaluation metric can be computed when the class is numeric
Apply - Class in weka.core.pmml.jaxbbindings: Java class for Apply element declaration.
Apply() - Constructor for class weka.core.pmml.jaxbbindings.Apply
apply(Instance) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Apply this rule to the supplied instance
apply(Instance) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Apply this rule to the supplied instance
apply(String[]) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Apply this rule to the supplied array of strings.
applyClassifier(PMMLModel, Instances) - Static method in class weka.core.pmml.PMMLFactory
applyCostMatrix(Instances, Random) - Method in class weka.classifiers.CostMatrix: Applies the cost matrix to a set of instances.
applyDefaults(Defaults) - Method in class weka.core.Settings: Applies a set of default settings.
applyMinMaxRescaleCast(double) - Method in class weka.core.pmml.TargetMetaInfo: Apply min and max, rescaleFactor, rescaleConstant and castInteger - in that order (where defined).
applyMissingAndOutlierTreatments(double[]) - Method in class weka.core.pmml.MiningSchema: Apply both missing and outlier treatments to an incoming instance.
applyMissingValuesTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the missing value treatments (if any) to an incoming instance.
applyMissingValueTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the missing value treatment method for this field.
applyOutlierTreatment(double) - Method in class weka.core.pmml.MiningFieldMetaInfo: Apply the outlier treatment method for this field.
applyOutlierTreatment(double[]) - Method in class weka.core.pmml.MiningSchema: Apply the outlier treatment methods (if any) to an incoming instance.
applyRules(Instance) - Method in class weka.gui.beans.SubstringReplacerRules
applySettings(Settings) - Method in class weka.core.packageManagement.DefaultPackageManager: Apply settings.
applySettings(Settings) - Method in class weka.core.packageManagement.PackageManager: Apply the supplied settings.
applySettings(Settings) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: No-op implementation.
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView: Apply user-changed settings
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView: Apply any user changes in the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView: Apply any user changes in the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView: Apply any changes to the settings
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Apply settings from the supplied settings object
applySettings(Settings) - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Applys settings from the supplied settings object
applySettings(Settings, String) - Method in class weka.gui.visualize.AttributePanel: Apply settings
applySettings(Settings, String) - Method in class weka.gui.visualize.MatrixPanel
applySettings(Settings, String) - Method in class weka.gui.visualize.Plot2D: Apply settings
applySettings(Settings, String) - Method in class weka.gui.visualize.VisualizePanel: Apply settings
applyToSettings() - Method in class weka.gui.SettingsEditor
applyToSettings() - Method in class weka.gui.SettingsEditor.SingleSettingsEditor
APPROVE_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies an OK property selection.
APPROVE_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies an OK property selection
APPROVE_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies an OK property selection
Apriori - Class in weka.associations: Class implementing an Apriori-type algorithm.
Apriori() - Constructor for class weka.associations.Apriori: Constructor that allows to sets default values for the minimum confidence and the maximum number of rules the minimum confidence.
AprioriItemSet - Class in weka.associations: Class for storing a set of items.
AprioriItemSet(int) - Constructor for class weka.associations.AprioriItemSet: Constructor
areaUnderPRC(int) - Method in class weka.classifiers.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderPRC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under precision-recall curve (AUPRC) for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
areaUnderROC(int) - Method in class weka.classifiers.evaluation.Evaluation: Returns the area under ROC for those predictions that have been collected in the evaluateClassifier(Classifier, Instances) method.
ARFF_ATTRIBUTE - Static variable in class weka.core.Attribute: The keyword used to denote the start of an arff attribute declaration
ARFF_ATTRIBUTE_DATE - Static variable in class weka.core.Attribute: The keyword used to denote a date attribute
ARFF_ATTRIBUTE_INTEGER - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_NUMERIC - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_REAL - Static variable in class weka.core.Attribute: A keyword used to denote a numeric attribute
ARFF_ATTRIBUTE_RELATIONAL - Static variable in class weka.core.Attribute: The keyword used to denote a relation-valued attribute
ARFF_ATTRIBUTE_STRING - Static variable in class weka.core.Attribute: The keyword used to denote a string attribute
ARFF_DATA - Static variable in class weka.core.Instances: The keyword used to denote the start of the arff data section
ARFF_END_SUBRELATION - Static variable in class weka.core.Attribute: The keyword used to denote the end of the declaration of a subrelation
ARFF_RELATION - Static variable in class weka.core.Instances: The keyword used to denote the start of an arff header
ArffLoader - Class in weka.core.converters: Reads a source that is in arff (attribute relation file format) format.
ArffLoader() - Constructor for class weka.core.converters.ArffLoader
ArffLoader.ArffReader - Class in weka.core.converters: Reads data from an ARFF file, either in incremental or batch mode.
ArffPanel - Class in weka.gui.arffviewer: A Panel representing an ARFF-Table and the associated filename.
ArffPanel() - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with no data
ArffPanel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel and loads the specified file
ArffPanel(Instances) - Constructor for class weka.gui.arffviewer.ArffPanel: initializes the panel with the given data
ArffReader(Reader) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data completely from the reader.
ArffReader(Reader, int) - Constructor for class weka.core.converters.ArffLoader.ArffReader
ArffReader(Reader, int, boolean) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads only the header and reserves the specified space for instances.
ArffReader(Reader, Instances, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Reads the data without header according to the specified template.
ArffReader(Reader, Instances, int, int, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffReader(Reader, Instances, int, int, boolean, String...) - Constructor for class weka.core.converters.ArffLoader.ArffReader: Initializes the reader without reading the header according to the specified template.
ArffSaver - Class in weka.core.converters: Writes to a destination in arff text format.
ArffSaver() - Constructor for class weka.core.converters.ArffSaver: Constructor
ArffSortedTableModel - Class in weka.gui.arffviewer: A sorter for the ARFF-Viewer - necessary because of the custom CellRenderer.
ArffSortedTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but loads the given file and creates from that a model
ArffSortedTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter w/o a model, but uses the given data to create a model from that
ArffSortedTableModel(TableModel) - Constructor for class weka.gui.arffviewer.ArffSortedTableModel: initializes the sorter with the given model
ArffTable - Class in weka.gui.arffviewer: A specialized JTable for the Arff-Viewer.
ArffTable() - Constructor for class weka.gui.arffviewer.ArffTable: initializes with no model
ArffTable(TableModel) - Constructor for class weka.gui.arffviewer.ArffTable: initializes with the given model
ArffTableCellRenderer - Class in weka.gui.arffviewer: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ArffTableCellRenderer() - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with a standard color
ArffTableCellRenderer(Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableCellRenderer(Color, Color, Color, Color) - Constructor for class weka.gui.arffviewer.ArffTableCellRenderer: initializes the Renderer with the given colors
ArffTableModel - Class in weka.gui.arffviewer: The model for the Arff-Viewer.
ArffTableModel(String, AbstractFileLoader...) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the object and loads the given file
ArffTableModel(Instances) - Constructor for class weka.gui.arffviewer.ArffTableModel: initializes the model with the given data
ArffViewer - Class in weka.gui.arffviewer: A little tool for viewing ARFF files.
ArffViewer() - Constructor for class weka.gui.arffviewer.ArffViewer: initializes the object
ArffViewerMainPanel - Class in weka.gui.arffviewer: The main panel of the ArffViewer.
ArffViewerMainPanel(Container) - Constructor for class weka.gui.arffviewer.ArffViewerMainPanel: initializes the object
Array - Class in weka.core.pmml: Class for encapsulating a PMML Array element.
Array.ArrayType - Enum in weka.core.pmml
arrayLeftDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division, C = A.\B
arrayLeftDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element left division in place, A = A.\B
arrayRightDivide(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division, C = A./B
arrayRightDivideEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element right division in place, A = A./B
arrayTimes(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication, C = A.*B
arrayTimesEquals(Matrix) - Method in class weka.core.matrix.Matrix: Element-by-element multiplication in place, A = A.*B
arrayToString(Object) - Static method in class weka.core.Utils: Returns the given Array in a string representation.
arrayToString(Object[]) - Static method in class weka.experiment.DatabaseUtils: Converts an array of objects to a string by inserting a space between each element.
ArrayType - Class in weka.core.pmml.jaxbbindings: Java class for ArrayType complex type.
ArrayType() - Constructor for class weka.core.pmml.jaxbbindings.ArrayType
ASEvaluation - Class in weka.attributeSelection: Abstract attribute selection evaluation class
ASEvaluation() - Constructor for class weka.attributeSelection.ASEvaluation
ASEvaluator - Class in weka.knowledgeflow.steps: Step that wraps a Weka attribute or subset evaluator.
ASEvaluator() - Constructor for class weka.knowledgeflow.steps.ASEvaluator
ASEvaluatorStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ASEvaluator step
ASEvaluatorStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ASEvaluatorStepEditorDialog
ASSearch - Class in weka.attributeSelection: Abstract attribute selection search class.
ASSearch() - Constructor for class weka.attributeSelection.ASSearch
ASSearchStrategy - Class in weka.knowledgeflow.steps: Step that wraps a Weka attribute selection search strategy.
ASSearchStrategy() - Constructor for class weka.knowledgeflow.steps.ASSearchStrategy
assign(Capabilities) - Method in class weka.core.Capabilities: retrieves the data from the given Capabilities object
assign(TestInstances) - Method in class weka.core.TestInstances: updates itself with all the settings from the given TestInstances object
assign(Tester) - Method in class weka.experiment.PairedTTester: retrieves all the settings from the given Tester
assign(ResultMatrix) - Method in class weka.experiment.ResultMatrix: acquires the data from the given matrix.
assign(Tester) - Method in interface weka.experiment.Tester: retrieves all the settings from the given Tester
assignCanopies(Instance) - Method in class weka.clusterers.Canopy: Uses T1 distance to assign canopies to the supplied instance.
assignIDs(int) - Method in class weka.classifiers.trees.j48.ClassifierTree: Assigns a uniqe id to every node in the tree.
assignIDs(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns unique IDs to all nodes in the tree
assignLeafModelNumbers(int) - Method in class weka.classifiers.trees.lmt.LMTNode: Assigns numbers to the logistic regression models at the leaves of the tree
assignSubToCenters(KDTreeNode, Instances, int[], int[]) - Method in class weka.core.neighboursearch.KDTree: Assigns instances of this node to center.
associatedConnections(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns a vector of BeanConnections associated with the supplied vector of BeanInstances, i.e.
AssociationModel - Class in weka.core.pmml.jaxbbindings: Java class for AssociationModel element declaration.
AssociationModel() - Constructor for class weka.core.pmml.jaxbbindings.AssociationModel
AssociationRule - Class in weka.associations: Abstract class for storing and manipulating an association rule.
AssociationRule() - Constructor for class weka.associations.AssociationRule
AssociationRule - Class in weka.core.pmml.jaxbbindings: Java class for AssociationRule element declaration.
AssociationRule() - Constructor for class weka.core.pmml.jaxbbindings.AssociationRule
AssociationRules - Class in weka.associations: Class encapsulating a list of association rules.
AssociationRules(List<AssociationRule>, String) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>, Object) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRules(List<AssociationRule>) - Constructor for class weka.associations.AssociationRules: Constructs a new AssociationRules.
AssociationRulesProducer - Interface in weka.associations: Interface to something that can provide a list of AssociationRules.
AssociationRuleVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize association results in the explorer.
AssociationsPanel - Class in weka.gui.explorer: This panel allows the user to select, configure, and run a scheme that learns associations.
AssociationsPanel() - Constructor for class weka.gui.explorer.AssociationsPanel: Creates the associator panel
Associator - Interface in weka.associations
Associator - Class in weka.gui.beans: Bean that wraps around weka.associations.
Associator() - Constructor for class weka.gui.beans.Associator: Creates a new Associator instance.
Associator - Class in weka.knowledgeflow.steps: Step that wraps a Weka associator.
Associator() - Constructor for class weka.knowledgeflow.steps.Associator
AssociatorBeanInfo - Class in weka.gui.beans: BeanInfo class for the Associator wrapper bean
AssociatorBeanInfo() - Constructor for class weka.gui.beans.AssociatorBeanInfo
AssociatorCustomizer - Class in weka.gui.beans: GUI customizer for the associator wrapper bean
AssociatorCustomizer() - Constructor for class weka.gui.beans.AssociatorCustomizer
AssociatorEvaluation - Class in weka.associations: Class for evaluating Associaters.
AssociatorEvaluation() - Constructor for class weka.associations.AssociatorEvaluation: default constructor
associatorTipText() - Method in class weka.associations.SingleAssociatorEnhancer: Returns the tip text for this property
ATT_ARRAY - Static variable in class weka.core.xml.XMLSerialization: the tag whether array or not (yes/no)
ATT_ARRAY_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_ARRAY
ATT_CLASS - Static variable in class weka.core.xml.XMLInstances: the class attribute
ATT_CLASS - Static variable in class weka.core.xml.XMLSerialization: the tag for the class
ATT_FORMAT - Static variable in class weka.core.xml.XMLInstances: the format attribute (for date attributes)
ATT_INDEX - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the index attribute.
ATT_INDEX - Static variable in class weka.core.xml.XMLInstances: the index attribute
ATT_MISSING - Static variable in class weka.core.xml.XMLInstances: the missing attribute
ATT_NAME - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLDocument: the "name" attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLOptions: the name attribute.
ATT_NAME - Static variable in class weka.core.xml.XMLSerialization: the tag for the name
ATT_NULL - Static variable in class weka.core.xml.XMLSerialization: the tag whether null or not (yes/no)
ATT_NULL_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_NULL
ATT_PREDICTED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted attribute.
ATT_PRIMITIVE - Static variable in class weka.core.xml.XMLSerialization: the tag whether primitive or not (yes/no)
ATT_PRIMITIVE_DEFAULT - Static variable in class weka.core.xml.XMLSerialization: default value for attribute ATT_PRIMITIVE
ATT_TYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "type" attribute.
ATT_TYPE - Static variable in class weka.core.xml.XMLInstances: the type attribute
ATT_TYPE - Static variable in class weka.core.xml.XMLOptions: the type attribute.
ATT_VALUE - Static variable in class weka.core.xml.XMLOptions: the value attribute.
ATT_VERSION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLDocument: the "version" attribute.
ATT_VERSION - Static variable in class weka.core.xml.XMLInstances: the version attribute
ATT_VERSION - Static variable in class weka.core.xml.XMLSerialization: the version attribute
ATT_WEIGHT - Static variable in class weka.core.xml.XMLInstances: the weight attribute
AttDefaults() - Constructor for class weka.gui.knowledgeflow.AttributeSummaryPerspective.AttDefaults
attIndex() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.C45Split: Returns index of attribute for which split was generated.
attIndex() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns index of attribute for which split was generated.
attList_IrrTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
attribute(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index.
Attribute - Class in weka.core: Class for handling an attribute.
Attribute(String) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute.
Attribute(String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute, where metadata is supplied.
Attribute(String, boolean) - Constructor for class weka.core.Attribute: Constructor for a numeric or string attribute.
Attribute(String, boolean, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a numeric or string attribute, where metadata is supplied.
Attribute(String, String) - Constructor for class weka.core.Attribute: Constructor for a date attribute.
Attribute(String, String, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for a date attribute, where metadata is supplied.
Attribute(String, List<String>) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes.
Attribute(String, List<String>, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes, where metadata is supplied.
Attribute(String, Instances) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, Instances, ProtectedProperties) - Constructor for class weka.core.Attribute: Constructor for relation-valued attributes.
Attribute(String, int) - Constructor for class weka.core.Attribute: Constructor for a numeric attribute with a particular index.
Attribute(String, String, int) - Constructor for class weka.core.Attribute: Constructor for date attributes with a particular index.
Attribute(String, List<String>, int) - Constructor for class weka.core.Attribute: Constructor for nominal attributes and string attributes with a particular index.
Attribute(String, Instances, int) - Constructor for class weka.core.Attribute: Constructor for a relation-valued attribute with a particular index.
attribute(int) - Method in interface weka.core.Instance: Returns the attribute with the given index.
attribute(int) - Method in class weka.core.Instances: Returns an attribute.
attribute(String) - Method in class weka.core.Instances: Returns an attribute given its name.
Attribute - Class in weka.core.pmml.jaxbbindings: Java class for Attribute element declaration.
Attribute() - Constructor for class weka.core.pmml.jaxbbindings.Attribute
attributeAsClass() - Method in class weka.gui.arffviewer.ArffPanel: sets the current attribute as class attribute, i.e.
attributeAsClass() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the current selected Attribute as class attribute, i.e.
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets the attribute at the given col index as the new class attribute
attributeAsClassAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: sets the attribute at the given col index as the new class attribute, i.e.
attributeCaseFix(String) - Method in class weka.experiment.DatabaseUtils: returns key column headings in their original case.
attributeCaseFix(String) - Method in interface weka.experiment.InstanceQueryAdapter: returns key column headings in their original case.
AttributeEvaluator - Interface in weka.attributeSelection: Interface for classes that evaluate attributes individually.
attributeIndexesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the tip text for this property.
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
attributeIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the tip text for this property.
attributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
AttributeListPanel - Class in weka.gui: Creates a panel that displays the attributes contained in a set of instances, letting the user select a single attribute for inspection.
AttributeListPanel() - Constructor for class weka.gui.AttributeListPanel: Creates the attribute selection panel with no initial instances.
AttributeLocator - Class in weka.core: This class locates and records the indices of a certain type of attributes, recursively in case of Relational attributes.
AttributeLocator(Instances, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int, int) - Constructor for class weka.core.AttributeLocator: Initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeLocator(Instances, int, int[]) - Constructor for class weka.core.AttributeLocator: initializes the AttributeLocator with the given data for the specified type of attribute.
AttributeMetaInfo - Class in weka.core
AttributeMetaInfo(ProtectedProperties, Attribute) - Constructor for class weka.core.AttributeMetaInfo: Creates the meta info object based on the given meta data.
attributeNamePrefixTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
attributeNamePrefixTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
attributeNames() - Method in class weka.classifiers.functions.SMO: Returns the attribute names.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
attributeNameTipText() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the tip text for this property
AttributePanel - Class in weka.gui.visualize: This panel displays one dimensional views of the attributes in a dataset.
AttributePanel() - Constructor for class weka.gui.visualize.AttributePanel
AttributePanel(Color) - Constructor for class weka.gui.visualize.AttributePanel: This constructs an attributePanel.
AttributePanelEvent - Class in weka.gui.visualize: Class encapsulating a change in the AttributePanel's selected x and y attributes.
AttributePanelEvent(boolean, boolean, int) - Constructor for class weka.gui.visualize.AttributePanelEvent: Constructor
AttributePanelListener - Interface in weka.gui.visualize: Interface for classes that want to listen for Attribute selection changes in the attribute panel
attributeRangeTipText() - Method in class weka.filters.unsupervised.attribute.StringToNominal
ATTRIBUTES - Static variable in class weka.core.json.JSONInstances: the attributes object.
AttributeSelectedClassifier - Class in weka.classifiers.meta: Dimensionality of training and test data is reduced by attribute selection before being passed on to a classifier.
AttributeSelectedClassifier() - Constructor for class weka.classifiers.meta.AttributeSelectedClassifier: Default constructor.
AttributeSelection - Class in weka.attributeSelection: Attribute selection class.
AttributeSelection() - Constructor for class weka.attributeSelection.AttributeSelection: constructor.
AttributeSelection - Class in weka.filters.supervised.attribute: A supervised attribute filter that can be used to select attributes.
AttributeSelection() - Constructor for class weka.filters.supervised.attribute.AttributeSelection: Constructor
attributeSelectionChange(AttributePanelEvent) - Method in interface weka.gui.visualize.AttributePanelListener: Called when the user clicks on an attribute bar
attributeSelectionMethodTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
AttributeSelectionPanel - Class in weka.gui: Creates a panel that displays the attributes contained in a set of instances, letting the user toggle whether each attribute is selected or not (eg: so that unselected attributes can be removed before classification).
AttributeSelectionPanel() - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel(boolean, boolean, boolean, boolean) - Constructor for class weka.gui.AttributeSelectionPanel: Creates the attribute selection panel with no initial instances.
AttributeSelectionPanel - Class in weka.gui.explorer: This panel allows the user to select and configure an attribute evaluator and a search method, set the attribute of the current dataset to be used as the class, and perform attribute selection using one of two selection modes (select using all the training data or perform a n-fold cross validation---on each trial selecting features using n-1 folds of the data).
AttributeSelectionPanel() - Constructor for class weka.gui.explorer.AttributeSelectionPanel: Creates the classifier panel
AttributeSelectionPanel.TestMode - Enum in weka.gui.explorer
AttributeSetEvaluator - Class in weka.attributeSelection: Abstract attribute set evaluator.
AttributeSetEvaluator() - Constructor for class weka.attributeSelection.AttributeSetEvaluator
attributeSparse(int) - Method in class weka.core.AbstractInstance: Returns the attribute with the given index in the sparse representation.
attributeSparse(int) - Method in interface weka.core.Instance: Returns the attribute with the given index in the sparse representation.
AttributeSpec() - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Default constructor
AttributeSpec(String) - Constructor for class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Constructor that takes an attribute specification in internal format
attributeSpecsTipText() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns the tip text for this property.
AttributeStats - Class in weka.core: A Utility class that contains summary information on an the values that appear in a dataset for a particular attribute.
AttributeStats() - Constructor for class weka.core.AttributeStats
attributeStats(int) - Method in class weka.core.Instances: Calculates summary statistics on the values that appear in this set of instances for a specified attribute.
attributesTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
attributesTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
attributesToString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Make a string from the attribues list.
AttributeSummarizer - Class in weka.gui.beans: Bean that encapsulates displays bar graph summaries for attributes in a data set.
AttributeSummarizer() - Constructor for class weka.gui.beans.AttributeSummarizer: Creates a new AttributeSummarizer instance.
AttributeSummarizer - Class in weka.knowledgeflow.steps: Step that collects data to display in a summary overview of attribute distributions
AttributeSummarizer() - Constructor for class weka.knowledgeflow.steps.AttributeSummarizer
AttributeSummarizerBeanInfo - Class in weka.gui.beans: Bean info class for the attribute summarizer bean
AttributeSummarizerBeanInfo() - Constructor for class weka.gui.beans.AttributeSummarizerBeanInfo
AttributeSummarizerCustomizer - Class in weka.gui.beans: GUI customizer for attribute summarizer.
AttributeSummarizerCustomizer() - Constructor for class weka.gui.beans.AttributeSummarizerCustomizer: Constructor
AttributeSummarizerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the AttributeSummarizer step
AttributeSummarizerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView
AttributeSummarizerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the attribute summarizer step
AttributeSummarizerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.AttributeSummarizerStepEditorDialog
AttributeSummaryPanel - Class in weka.gui: This panel displays summary statistics about an attribute: name, type number/% of missing/unique values, number of distinct values.
AttributeSummaryPanel() - Constructor for class weka.gui.AttributeSummaryPanel: Creates the instances panel with no initial instances.
AttributeSummaryPerspective - Class in weka.gui.knowledgeflow: Knowledge Flow perspective that provides a matrix of AttributeVisualizationPanels
AttributeSummaryPerspective() - Constructor for class weka.gui.knowledgeflow.AttributeSummaryPerspective: Constructor
AttributeSummaryPerspective.AttDefaults - Class in weka.gui.knowledgeflow: Default settings for the AttributeSummaryPerspective
attributeToDoubleArray(int) - Method in class weka.core.Instances: Gets the value of all instances in this dataset for a particular attribute.
AttributeTransformer - Interface in weka.attributeSelection: Abstract attribute transformer.
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property
attributeTypeTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the tip text for this property
attributeTypeToString(int) - Static method in class weka.core.CheckScheme: returns a string representation of the attribute type
attributeValues - Variable in class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer: the associated attribute values (attribute-name - value).
AttributeVisualizationPanel - Class in weka.gui: Creates a panel that shows a visualization of an attribute in a dataset.
AttributeVisualizationPanel() - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor - If used then the class will not show the class selection combo box.
AttributeVisualizationPanel(boolean) - Constructor for class weka.gui.AttributeVisualizationPanel: Constructor.
attrIndexRangeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Finds the best splitting point for an attribute in the instances
attrSplit(int, Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Finds the best splitting point for an attribute in the instances
autoBuildTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
autoKeyGenerationTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
AVERAGE_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Average of Probabilities
AveragingResultProducer - Class in weka.experiment: Takes the results from a ResultProducer and submits the average to the result listener.
AveragingResultProducer() - Constructor for class weka.experiment.AveragingResultProducer
avgCost() - Method in class weka.classifiers.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgCost() - Method in class weka.classifiers.evaluation.Evaluation: Gets the average cost, that is, total cost of misclassifications (incorrect plus unclassified) over the total number of instances.
avgProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the average transformation probability
AXIS_COLOR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Axis colour default
AXIS_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Axis colour key

B

B_ENTROPY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
B_SPHERE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: Blend setting modes
BACKGROUND_COLOR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Scatter plot background colour default
BACKGROUND_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Scatter plot background colour key
BackgroundDesktopPane(String) - Constructor for class weka.gui.Main.BackgroundDesktopPane: intializes the desktop pane.
backQuoteChars(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
BACKUP_EXTENSION - Static variable in class weka.gui.scripting.Script: the backup extension.
Bagging - Class in weka.classifiers.meta: Class for bagging a classifier to reduce variance.
Bagging() - Constructor for class weka.classifiers.meta.Bagging: Constructor.
bagSizePercentTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
balanceClassTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property
BallNode - Class in weka.core.neighboursearch.balltrees: Class representing a node of a BallTree.
BallNode(int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Constructor.
BallNode(int, int, int) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallNode(int, int, int, Instance, double) - Constructor for class weka.core.neighboursearch.balltrees.BallNode: Creates a new instance of BallNode.
BallSplitter - Class in weka.core.neighboursearch.balltrees: Abstract class for splitting a ball tree's BallNode.
BallSplitter() - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: default constructor.
BallSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.BallSplitter: Creates a new instance of BallSplitter.
ballSplitterTipText() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns the tip text for this property.
BallTree - Class in weka.core.neighboursearch: Class implementing the BallTree/Metric Tree algorithm for nearest neighbour search.
The connection to dataset is only a reference.
BallTree() - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTree(Instances) - Constructor for class weka.core.neighboursearch.BallTree: Creates a new instance of BallTree.
BallTreeConstructor - Class in weka.core.neighboursearch.balltrees: Abstract class for constructing a BallTree .
BallTreeConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BallTreeConstructor: Creates a new instance of BallTreeConstructor.
ballTreeConstructorTipText() - Method in class weka.core.neighboursearch.BallTree: Returns the tip text for this property.
BAR_BACKGROUND_COLOUR - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Attribute bar background colour key
BAR_BACKGROUND_COLOUR_KEY - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Attribute bar background colour key
BASE_ICON_PATH - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Base path for step icons
BASE_ICON_PATH - Static variable in class weka.gui.knowledgeflow.StepVisual: Standard base path for Step icons
baseClassifiersImplementMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.Stacking: Returns true if any of the base classifiers are able to generate batch predictions efficiently and all of them implement BatchPredictor.
BaseCumHazardTables - Class in weka.core.pmml.jaxbbindings: Java class for BaseCumHazardTables element declaration.
BaseCumHazardTables() - Constructor for class weka.core.pmml.jaxbbindings.BaseCumHazardTables
BaseExecutionEnvironment - Class in weka.knowledgeflow: Base class for execution environments
BaseExecutionEnvironment() - Constructor for class weka.knowledgeflow.BaseExecutionEnvironment
BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults - Class in weka.knowledgeflow: Defaults for the base execution environment
BaseExecutionEnvironmentDefaults() - Constructor for class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults
BaseInteractiveViewer - Class in weka.gui.knowledgeflow: Base class than clients can extend when implementing StepInteractiveViewer.
BaseInteractiveViewer() - Constructor for class weka.gui.knowledgeflow.BaseInteractiveViewer: Constructor
Baseline - Class in weka.core.pmml.jaxbbindings: Java class for Baseline element declaration.
Baseline() - Constructor for class weka.core.pmml.jaxbbindings.Baseline
BaselineCell - Class in weka.core.pmml.jaxbbindings: Java class for BaselineCell element declaration.
BaselineCell() - Constructor for class weka.core.pmml.jaxbbindings.BaselineCell
BaselineModel - Class in weka.core.pmml.jaxbbindings: Java class for BaselineModel element declaration.
BaselineModel() - Constructor for class weka.core.pmml.jaxbbindings.BaselineModel
BaselineStratum - Class in weka.core.pmml.jaxbbindings: Java class for BaselineStratum element declaration.
BaselineStratum() - Constructor for class weka.core.pmml.jaxbbindings.BaselineStratum
BASELINETESTSTATISTIC - Enum in weka.core.pmml.jaxbbindings: Java class for BASELINE-TEST-STATISTIC.
BaseSimpleDataVisualizer - Class in weka.knowledgeflow.steps: Abstract base class for simple data visualization steps that just collect data sets for visualization.
BaseSimpleDataVisualizer() - Constructor for class weka.knowledgeflow.steps.BaseSimpleDataVisualizer
BaseStep - Class in weka.knowledgeflow.steps: Base class for implementations of Step to use.
BaseStep() - Constructor for class weka.knowledgeflow.steps.BaseStep: Constructor
BaseStepExtender - Interface in weka.knowledgeflow.steps: A minimal set of methods, duplicated from the Step interface, that a simple subclass of BaseStep would need to implement in order to function as a start and/or main processing step in the Knowledge Flow.
baseTipText() - Method in class weka.core.neighboursearch.CoverTree: Returns the tip text for this property.
BasicAction(String, String, String, Character) - Constructor for class weka.gui.scripting.FileScriptingPanel.BasicAction: Constructor for setting up an action.
BATCH - Static variable in interface weka.core.converters.Loader
BATCH - Static variable in interface weka.core.converters.Saver
BATCH_FINISHED - Static variable in class weka.gui.beans.IncrementalClassifierEvent
BATCH_FINISHED - Static variable in class weka.gui.beans.InstanceEvent
BATCH_FINISHED - Static variable in class weka.gui.streams.InstanceEvent: Specifies that the batch of instances is finished
BATCH_SIZE_DEFAULT - Static variable in class weka.classifiers.AbstractClassifier: Default preferred batch size for batch predictions
BatchAssociationRulesEvent - Class in weka.gui.beans: Class encapsulating a set of association rules.
BatchAssociationRulesEvent(Object, AssociationRules) - Constructor for class weka.gui.beans.BatchAssociationRulesEvent: Creates a new BatchAssociationRulesEvent instance.
BatchAssociationRulesListener - Interface in weka.gui.beans: Interface to something that can process a BatchAssociationRulesEvent.
BatchClassifierEvent - Class in weka.gui.beans: Class encapsulating a built classifier and a batch of instances to test on.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierEvent(Object, Classifier, DataSetEvent, DataSetEvent, int, int, int, int) - Constructor for class weka.gui.beans.BatchClassifierEvent: Creates a new BatchClassifierEvent instance.
BatchClassifierListener - Interface in weka.gui.beans: Interface to something that can process a BatchClassifierEvent
BatchClustererEvent - Class in weka.gui.beans: Class encapsulating a built clusterer and a batch of instances to test on.
BatchClustererEvent(Object, Clusterer, DataSetEvent, int, int, int) - Constructor for class weka.gui.beans.BatchClustererEvent: Creates a new BatchClustererEvent instance.
BatchClustererListener - Interface in weka.gui.beans: Interface to something that can process a BatchClustererEvent
BatchConverter - Interface in weka.core.converters: Marker interface for a loader/saver that can retrieve instances in batch mode
batchFilterFile(Filter, String[]) - Static method in class weka.filters.Filter: Method for testing filters ability to process multiple batches.
batchFinished() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
batchFinished() - Method in class weka.classifiers.functions.SGDText
batchFinished() - Method in interface weka.classifiers.UpdateableBatchProcessor: Signal that the training data is finished (for now).
batchFinished() - Method in class weka.filters.Filter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.MultiFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleBatchFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.SimpleStreamFilter: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.AttributeSelection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.ClassOrder: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.NominalToBinary: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.attribute.PartitionMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.SpreadSubsample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddCluster: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddID: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.AddNoise: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Center: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Discretize: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.MathExpression: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.NominalToString: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Normalize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveType: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.Standardize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Randomize: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Signifies that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.RemoveRange: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.Resample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceJoiner: Signify that this batch of input to the filter is finished.
batchFinished() - Method in class weka.gui.streams.InstanceSavePanel
batchFinished() - Method in class weka.gui.streams.InstanceTable
batchFinished() - Method in class weka.gui.streams.InstanceViewer
BatchPredictor - Interface in weka.core: Interface to something that can produce predictions in a batch manner when presented with a set of Instances.
batchSizeTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.Bagging: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.RandomCommittee: Tool tip text for this property
batchSizeTipText() - Method in class weka.classifiers.meta.RandomSubSpace: Tool tip text for this property
BAYES - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable: score types
BayesInput - Class in weka.core.pmml.jaxbbindings: Java class for BayesInput element declaration.
BayesInput() - Constructor for class weka.core.pmml.jaxbbindings.BayesInput
BayesInputs - Class in weka.core.pmml.jaxbbindings: Java class for BayesInputs element declaration.
BayesInputs() - Constructor for class weka.core.pmml.jaxbbindings.BayesInputs
BayesNet - Class in weka.classifiers.bayes: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNet() - Constructor for class weka.classifiers.bayes.BayesNet
BayesNet - Static variable in interface weka.core.Drawable
BayesNet - Class in weka.datagenerators.classifiers.classification: Generates random instances based on a Bayes network.
BayesNet() - Constructor for class weka.datagenerators.classifiers.classification.BayesNet: initializes the generator
BayesNetEstimator - Class in weka.classifiers.bayes.net.estimate: BayesNetEstimator is the base class for estimating the conditional probability tables of a Bayes network once the structure has been learned.
BayesNetEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BayesNetEstimator
BayesNetGenerator - Class in weka.classifiers.bayes.net: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
BayesNetGenerator() - Constructor for class weka.classifiers.bayes.net.BayesNetGenerator: Constructor for BayesNetGenerator.
BayesOutput - Class in weka.core.pmml.jaxbbindings: Java class for BayesOutput element declaration.
BayesOutput() - Constructor for class weka.core.pmml.jaxbbindings.BayesOutput
BDeu - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
BEAN_EXECUTING - Static variable in class weka.gui.beans.BeanInstance
BeanCommon - Interface in weka.gui.beans: Interface specifying routines that all weka beans should implement in order to allow the bean environment to exercise some control over the bean and also to allow the bean to exercise some control over connections.
BeanConnection - Class in weka.gui.beans: Class for encapsulating a connection between two beans.
BeanConnection(BeanInstance, BeanInstance, EventSetDescriptor, Integer...) - Constructor for class weka.gui.beans.BeanConnection: Creates a new BeanConnection instance.
BeanCustomizer - Interface in weka.gui.beans: Extends java.beans.Customizer and provides a method to register a listener interested in notification about whether the customizer has modified the object that it is customizing.
BeanCustomizer.ModifyListener - Interface in weka.gui.beans: Interface for something that is interested in the modified status of a source object (typically a BeanCustomizer that is editing an object)
BeanInstance - Class in weka.gui.beans: Class that manages a set of beans.
BeanInstance(JComponent, Object, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance.
BeanInstance(JComponent, String, int, int, Integer...) - Constructor for class weka.gui.beans.BeanInstance: Creates a new BeanInstance instance given the fully qualified name of the bean
BeansProperties - Class in weka.gui.beans: Utility class encapsulating various properties for the KnowledgeFlow and providing methods to register and deregister plugin Bean components
BeansProperties() - Constructor for class weka.gui.beans.BeansProperties
BeanVisual - Class in weka.gui.beans: BeanVisual encapsulates icons and label for a given bean.
BeanVisual(String, String, String) - Constructor for class weka.gui.beans.BeanVisual: Constructor
BestFirst - Class in weka.attributeSelection: BestFirst:

Searches the space of attribute subsets by greedy hillclimbing augmented with a backtracking facility.
BestFirst() - Constructor for class weka.attributeSelection.BestFirst: Constructor
BestFirst.Link2 - Class in weka.attributeSelection: Class for a node in a linked list.
BestFirst.LinkedList2 - Class in weka.attributeSelection: Class for handling a linked list.
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Return the best split
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
bestSplit(SplitMetric, Map<String, WeightMass>, String) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
bias() - Method in class weka.classifiers.functions.SGDText
bias() - Method in class weka.classifiers.functions.SMO: Returns the bias of each binary SMO.
biasToUniformClassTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
BIBTEX_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the end comment tag for inserting the generated BibTex
BIBTEX_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the start comment tag for inserting the generated BibTex
BIFFileTipText() - Method in class weka.classifiers.bayes.BayesNet
BIFFormatException - Exception in weka.gui.graphvisualizer: This is the Exception thrown by BIFParser, if there was an error in parsing the XMLBIF string or input stream.
BIFFormatException(String) - Constructor for exception weka.gui.graphvisualizer.BIFFormatException
BIFParser - Class in weka.gui.graphvisualizer: This class parses an inputstream or a string in XMLBIF ver.
BIFParser(String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is a String)
BIFParser(InputStream, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.BIFParser: Constructor (if our input is an InputStream)
BIFReader - Class in weka.classifiers.bayes.net: Builds a description of a Bayes Net classifier stored in XML BIF 0.3 format.

For more details on XML BIF see:

Fabio Cozman, Marek Druzdzel, Daniel Garcia (1998).
BIFReader() - Constructor for class weka.classifiers.bayes.net.BIFReader: the default constructor
binarizeNumericAttributesTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the tip text for this property
BINARY - Static variable in class weka.gui.beans.SerializedModelSaver
binaryAttributesNominalTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
binaryAttributesNominalTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
BinaryItem - Class in weka.associations: Class that encapsulates an item whose backing Attribute is binary or unary.
BinaryItem(Attribute, int) - Constructor for class weka.associations.BinaryItem: Constructor.
BinarySimilarity - Class in weka.core.pmml.jaxbbindings: Java class for binarySimilarity element declaration.
BinarySimilarity() - Constructor for class weka.core.pmml.jaxbbindings.BinarySimilarity
BinarySMO() - Constructor for class weka.classifiers.functions.SMO.BinarySMO
BinarySparseInstance - Class in weka.core: Class for storing a binary-data-only instance as a sparse vector.
BinarySparseInstance(Instance) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given instance.
BinarySparseInstance(SparseInstance) - Constructor for class weka.core.BinarySparseInstance: Constructor that copies the info from the given instance.
BinarySparseInstance(double, double[]) - Constructor for class weka.core.BinarySparseInstance: Constructor that generates a sparse instance from the given parameters.
BinarySparseInstance(double, int[], int) - Constructor for class weka.core.BinarySparseInstance: Constructor that inititalizes instance variable with given values.
BinarySparseInstance(int) - Constructor for class weka.core.BinarySparseInstance: Constructor of an instance that sets weight to one, all values to 1, and the reference to the dataset to null.
binarySplitsTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
binarySplitsTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
binaryToKOML(String, String) - Static method in class weka.core.xml.SerialUIDChanger: converts a binary file into a KOML XML file
BinC45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-like binary (!) split for a given dataset.
BinC45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45ModelSelection: Initializes the split selection method with the given parameters.
BinC45Split - Class in weka.classifiers.trees.j48: Class implementing a binary C4.5-like split on an attribute.
BinC45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.BinC45Split: Initializes the split model.
binomialStandardError(double, int) - Static method in class weka.core.Statistics: Computes standard error for observed values of a binomial random variable.
binRangePrecisionTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
binRangePrecisionTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
binsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
BIRCHCluster - Class in weka.datagenerators.clusterers: Cluster data generator designed for the BIRCH System

Dataset is generated with instances in K clusters.
Instances are 2-d data points.
Each cluster is characterized by the number of data points in itits radius and its center.
BIRCHCluster() - Constructor for class weka.datagenerators.clusterers.BIRCHCluster: initializes the generator with default values
BIRD_IMAGE1 - Static variable in class weka.core.RepositoryIndexGenerator
BIRD_IMAGE2 - Static variable in class weka.core.RepositoryIndexGenerator
Block - Class in weka.knowledgeflow.steps: A step that waits for a specified step to finish processing before allowing incoming data to proceed downstream.
Block() - Constructor for class weka.knowledgeflow.steps.Block
blocker(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: A function used to stop the code that called buildclassifier from continuing on before the user has finished the decision tree.
BlockStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the Block step
BlockStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.BlockStepEditorDialog
BMAEstimator - Class in weka.classifiers.bayes.net.estimate: BMAEstimator estimates conditional probability tables of a Bayes network using Bayes Model Averaging (BMA).
BMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.BMAEstimator
BMPWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a BMP-file.
BMPWriter() - Constructor for class weka.gui.visualize.BMPWriter: initializes the object.
BMPWriter(JComponent) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component.
BMPWriter(JComponent, File) - Constructor for class weka.gui.visualize.BMPWriter: initializes the object with the given Component and filename.
BOOL - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BOOL used for reading experiment results.
BOOLEAN - Static variable in interface weka.core.expressionlanguage.parser.sym
BOOLEAN - Static variable in interface weka.core.json.sym
booleanColsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
BooleanConstant(boolean) - Constructor for class weka.core.expressionlanguage.common.Primitives.BooleanConstant
BooleanVariable(String) - Constructor for class weka.core.expressionlanguage.common.Primitives.BooleanVariable
BottomUpConstructor - Class in weka.core.neighboursearch.balltrees: The class that constructs a ball tree bottom up.
BottomUpConstructor() - Constructor for class weka.core.neighboursearch.balltrees.BottomUpConstructor: Creates a new instance of BottomUpConstructor.
BoundaryPanel - Class in weka.gui.boundaryvisualizer: BoundaryPanel.
BoundaryPanel(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanel: Creates a new BoundaryPanel instance.
BoundaryPanelDistributed - Class in weka.gui.boundaryvisualizer: This class extends BoundaryPanel with code for distributing the processing necessary to create a visualization among a list of remote machines.
BoundaryPanelDistributed(int, int) - Constructor for class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Creates a new BoundaryPanelDistributed instance.
BoundaryPlotter - Class in weka.knowledgeflow.steps: A step that computes visualization data for class/cluster decision boundaries.
BoundaryPlotter() - Constructor for class weka.knowledgeflow.steps.BoundaryPlotter: Constructor
BoundaryPlotter.RenderingUpdateListener - Interface in weka.knowledgeflow.steps: Interface for something that wants to be informed of rendering progress updates
BoundaryPlotterInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer component for the boundary plotter step
BoundaryPlotterInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView
BoundaryPlotterStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the boundary plotter step
BoundaryPlotterStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.BoundaryPlotterStepEditorDialog
BoundaryValueMeans - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValueMeans element declaration.
BoundaryValueMeans() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValueMeans
BoundaryValues - Class in weka.core.pmml.jaxbbindings: Java class for BoundaryValues element declaration.
BoundaryValues() - Constructor for class weka.core.pmml.jaxbbindings.BoundaryValues
BoundaryVisualizer - Class in weka.gui.boundaryvisualizer: BoundaryVisualizer.
BoundaryVisualizer() - Constructor for class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new BoundaryVisualizer instance.
BracketNode() - Constructor for class weka.knowledgeflow.steps.FlowByExpression.BracketNode
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.Split: Returns the name of the branch that the supplied instance would go down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.SplitNode: Return the branch that the supplied instance goes down
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
branchForInstance(Instance) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
breakTiesRandomlyTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
breakTiesRandomlyTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
breakUp(String, int) - Static method in class weka.core.Utils: Breaks up the string, if wider than "columns" characters.
BrowserHelper - Class in weka.gui: A little helper class for browser related stuff.
BrowserHelper() - Constructor for class weka.gui.BrowserHelper
bufferedImageMapToSerializableByteMap(Map<String, BufferedImage>) - Static method in class weka.knowledgeflow.steps.ImageViewer: Utility method to convert a map of BufferedImage to a map of byte arrays (that hold each image as png bytes)
bufferSizeTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
build(String, String) - Method in class weka.gui.HierarchyPropertyParser: Build a tree from the given property with the given delimitor
buildAssociations(Instances) - Method in class weka.associations.Apriori: Method that generates all large itemsets with a minimum support, and from these all association rules with a minimum confidence.
buildAssociations(Instances) - Method in interface weka.associations.Associator: Generates an associator.
buildAssociations(Instances) - Method in class weka.associations.FilteredAssociator: Build the associator on the filtered data.
buildAssociations(Instances) - Method in class weka.associations.FPGrowth: Method that generates all large item sets with a minimum support, and from these all association rules with a minimum metric (i.e.
buildCalibrationModelsTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
buildClassifier(Instances) - Method in class weka.classifiers.bayes.BayesNet: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayes: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Generates the classifier.
buildClassifier(Instances) - Method in interface weka.classifiers.Classifier: Generates a classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.GaussianProcesses: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.LinearRegression: Builds a regression model for the given data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.Logistic: Builds the classifier
buildClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron: Call this function to build and train a neural network for the training data provided.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGD: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SGDText: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SimpleLogistic: Builds the logistic regression using LogitBoost.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMO: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.SMOreg: Method for building the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: learn SVM parameters from data.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMO: learn SVM parameters from data using Smola's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: learn SVM parameters from data using Keerthi's SMO algorithm.
buildClassifier(Instances) - Method in class weka.classifiers.functions.VotedPerceptron: Builds the ensemble of perceptrons.
buildClassifier(Instances) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Stump method for building the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.IBk: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.KStar: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.lazy.LWL: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Build the classifier on the dimensionally reduced data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Bagging: Bagging method.
buildClassifier(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Builds the model of the base learner.
buildClassifier(Instances) - Method in class weka.classifiers.meta.CVParameterSelection: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost: Method used to build the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifier: Builds the classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable
buildClassifier(Instances) - Method in class weka.classifiers.meta.MultiScheme: Buildclassifier selects a classifier from the set of classifiers by minimising error on the training data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomCommittee: Builds the committee of randomizable classifiers.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Build the classifier on the filtered data.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RandomSubSpace: builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.RegressionByDiscretization: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Stacking: Builds a classifier using stacking.
buildClassifier(Instances) - Method in class weka.classifiers.meta.Vote: Builds all classifiers in the ensemble
buildClassifier(Instances) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Build the classifier
buildClassifier(Instances) - Method in class weka.classifiers.misc.SerializedClassifier: loads only the serialized classifier
buildClassifier(Instances) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Stump method for building the classifiers
buildClassifier(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Throw an exception - PMML models are pre-built.
buildClassifier(Instances) - Method in class weka.classifiers.rules.DecisionTable: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.JRip: Builds Ripper in the order of class frequencies.
buildClassifier(Instances) - Method in class weka.classifiers.rules.OneR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.PART: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.rules.part.MakeDecList: Builds dec list.
buildClassifier(Instances) - Method in class weka.classifiers.rules.ZeroR: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.DecisionStump: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.HoeffdingTree: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.J48: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Creates a C4.5-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Builds the classifier split model for the given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Method for building a classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Method for building a naive bayes classifier tree
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Build the no-split node
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Creates a NBTree-type split on the given data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Creates a "no-split"-split for a given set of instances.
buildClassifier(Instances) - Method in class weka.classifiers.trees.j48.PruneableClassifierTree: Method for building a pruneable classifier tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.LMT: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building a logistic model tree (only called for the root node).
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.LogisticBase: Builds the logistic regression model usiing LogitBoost.
buildClassifier(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Builds the split.
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
buildClassifier(Instances) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Builds a simple linear regression model given the supplied training data.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.M5Base: Generates the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Builds the classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.Rule: Generates a single rule or m5 model tree.
buildClassifier(Instances) - Method in class weka.classifiers.trees.m5.RuleNode: Build this node (find an attribute and split point)
buildClassifier(Instances) - Method in class weka.classifiers.trees.RandomTree: Builds classifier.
buildClassifier(Instances) - Method in class weka.classifiers.trees.REPTree: Builds classifier.
buildClusterer(Instances) - Method in class weka.clusterers.AbstractClusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Canopy
buildClusterer(Instances) - Method in interface weka.clusterers.Clusterer: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.Cobweb: Builds the clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.EM: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FarthestFirst: Generates a clusterer.
buildClusterer(Instances) - Method in class weka.clusterers.FilteredClusterer: Build the clusterer on the filtered data.
buildClusterer(Instances) - Method in class weka.clusterers.HierarchicalClusterer
buildClusterer(Instances) - Method in class weka.clusterers.MakeDensityBasedClusterer: Builds a clusterer for a set of instances.
buildClusterer(Instances) - Method in class weka.clusterers.SimpleKMeans: Generates a clusterer.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.C45PruneableDecList: Builds the partial tree without hold out set.
buildDecList(Instances, boolean) - Method in class weka.classifiers.rules.part.ClassifierDecList: Builds the partial tree without hold out set.
buildDecList(Instances, Instances, boolean) - Method in class weka.classifiers.rules.part.PruneableDecList: Builds the partial tree with hold out set
buildEstimator(Estimator, String[], boolean) - Static method in class weka.estimators.Estimator: Build an estimator using the options.
buildEstimator(Estimator, Instances, int, int, int, boolean) - Static method in class weka.estimators.Estimator
buildEvaluator(Instances) - Method in class weka.attributeSelection.ASEvaluation: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CfsSubsetEval: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierAttributeEval: Initializes a ClassifierAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval: Generates a attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.CorrelationAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.GainRatioAttributeEval: Initializes a gain ratio attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.InfoGainAttributeEval: Initializes an information gain attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.OneRAttributeEval: Initializes a OneRAttribute attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Initializes principal components and performs the analysis
buildEvaluator(Instances) - Method in class weka.attributeSelection.ReliefFAttributeEval: Initializes a ReliefF attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Initializes a symmetrical uncertainty attribute evaluator.
buildEvaluator(Instances) - Method in class weka.attributeSelection.WrapperSubsetEval: Generates a attribute evaluator.
buildGenerator(Instances) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Build the data generator
buildGenerator(Instances) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Initialize the generator using the supplied instances
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.CachedKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Kernel: builds the kernel with the given data
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.Puk: builds the kernel with the given data.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.RBFKernel: Builds the kernel.
buildKernel(Instances) - Method in class weka.classifiers.functions.supportVector.StringKernel: builds the kernel with the given data.
buildModel(int, double[], double[]) - Method in class weka.estimators.UnivariateMixtureEstimator: Build mixture model.
buildRegressionTreeTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
buildRule(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for building a pruned partial tree.
buildRule(Instances, Instances) - Method in class weka.classifiers.rules.part.PruneableDecList: Method for building a pruned partial tree.
buildStructure() - Method in class weka.classifiers.bayes.BayesNet: buildStructure determines the network structure/graph of the network.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: buildStructure determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.TAN: buildStructure determines the network structure/graph of the network using the maximimum weight spanning tree algorithm of Chow and Liu
buildStructure(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: buildStructure determines the network structure/graph of the network.
buildTree(Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure.
buildTree(Instances, Instances, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Builds the tree structure with hold out set
buildTree(Instances, SimpleLinearRegression[][], double, double, Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for building the tree structure.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Builds the ball tree.
buildTree() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Builds the ball tree bottom up.
buildTree() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Builds a ball tree middle out.
buildTree() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Builds the ball tree top down.
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.Evaluation
BUILT_IN_EVAL_METRICS - Static variable in class weka.classifiers.evaluation.Evaluation
BuiltInArithmetic - Class in weka.core.pmml: Built-in function for +, -, *, /.
BuiltInArithmetic(BuiltInArithmetic.Operator) - Constructor for class weka.core.pmml.BuiltInArithmetic: Construct a new Arithmetic built-in pmml function.
BuiltInMath - Class in weka.core.pmml: Built-in function for min, max, sum, avg, log10, ln, sqrt, abs, exp, pow, threshold, floor, ceil and round.
BuiltInMath(BuiltInMath.MathFunc) - Constructor for class weka.core.pmml.BuiltInMath: Construct a new built-in pmml Math function.
BuiltInString - Class in weka.core.pmml: Built-in function for uppercase, substring and trimblanks.
BVDecompose - Class in weka.classifiers: Class for performing a Bias-Variance decomposition on any classifier using the method specified in:

Ron Kohavi, David H.
BVDecompose() - Constructor for class weka.classifiers.BVDecompose
BVDecomposeSegCVSub - Class in weka.classifiers: This class performs Bias-Variance decomposion on any classifier using the sub-sampled cross-validation procedure as specified in (1).
The Kohavi and Wolpert definition of bias and variance is specified in (2).
The Webb definition of bias and variance is specified in (3).

Geoffrey I.
BVDecomposeSegCVSub() - Constructor for class weka.classifiers.BVDecomposeSegCVSub
BYTE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for BYTE used for reading experiment results.
byteArrayImageMapToBufferedImageMap(Map<String, byte[]>) - Static method in class weka.knowledgeflow.steps.ImageViewer: Utility method to convert a map of byte[] png image data to a map of BufferedImage

C

C45Loader - Class in weka.core.converters: Reads a file that is C45 format.
C45Loader() - Constructor for class weka.core.converters.C45Loader
C45ModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a C4.5-type split for a given dataset.
C45ModelSelection(int, Instances, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45ModelSelection: Initializes the split selection method with the given parameters.
C45PruneableClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure that can be pruned using C4.5 procedures.
C45PruneableClassifierTree(ModelSelection, boolean, float, boolean, boolean, boolean) - Constructor for class weka.classifiers.trees.j48.C45PruneableClassifierTree: Constructor for pruneable tree structure.
C45PruneableDecList - Class in weka.classifiers.rules.part: Class for handling a partial tree structure pruned using C4.5's pruning heuristic.
C45PruneableDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.C45PruneableDecList: Constructor for pruneable tree structure.
C45Saver - Class in weka.core.converters: Writes to a destination that is in the format used by the C4.5 algorithm.
Therefore it outputs a names and a data file.
C45Saver() - Constructor for class weka.core.converters.C45Saver: Constructor
C45Split - Class in weka.classifiers.trees.j48: Class implementing a C4.5-type split on an attribute.
C45Split(int, int, double, boolean) - Constructor for class weka.classifiers.trees.j48.C45Split: Initializes the split model.
CachedKernel - Class in weka.classifiers.functions.supportVector: Base class for RBFKernel and PolyKernel that implements a simple LRU.
CachedKernel() - Constructor for class weka.classifiers.functions.supportVector.CachedKernel: default constructor - does nothing.
cacheKeyNameTipText() - Method in class weka.experiment.DatabaseResultListener: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns the tip text for this property
cacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
CacheTable(int, float) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
CacheTable() - Constructor for class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Constructs a new hashtable with a default capacity and load factor.
calcCentroidPivot(int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcCentroidPivot(int, int, int[], Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node.
calcColumnWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal column width of the given column
calcColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the column of the given table.
calcFullMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
calcGraph(int, int) - Method in class weka.gui.AttributeVisualizationPanel: Recalculates the barplot or histogram to display, required usually when the attribute is changed or the component is resized.
calcHeaderWidth(int) - Method in class weka.gui.JTableHelper: calcs the optimal header width of the given column
calcHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper: Calculates the optimal width for the header of the given table.
calcMargins(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator: Calc marginal distributions of nodes in Bayesian network Note that a connected network is assumed.
calcNodeScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score for given parent set
calcOutOfBagTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
calcPivot(BallNode, BallNode, Instances) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the centroid pivot of a node based on its two child nodes.
calcPivot(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: /** Calculates the centroid pivot of a node based on its two child nodes (if merging two nodes).
calcPivot(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the centroid pivot of a node based on the list of points that it contains (tbe two lists of its children are provided).
calcRadius(int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of node.
calcRadius(int, int, int[], Instances, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node.
calcRadius(BallNode, BallNode, Instance, DistanceFunction) - Static method in class weka.core.neighboursearch.balltrees.BallNode: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(BottomUpConstructor.TempNode, BottomUpConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Calculates the radius of a node based on its two child nodes.
calcRadius(MiddleOutConstructor.TempNode, MiddleOutConstructor.TempNode) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on its two child nodes (if merging two nodes).
calcRadius(MiddleOutConstructor.MyIdxList, MiddleOutConstructor.MyIdxList, Instance, Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Calculates the radius of a node based on the list of points that it contains (the two lists of its children are provided).
calcScore(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: performCV returns the accuracy calculated using cross validation.
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Added Parent
calcScoreWithExtraParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With AddedParent
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithMissingParent(int, int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Calc Node Score With Parent Deleted
calcScoreWithReversedParent(int, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Calc Node Score With Arrow reversed
calculateAdjRSquared(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the adjusted R-squared value for a linear regression model.
calculateAlphas() - Method in class weka.classifiers.trees.lmt.LMTNode: Updates the alpha field for all nodes.
calculateDerived() - Method in class weka.experiment.PairedStats: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.PairedStatsCorrected: Calculates the derived statistics (significance etc).
calculateDerived() - Method in class weka.experiment.Stats: Tells the object to calculate any statistics that don't have their values automatically updated during add.
calculateFStat(double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the F-statistic for a linear regression model.
calculateRSquared(Instances, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the R-squared value for a linear regression model, where sum of squared residuals is already calculated.
calculateSSR(Instances, Attribute, double, double) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the sum of squared residuals of the simple linear regression model: y = a + bx.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedCorrectedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in class weka.experiment.PairedTTester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStatistics(Instance, int, int, int) - Method in interface weka.experiment.Tester: Computes a paired t-test comparison for a specified dataset between two resultsets.
calculateStdDevsTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
calculateStdErrorOfCoef(Instances, Attribute, double, double, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the standard errors of slope and intercept for a simple linear regression model: y = a + bx.
calculateStdErrorOfCoef(Instances, boolean[], double, int, int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the standard errors of the coefficients in a multiple linear regression.
calculateTStats(double[], double[], int) - Static method in class weka.classifiers.evaluation.RegressionAnalysis: Returns an array of the t-statistic of each coefficient in a multiple linear regression model.
calibratorTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
call() - Method in class weka.knowledgeflow.StepTask: Executor service calls this method to do the work
CallbackNotifierDelegate - Interface in weka.knowledgeflow: Interface to something that can notify a Step that a Task submitted by ExecutionEnvironment.submitTask() has finished.
canAcceptConnection(Class<?>) - Method in class weka.gui.beans.MetaBean: Checks to see if any of the inputs to this group implements the supplied listener class
cancel() - Method in class weka.core.converters.AbstractFileSaver: Cancels the incremental saving process.
cancel() - Method in class weka.core.converters.AbstractSaver: Cancels the incremental saving process if the write mode is CANCEL.
cancel() - Method in class weka.core.converters.DatabaseSaver: Cancels the incremental saving process and tries to drop the table if the write mode is CANCEL.
CANCEL_OPTION - Static variable in class weka.gui.experiment.OutputFormatDialog: Signifies a cancelled property selection.
CANCEL_OPTION - Static variable in class weka.gui.ListSelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.PropertySelectorDialog: Signifies a cancelled property selection
CANCEL_OPTION - Static variable in class weka.gui.ViewerDialog: Signifies a cancelled property selection
canMoveDown(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved down
canMoveUp(JList) - Static method in class weka.gui.JListHelper: checks whether the selected items can be moved up
Canopy - Class in weka.clusterers: Cluster data using the capopy clustering algorithm, which requires just one pass over the data.
Canopy() - Constructor for class weka.clusterers.Canopy
CANOPY - Static variable in class weka.clusterers.SimpleKMeans
canopyMaxNumCanopiesToHoldInMemoryTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyMinimumCanopyDensityTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyPeriodicPruningRateTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
canopyT1TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canopyT2TipText() - Method in class weka.clusterers.SimpleKMeans: Tip text for this property
canPlot(boolean) - Method in class weka.gui.explorer.AbstractPlotInstances: Returns whether all the data is available and the plot instances can be used for plotting.
canProduceRules() - Method in class weka.associations.Apriori: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in interface weka.associations.AssociationRulesProducer: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FilteredAssociator: Returns true if this AssociationRulesProducer can actually produce rules.
canProduceRules() - Method in class weka.associations.FPGrowth: Returns true if this AssociationRulesProducer can actually produce rules.
canRedo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return whether there is something on the undo stack that can be performed
canUndo() - Method in interface weka.core.Undoable: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffPanel: returns whether an undo is possible
canUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether an undo is possible, i.e.
canUndo() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether an undo is possible, i.e.
Capabilities - Class in weka.core: A class that describes the capabilites (e.g., handling certain types of attributes, missing values, types of classes, etc.) of a specific classifier.
Capabilities(CapabilitiesHandler) - Constructor for class weka.core.Capabilities: initializes the capabilities for the given owner
capabilities() - Method in class weka.core.Capabilities: Returns an Iterator over the stored capabilities
Capabilities - Class in weka.gui.simplecli: Outputs the capabilities of the specified class.
Capabilities() - Constructor for class weka.gui.simplecli.Capabilities
Capabilities.Capability - Enum in weka.core: enumeration of all capabilities
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AssociationsPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.AttributeSelectionPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClassifierPanel: method gets called in case of a change event.
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.ClustererPanel: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in interface weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener: method gets called in case of a change event
capabilitiesFilterChanged(Explorer.CapabilitiesFilterChangeEvent) - Method in class weka.gui.explorer.PreprocessPanel: method gets called in case of a change event
CapabilitiesFilterChangeEvent(Object, Capabilities) - Constructor for class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent: Constructs a GOECapabilitiesFilterChangeEvent object.
CapabilitiesFilterDialog() - Constructor for class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: creates a dialog to choose Capabilities from.
CapabilitiesHandler - Interface in weka.core: Classes implementing this interface return their capabilities in regards to datasets.
CapabilitiesIgnorer - Interface in weka.core: Classes implementing this interface make it possible to turn off capabilities checking.
CapabilitiesUtils - Class in weka.core: Helper class for Capabilities.
CapabilitiesUtils() - Constructor for class weka.core.CapabilitiesUtils
capacity() - Method in class weka.core.matrix.DoubleVector: Gets the capacity of the vector.
capacity() - Method in class weka.core.matrix.IntVector: Returns the capacity of the vector
cardinalityTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the tip text for this property
caretUpdate(CaretEvent) - Method in class weka.gui.LogWindow: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.ConnectionPanel: Called when the caret position is updated.
caretUpdate(CaretEvent) - Method in class weka.gui.sql.QueryPanel: Called when the caret position is updated.
CartesianProduct - Class in weka.filters.unsupervised.attribute: A filter for performing the Cartesian product of a set of nominal attributes.
CartesianProduct() - Constructor for class weka.filters.unsupervised.attribute.CartesianProduct
carTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
CARuleMiner - Interface in weka.associations: Interface for learning class association rules.
CaseInsensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator
CaseSensitiveComparator() - Constructor for class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator
cast(Object) - Static method in class weka.core.Utils: Casting an object without "unchecked" compile-time warnings.
cat(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Combine two vectors together
CategoricalPredictor - Class in weka.core.pmml.jaxbbindings: Java class for CategoricalPredictor element declaration.
CategoricalPredictor() - Constructor for class weka.core.pmml.jaxbbindings.CategoricalPredictor
Categories - Class in weka.core.pmml.jaxbbindings: Java class for Categories element declaration.
Categories() - Constructor for class weka.core.pmml.jaxbbindings.Categories
Category - Class in weka.core.pmml.jaxbbindings: Java class for Category element declaration.
Category() - Constructor for class weka.core.pmml.jaxbbindings.Category
CATSCORINGMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for CAT-SCORING-METHOD.
Center - Class in weka.filters.unsupervised.attribute: Centers all numeric attributes in the given dataset to have zero mean (apart from the class attribute, if set).
Center() - Constructor for class weka.filters.unsupervised.attribute.Center
centerDataTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
centerDataTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property
centerHorizontal(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between left and right most node in the list
centerInstances(Instances, int[], double) - Method in class weka.core.neighboursearch.KDTree: Assigns instances to centers using KDTree.
centerVertical(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: center set of nodes half way between top and bottom most node in the list
CfsSubsetEval - Class in weka.attributeSelection: CfsSubsetEval :

Evaluates the worth of a subset of attributes by considering the individual predictive ability of each feature along with the degree of redundancy between them.

Subsets of features that are highly correlated with the class while having low intercorrelation are preferred.

For more information see:

M.
CfsSubsetEval() - Constructor for class weka.attributeSelection.CfsSubsetEval: Constructor
ChangeDateFormat - Class in weka.filters.unsupervised.attribute: Changes the date format used by a date attribute.
ChangeDateFormat() - Constructor for class weka.filters.unsupervised.attribute.ChangeDateFormat
changeLength(double) - Method in class weka.core.AlgVector: Changes the length of a vector.
changeUID(long, long, String, String) - Static method in class weka.core.xml.SerialUIDChanger: changes the oldUID into newUID from the given file (binary/KOML) into the other one (binary/KOML).
CharacterDelimitedTokenizer - Class in weka.core.tokenizers: Abstract superclass for tokenizers that take characters as delimiters.
CharacterDelimitedTokenizer() - Constructor for class weka.core.tokenizers.CharacterDelimitedTokenizer
Characteristic - Class in weka.core.pmml.jaxbbindings: Java class for Characteristic element declaration.
Characteristic() - Constructor for class weka.core.pmml.jaxbbindings.Characteristic
Characteristics - Class in weka.core.pmml.jaxbbindings: Java class for Characteristics element declaration.
Characteristics() - Constructor for class weka.core.pmml.jaxbbindings.Characteristics
CharacterNGramTokenizer - Class in weka.core.tokenizers: Splits a string into an n-gram with min and max grams.
CharacterNGramTokenizer() - Constructor for class weka.core.tokenizers.CharacterNGramTokenizer
charSetTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
ChartEvent - Class in weka.gui.beans: Event encapsulating info for plotting a data point on the StripChart
ChartEvent(Object, Vector<String>, double, double, double[], boolean) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
ChartEvent(Object) - Constructor for class weka.gui.beans.ChartEvent: Creates a new ChartEvent instance.
chartingEvalWindowSizeTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Return a tip text string for this property
chartingEvalWindowSizeTipText() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Return a tip text string for this property
ChartListener - Interface in weka.gui.beans: Interface to something that can process a ChartEvent
Chebychev - Class in weka.core.pmml.jaxbbindings: Java class for chebychev element declaration.
Chebychev() - Constructor for class weka.core.pmml.jaxbbindings.Chebychev
ChebyshevDistance - Class in weka.core: Implements the Chebyshev distance.
ChebyshevDistance() - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object, Instances must be still set.
ChebyshevDistance(Instances) - Constructor for class weka.core.ChebyshevDistance: Constructs an Chebyshev Distance object and automatically initializes the ranges.
check(double) - Method in class weka.classifiers.trees.j48.Distribution: Checks if at least two bags contain a minimum number of instances.
Check - Class in weka.core: Abstract general class for testing in Weka.
Check() - Constructor for class weka.core.Check
CheckAssociator - Class in weka.associations: Class for examining the capabilities and finding problems with associators.
CheckAssociator() - Constructor for class weka.associations.CheckAssociator
CheckAttributeSelection - Class in weka.attributeSelection: Class for examining the capabilities and finding problems with attribute selection schemes.
CheckAttributeSelection() - Constructor for class weka.attributeSelection.CheckAttributeSelection
CheckBoxList - Class in weka.gui: An extended JList that contains CheckBoxes.
CheckBoxList() - Constructor for class weka.gui.CheckBoxList: initializes the list with an empty CheckBoxListModel
CheckBoxList(CheckBoxList.CheckBoxListModel) - Constructor for class weka.gui.CheckBoxList: initializes the list with the given CheckBoxListModel
CheckBoxList.CheckBoxListModel - Class in weka.gui: A specialized model.
CheckBoxList.CheckBoxListRenderer - Class in weka.gui: A specialized CellRenderer for the CheckBoxList
CheckBoxListModel() - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: initializes the model with no data.
CheckBoxListModel(Object[]) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
CheckBoxListModel(Vector) - Constructor for class weka.gui.CheckBoxList.CheckBoxListModel: Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
CheckBoxListRenderer() - Constructor for class weka.gui.CheckBoxList.CheckBoxListRenderer
checkCanonicalUserOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options stay the same after settting, getting and re-setting again
CheckClassifier - Class in weka.classifiers: Class for examining the capabilities and finding problems with classifiers.
CheckClassifier() - Constructor for class weka.classifiers.CheckClassifier
CheckClusterer - Class in weka.clusterers: Class for examining the capabilities and finding problems with clusterers.
CheckClusterer() - Constructor for class weka.clusterers.CheckClusterer: default constructor
checkConstraint(Package) - Method in class weka.core.packageManagement.PackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.PackageConstraint: Check the target package constraint against the constraint embodied in this package constraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.VersionPackageConstraint: Check the target package constraint against the constraint embodied in this package constraint.
checkConstraint(Package) - Method in class weka.core.packageManagement.VersionPackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(Package) - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Check the target package against the constraint embodied in this PackageConstraint.
checkConstraint(PackageConstraint) - Method in class weka.core.packageManagement.VersionRangePackageConstraint
checkDefaultOptions() - Method in class weka.core.CheckOptionHandler: checks whether the default options can be processed completely or some invalid options are returned by the getOptions() method.
checkErrorRateTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
CheckEstimator - Class in weka.estimators: Class for examining the capabilities and finding problems with estimators.
CheckEstimator() - Constructor for class weka.estimators.CheckEstimator
CheckEstimator.AttrTypes - Class in weka.estimators: class that contains info about the attribute types the estimator can estimate estimator work on one attribute only
CheckEstimator.EstTypes - Class in weka.estimators: public class that contains info about the chosen attribute type estimator work on one attribute only
CheckEstimator.PostProcessor - Class in weka.estimators: a class for postprocessing the test-data
checkForAttributeType(int) - Method in class weka.core.Instances: Checks for attributes of the given type in the dataset
checkForMissingFiles(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageLibIsolatingClassLoader: Checks to see if there are any missing files/directories for a given package.
checkForMissingFiles(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks to see if there are any missing files/directories for a given package.
checkForNewPackages(PrintStream...) - Static method in class weka.core.WekaPackageManager: Check for new packages on the server and refresh the local cache if needed
checkForRemainingOptions(String[]) - Static method in class weka.core.Utils: Checks if the given array contains any non-empty options.
checkForStringAttributes() - Method in class weka.core.Instances: Checks for string attributes in the dataset
checkForThirdPartyClass(String, WekaPackageLibIsolatingClassLoader) - Static method in class weka.core.SerializationHelper: Checks to see if the supplied package class loader (or any of its dependent package class loaders) has the given third party class.
checkGlobalInfo() - Method in class weka.core.CheckGOE: checks whether the object declares a globalInfo method.
CheckGOE - Class in weka.core: Simple command line checking of classes that are editable in the GOE.
CheckGOE() - Constructor for class weka.core.CheckGOE: default constructor
checkIndicesList(MiddleOutConstructor.MyIdxList, int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Checks whether if the points in an index list are in some specified of the master index array.
checkInstance(Instance) - Method in class weka.core.Instances: Checks if the given instance is compatible with this dataset.
CheckKernel - Class in weka.classifiers.functions.supportVector: Class for examining the capabilities and finding problems with kernels.
CheckKernel() - Constructor for class weka.classifiers.functions.supportVector.CheckKernel
checkListOptions() - Method in class weka.core.CheckOptionHandler: checks whether the listOptions method works
checkModel() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Checks if generated model is valid.
checkModel(int) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Checks if there are at least 2 subsets that contain >= minNumInstances.
CheckOptionHandler - Class in weka.core: Simple command line checking of classes that implement OptionHandler.
CheckOptionHandler() - Constructor for class weka.core.CheckOptionHandler
checkRemainingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed completely or some "left-over" options remain
checkResettingOptions() - Method in class weka.core.CheckOptionHandler: checks whether the optionhandler can be re-setted again to default options after the user-supplied options have been set.
CheckScheme - Class in weka.core: Abstract general class for testing schemes in Weka.
CheckScheme() - Constructor for class weka.core.CheckScheme
CheckScheme.PostProcessor - Class in weka.core: a class for postprocessing the test-data
checkSetOptions() - Method in class weka.core.CheckOptionHandler: checks whether the user-supplied options can be processed at all
CheckSource - Class in weka.classifiers: A simple class for checking the source generated from Classifiers implementing the weka.classifiers.Sourcable interface.
CheckSource() - Constructor for class weka.classifiers.CheckSource
CheckSource - Class in weka.filters: A simple class for checking the source generated from Filters implementing the weka.filters.Sourcable interface.
CheckSource() - Constructor for class weka.filters.CheckSource
checkStatus(Object) - Method in interface weka.experiment.Compute: Check on the status of a Task
checkStatus(Object) - Method in class weka.experiment.RemoteEngine: Returns status information on a particular task
checksTurnedOffTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
checksTurnedOffTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
checkToolTips() - Method in class weka.core.CheckGOE: checks whether the object declares tip text method for all its properties.
checkWindowShouldBeClosed(WindowEvent) - Method in class weka.gui.GUIChooserApp: Asks the user whether the window that generated the window evident given as the argument should really be closed.
ChildFrameMDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameMDI: constructs a new internal frame that knows about its parent.
ChildFrameSDI(GUIChooserApp, String) - Constructor for class weka.gui.GUIChooserApp.ChildFrameSDI: constructs a new internal frame that knows about its parent.
ChildFrameSDI(Main, String) - Constructor for class weka.gui.Main.ChildFrameSDI: constructs a new internal frame that knows about its parent.
ChildParent - Class in weka.core.pmml.jaxbbindings: Java class for ChildParent element declaration.
ChildParent() - Constructor for class weka.core.pmml.jaxbbindings.ChildParent
childrenValues() - Method in class weka.gui.HierarchyPropertyParser: The value in the children nodes.
chisqDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: chi-squared
chiSquared(double[][], boolean) - Static method in class weka.core.ContingencyTables: Returns chi-squared probability for a given matrix.
chiSquaredProbability(double, double) - Static method in class weka.core.Statistics: Returns chi-squared probability for given value and degrees of freedom.
chiVal(double[][], boolean) - Static method in class weka.core.ContingencyTables: Computes chi-squared statistic for a contingency table.
chol() - Method in class weka.core.matrix.Matrix: Cholesky Decomposition
CholeskyDecomposition - Class in weka.core.matrix: Cholesky Decomposition.
CholeskyDecomposition(Matrix) - Constructor for class weka.core.matrix.CholeskyDecomposition: Cholesky algorithm for symmetric and positive definite matrix.
chooseIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Method for choosing a subset to expand.
chooseLastIndex() - Method in class weka.classifiers.rules.part.ClassifierDecList: Choose last index (ie.
CISearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci: The CISearchAlgorithm class supports Bayes net structure search algorithms that are based on conditional independence test (as opposed to for example score based of cross validation based search algorithms).
CISearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm
CityBlock - Class in weka.core.pmml.jaxbbindings: Java class for cityBlock element declaration.
CityBlock() - Constructor for class weka.core.pmml.jaxbbindings.CityBlock
CLASS - Static variable in class weka.core.json.JSONInstances: the class attribute indicator.
CLASS - Static variable in class weka.knowledgeflow.JSONFlowUtils
CLASS_GROOVYCLASSLOADER - Static variable in class weka.core.scripting.Groovy: the classname of the Groovy classloader.
CLASS_IS_LAST - Static variable in class weka.core.TestInstances: can be used for settting the class attribute index to last
CLASS_PYTHONINERPRETER - Static variable in class weka.core.scripting.Jython: the classname of the Python interpreter
CLASS_PYTHONOBJECTINPUTSTREAM - Static variable in class weka.core.scripting.Jython: the classname of the Python ObjectInputStream
ClassAssigner - Class in weka.filters.unsupervised.attribute: Filter that can set and unset the class index.
ClassAssigner() - Constructor for class weka.filters.unsupervised.attribute.ClassAssigner
ClassAssigner - Class in weka.gui.beans: Bean that assigns a class attribute to a data set.
ClassAssigner() - Constructor for class weka.gui.beans.ClassAssigner
ClassAssigner - Class in weka.knowledgeflow.steps: Knowledge Flow step for assigning a class attribute in incoming data
ClassAssigner() - Constructor for class weka.knowledgeflow.steps.ClassAssigner
ClassAssignerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class assigner bean
ClassAssignerBeanInfo() - Constructor for class weka.gui.beans.ClassAssignerBeanInfo
ClassAssignerCustomizer - Class in weka.gui.beans: GUI customizer for the class assigner bean
ClassAssignerCustomizer() - Constructor for class weka.gui.beans.ClassAssignerCustomizer
ClassAssignerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ClassAssigner step
ClassAssignerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassAssignerStepEditorDialog
classAttribute() - Method in class weka.core.AbstractInstance: Returns class attribute.
classAttribute() - Method in interface weka.core.Instance: Returns class attribute.
classAttribute() - Method in class weka.core.Instances: Returns the class attribute.
classAttributeNames() - Method in class weka.classifiers.functions.SMO
ClassBalancer - Class in weka.filters.supervised.instance: Reweights the instances in the data so that each class has the same total weight.
ClassBalancer() - Constructor for class weka.filters.supervised.instance.ClassBalancer
ClassCache - Class in weka.core: A singleton that stores all classes on the classpath.
ClassCache() - Constructor for class weka.core.ClassCache: Initializes the cache.
ClassCache.ClassFileFilter - Class in weka.core: For filtering classes.
ClassCache.DirectoryFilter - Class in weka.core: For filtering classes.
classColumnTipText() - Method in class weka.gui.beans.ClassAssigner: Tool tip text for this property
ClassConditionalProbabilities - Class in weka.filters.supervised.attribute: Converts the values of nominal and/or numeric attributes into class conditional probabilities.
ClassConditionalProbabilities() - Constructor for class weka.filters.supervised.attribute.ClassConditionalProbabilities
ClassDiscovery - Class in weka.core: This class is used for discovering classes that implement a certain interface or a derived from a certain class.
ClassDiscovery() - Constructor for class weka.core.ClassDiscovery
ClassDiscovery.StringCompare - Class in weka.core: compares two strings.
classDistributionIsPure() - Method in class weka.classifiers.trees.ht.HNode: Returns true if the class distribution is pure
ClassFileFilter() - Constructor for class weka.core.ClassCache.ClassFileFilter
classFirst(boolean) - Method in class weka.experiment.Experiment: Sets whether the first attribute is treated as the class for all datasets involved in the experiment.
classFlagTipText() - Method in class weka.datagenerators.ClusterGenerator: Returns the tip text for this property
ClassificationGenerator - Class in weka.datagenerators: Abstract class for data generators for classifiers.
ClassificationGenerator() - Constructor for class weka.datagenerators.ClassificationGenerator: initializes with default values
ClassificationViaRegression - Class in weka.classifiers.meta: Class for doing classification using regression methods.
ClassificationViaRegression() - Constructor for class weka.classifiers.meta.ClassificationViaRegression: Default constructor.
Classifier - Interface in weka.classifiers: Classifier interface.
Classifier - Class in weka.gui.beans: Bean that wraps around weka.classifiers
Classifier() - Constructor for class weka.gui.beans.Classifier: Creates a new Classifier instance.
Classifier - Class in weka.knowledgeflow.steps: Step that wraps a Weka classifier.
Classifier() - Constructor for class weka.knowledgeflow.steps.Classifier
ClassifierAttributeEval - Class in weka.attributeSelection: ClassifierAttributeEval :

Evaluates the worth of an attribute by using a user-specified classifier.

Valid options are:
ClassifierAttributeEval() - Constructor for class weka.attributeSelection.ClassifierAttributeEval: Constructor.
ClassifierBeanInfo - Class in weka.gui.beans: BeanInfo class for the Classifier wrapper bean
ClassifierBeanInfo() - Constructor for class weka.gui.beans.ClassifierBeanInfo
ClassifierCustomizer - Class in weka.gui.beans: GUI customizer for the classifier wrapper bean
ClassifierCustomizer() - Constructor for class weka.gui.beans.ClassifierCustomizer
ClassifierDecList - Class in weka.classifiers.rules.part: Class for handling a rule (partial tree) for a decision list.
ClassifierDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.ClassifierDecList: Constructor - just calls constructor of class DecList.
ClassifierErrorsPlotInstances - Class in weka.gui.explorer: A class for generating plottable visualization errors.
ClassifierErrorsPlotInstances() - Constructor for class weka.gui.explorer.ClassifierErrorsPlotInstances
ClassifierPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a classifier, set the attribute of the current dataset to be used as the class, and evaluate the classifier using a number of testing modes (test on the training data, train/test on a percentage split, n-fold cross-validation, test on a separate split).
ClassifierPanel() - Constructor for class weka.gui.explorer.ClassifierPanel: Creates the classifier panel.
ClassifierPanel.TestMode - Enum in weka.gui.explorer
ClassifierPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Classifier panel and execute it.
ClassifierPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained classifiers
ClassifierPerformanceEvaluator() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluator
ClassifierPerformanceEvaluator - Class in weka.knowledgeflow.steps: Step that implements batch classifier evaluation
ClassifierPerformanceEvaluator() - Constructor for class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Constructor
ClassifierPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the classifier performance evaluator
ClassifierPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
ClassifierPerformanceEvaluatorCustomizer - Class in weka.gui.beans: GUI customizer for the classifier performance evaluator component
ClassifierPerformanceEvaluatorCustomizer() - Constructor for class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Constructor
ClassifierPerformanceEvaluatorStepEditorDialog - Class in weka.gui.knowledgeflow.steps: GUI step editor dialog for the ClassifierPerformanceEvaluator step
ClassifierPerformanceEvaluatorStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassifierPerformanceEvaluatorStepEditorDialog: Constructor
classifiers() - Method in class weka.classifiers.meta.LogitBoost: Returns the array of classifiers that have been built.
ClassifierSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a classification scheme on a nominal class attribute.
ClassifierSplitEvaluator() - Constructor for class weka.experiment.ClassifierSplitEvaluator: No args constructor.
ClassifierSplitModel - Class in weka.classifiers.trees.j48: Abstract class for classification models that can be used recursively to split the data.
ClassifierSplitModel() - Constructor for class weka.classifiers.trees.j48.ClassifierSplitModel
classifiersTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
classifiersTipText() - Method in class weka.classifiers.MultipleClassifiersCombiner: Returns the tip text for this property
ClassifierSubsetEval - Class in weka.attributeSelection: Classifier subset evaluator:

Evaluates attribute subsets on training data or a separate hold out testing set.
ClassifierSubsetEval() - Constructor for class weka.attributeSelection.ClassifierSubsetEval
classifierTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
classifierTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
classifierTipText() - Method in class weka.classifiers.SingleClassifierEnhancer: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.experiment.RegressionSplitEvaluator: Returns the tip text for this property
classifierTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
classifierTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
ClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure used for classification.
ClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.ClassifierTree: Constructor.
CLASSIFY_CHILD - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: Asks for another learning scheme to classify this node.
classifyInstance(Instance) - Method in class weka.classifiers.AbstractClassifier: Classifies the given test instance.
classifyInstance(Instance) - Method in interface weka.classifiers.Classifier: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.GaussianProcesses: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.LinearRegression: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.functions.SMOreg: Classifies the given instance using the linear regression function.
classifyInstance(Instance) - Method in class weka.classifiers.meta.AdditiveRegression: Classify an instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a predicted class for the test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.Vote: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Classifies the given test instance.
classifyInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
classifyInstance(Instance) - Method in class weka.classifiers.rules.OneR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.PART: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.rules.ZeroR: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Classifies a given instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.J48: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.LMT: Classifies an instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Generate a prediction for the supplied instance.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.M5Base: Calculates a prediction for an instance using a set of rules or an M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Predicts the class of the supplied instance using the linear model.
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.Rule: Calculates a prediction for an instance using this rule or M5 model tree
classifyInstance(Instance) - Method in class weka.classifiers.trees.m5.RuleNode: Classify an instance using this node.
classIndex() - Method in class weka.core.AbstractInstance: Returns the class attribute's index.
classIndex() - Method in interface weka.core.Instance: Returns the class attribute's index.
classIndex() - Method in class weka.core.Instances: Returns the class attribute's index.
classIndexTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
classIndexTipText() - Method in class weka.associations.FilteredAssociator: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.LibSVMSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.core.converters.SVMLightSaver: Returns the tip text for this property.
classIndexTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
classIndexTipText() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns the tip text for this property.
classIndexTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
classIsMissing() - Method in class weka.core.AbstractInstance: Tests if an instance's class is missing.
classIsMissing() - Method in interface weka.core.Instance: Tests if an instance's class is missing.
ClassLabels - Class in weka.core.pmml.jaxbbindings: Java class for ClassLabels element declaration.
ClassLabels() - Constructor for class weka.core.pmml.jaxbbindings.ClassLabels
ClassloaderUtil - Class in weka.core: Utility class that can add jar files to the classpath dynamically.
ClassloaderUtil() - Constructor for class weka.core.ClassloaderUtil
className(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the name of one of the classes.
classNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
ClassOrder - Class in weka.filters.supervised.attribute: Changes the order of the classes so that the class values are no longer of in the order specified in the header.
ClassOrder() - Constructor for class weka.filters.supervised.attribute.ClassOrder
classOrderTipText() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the tip text for this property
ClassPanel - Class in weka.gui.visualize: This panel displays coloured labels for nominal attributes and a spectrum for numeric attributes.
ClassPanel() - Constructor for class weka.gui.visualize.ClassPanel
ClassPanel(Color) - Constructor for class weka.gui.visualize.ClassPanel
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.BinC45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.C45Split: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return the probability for a class value
classProb(int, Instance, int) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Return the probability for a class value
classProbLaplace(int, Instance, int) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Gets class probability for instance.
ClassRunner(SimpleCLIPanel, Class<?>, String[]) - Constructor for class weka.gui.SimpleCLIPanel.ClassRunner: Sets up the class runner thread.
classValue() - Method in class weka.core.AbstractInstance: Returns an instance's class value in internal format.
classValue() - Method in interface weka.core.Instance: Returns an instance's class value as a floating-point number.
classValueIndexTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
ClassValuePicker - Class in weka.gui.beans
ClassValuePicker() - Constructor for class weka.gui.beans.ClassValuePicker
ClassValuePicker - Class in weka.knowledgeflow.steps: Step that allows the selection of the class label that is to be considered as the "positive" class when computing threshold curves.
ClassValuePicker() - Constructor for class weka.knowledgeflow.steps.ClassValuePicker
ClassValuePickerBeanInfo - Class in weka.gui.beans: BeanInfo class for the class value picker bean
ClassValuePickerBeanInfo() - Constructor for class weka.gui.beans.ClassValuePickerBeanInfo
ClassValuePickerCustomizer - Class in weka.gui.beans
ClassValuePickerCustomizer() - Constructor for class weka.gui.beans.ClassValuePickerCustomizer
ClassValuePickerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the ClassValuePicker step.
ClassValuePickerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ClassValuePickerStepEditorDialog
clean() - Method in class weka.attributeSelection.ASEvaluation: Tells the evaluator that the attribute selection process is complete.
clean() - Method in class weka.attributeSelection.CfsSubsetEval
clean() - Method in class weka.attributeSelection.WrapperSubsetEval
clean() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.Kernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Frees the cache used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Frees the memory used by the kernel.
clean() - Method in class weka.classifiers.functions.supportVector.StringKernel: Frees the memory used by the kernel.
clean() - Method in interface weka.core.DistanceFunction: Free any references to training instances
clean() - Method in class weka.core.FilteredDistance: Free any references to training instances
clean() - Method in class weka.core.NormalizableDistance
cleanUp(Instances) - Method in class weka.classifiers.rules.JRip.RipperRule: Removes redundant tests in the rule.
cleanup(Instances) - Method in class weka.classifiers.rules.part.ClassifierDecList: Cleanup in order to save memory.
cleanUp() - Method in class weka.classifiers.rules.RuleStats: Frees up memory after classifier has been built.
cleanup() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.j48.C45ModelSelection: Sets reference to training data to null.
cleanup(Instances) - Method in class weka.classifiers.trees.j48.ClassifierTree: Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Sets reference to training data to null.
cleanup() - Method in class weka.classifiers.trees.lmt.LogisticBase: Cleanup in order to save memory.
cleanup() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Method not in use
cleanUp() - Method in class weka.clusterers.Canopy: Save memory
cleanUp(String) - Static method in class weka.core.ClassCache: Fixes the classname, turns "/" and "\" into "." and removes ".class".
cleanUp() - Method in class weka.gui.explorer.AbstractPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: For freeing up memory.
cleanUp() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: For freeing up memory.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.AbstractSetupPanel: Hook method for cleaning up the interface after a switch.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.SetupPanel: Hook method for cleaning up the interface after a switch.
cleanUpAfterSwitch() - Method in class weka.gui.experiment.SimpleSetupPanel: Hook method for cleaning up the interface after a switch.
clear() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Clears this hashtable so that it contains no keys.
clear() - Method in class weka.classifiers.xml.XMLClassifier: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.neighboursearch.covertrees.Stack: Removes all the elements from the stack.
clear() - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
clear() - Method in class weka.core.Stopwords: removes all stopwords
clear() - Method in class weka.core.Tee: removes all streams and places the default printstream, if any, again in the list.
clear() - Method in class weka.core.Trie: Removes all of the elements from this collection
clear() - Method in class weka.core.xml.MethodHandler: removes all mappings
clear() - Method in class weka.core.xml.XMLBasicSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLDocument: sets up an empty DOM document, with the current DOCTYPE and root node.
clear() - Method in class weka.core.xml.XMLSerialization: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.core.xml.XMLSerializationMethodHandler: removes all current methods and adds the methods according to the
clear() - Method in class weka.experiment.ResultMatrix: removes the stored data and the ordering, but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixCSV: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixGnuPlot: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.ResultMatrixLatex: removes the stored data but retains the dimensions of the matrix.
clear() - Method in class weka.experiment.xml.XMLExperiment: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.beans.xml.XMLBeans: generates internally a new XML document and clears also the IgnoreList and the mappings for the Read/Write-Methods
clear() - Method in class weka.gui.GenericObjectEditorHistory: Clears the history.
clear() - Method in class weka.gui.LogWindow: clears the output
clear() - Method in class weka.gui.sql.ConnectionPanel: sets the parameters back to standard.
clear() - Method in class weka.gui.sql.InfoPanel: clears the content of the panel
clear() - Method in class weka.gui.sql.QueryPanel: clears the textarea.
clear() - Method in class weka.gui.sql.ResultPanel: sets the parameters back to standard
clear() - Method in class weka.gui.sql.SqlViewer: calls the clear method of all sub-panels to set back to default values and free up memory.
clearAllConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Clear all connections to/from the step managed by this manager.
clearAllStepOutputListeners() - Method in class weka.knowledgeflow.StepManagerImpl: Clear all registered StepOutputListeners
clearAttributeSpecs() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Clear the list of attribute specifications
clearCache() - Static method in class weka.core.ClassDiscovery: clears the cache for class/classnames queries.
clearClassCache() - Static method in class weka.core.ClassDiscovery: Calls clearCache() and resets the cache of classes on the classpath (i.e.
clearDesignPaletteSelection() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Clear the current selection in the design palette
clearHeader() - Method in class weka.experiment.ResultMatrix: removes all the header information.
clearLayout() - Method in class weka.gui.beans.KnowledgeFlowApp
clearPayload() - Method in class weka.knowledgeflow.Data: Clear all payload elements from this Data object
clearPlotData() - Method in class weka.knowledgeflow.steps.DataVisualizer
clearPlotData() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Clear all plot data (both onscreen and offscreen)
clearRanking() - Method in class weka.experiment.ResultMatrix: clears the currently stored ranking data.
clearRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle with the background color.
clearResultData() - Method in class weka.knowledgeflow.JobEnvironment
clearResults() - Method in class weka.gui.ResultHistoryPanel: Removes all of the result buffers from the history.
clearSearch() - Method in class weka.gui.arffviewer.ArffPanel: clears the search, i.e.
clearSearch() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: clears the search, i.e.
clearStatus() - Method in class weka.gui.beans.LogPanel: Clear the status area.
clearStepOutputListeners(String) - Method in class weka.knowledgeflow.StepManagerImpl: Clear all the StepOutputListeners that are registered to receive the supplied connection type.
clearStepProperties() - Method in class weka.knowledgeflow.JobEnvironment: Clear all step properties
clearSummary() - Method in class weka.experiment.ResultMatrix: clears the current summary data.
clearUndo() - Method in interface weka.core.Undoable: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffPanel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: removes the undo history
clearUndo() - Method in class weka.gui.arffviewer.ArffTableModel: removes the undo history
clearUndoStack() - Method in class weka.classifiers.bayes.net.EditableBayesNet: remove all actions from the undo stack
clip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
clipRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
Clock() - Constructor for class weka.core.Debug.Clock: automatically starts the clock with FORMAT_SECONDS format and CPU time if available
Clock(int) - Constructor for class weka.core.Debug.Clock: automatically starts the clock with the given output format and CPU time if available
Clock(boolean) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately with the FORMAT_SECONDS output format and CPU time if available
Clock(boolean, int) - Constructor for class weka.core.Debug.Clock: starts the clock depending on start immediately, using CPU time if available
clone() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Creates and returns a clone of this object.
clone() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Allows to clone a model (shallow copy).
clone() - Method in class weka.classifiers.trees.j48.Distribution: Clones distribution (Deep copy of distribution).
clone() - Method in class weka.core.AlgVector: Creates and returns a clone of this object.
clone() - Method in class weka.core.Capabilities: Creates and returns a copy of this object.
clone() - Method in class weka.core.Matrix: Deprecated.

Creates and returns a clone of this object.
clone() - Method in class weka.core.matrix.DoubleVector: Clones the DoubleVector object.
clone() - Method in class weka.core.matrix.IntVector: Clones the IntVector object.
clone() - Method in class weka.core.matrix.Matrix: Clone the Matrix object.
clone() - Method in class weka.core.packageManagement.DefaultPackage: Clone this package.
clone() - Method in class weka.core.packageManagement.Package
clone() - Method in class weka.core.PropertyPath.PathElement: returns a clone of the current object
clone() - Method in class weka.core.TestInstances: creates a clone of the current object
clone() - Method in class weka.core.Trie: returns a deep copy of itself
clone() - Method in class weka.core.Trie.TrieNode: creates a deep copy of itself
clone(Estimator) - Static method in class weka.estimators.Estimator: Creates a deep copy of the given estimator using serialization.
close(ResultSet) - Method in class weka.experiment.DatabaseUtils: closes the ResultSet and the statement that generated the ResultSet to avoid memory leaks in JDBC drivers - in contrast to the JDBC specs, a lot of JDBC drives don't clean up correctly.
close() - Method in class weka.experiment.DatabaseUtils: closes the m_PreparedStatement to avoid memory leaks.
close() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the window, i.e., if the parent is not null and implements the WindowListener interface it calls the windowClosing method
close() - Method in class weka.gui.LogWindow: closes the frame
CloseableTabTitle - Class in weka.gui: Tab title widget that allows the user to click a little cross in order to close the tab
CloseableTabTitle(JTabbedPane, String, CloseableTabTitle.ClosingCallback) - Constructor for class weka.gui.CloseableTabTitle: Constructor.
CloseableTabTitle.ClosingCallback - Interface in weka.gui: Interface for a callback for notification of a tab's close widget being clicked
closeAllFiles() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes all open files
closeAllTabs() - Method in class weka.gui.beans.KnowledgeFlowApp
closeAllTabs() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Close all the open tabs
closeFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFile(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: closes the current tab
closeFrame() - Method in class weka.gui.SetInstancesPanel: closes the frame, i.e., the visibility is set to false.
closePressed() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Called when the close button is pressed.
closePressed() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Called when the viewer's window is closed
closePressed() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Called when the close button is pressed
closePressed() - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Called when the close button is pressed
closestPoint(Instance, Instances, int[]) - Method in class weka.core.EuclideanDistance: Returns the index of the closest point to the current instance.
closeToDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closeToToleranceTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
closing() - Method in interface weka.gui.knowledgeflow.StepEditorDialog.ClosingListener
closingCancel() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under a CANCEL condition
closingCancel() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the Cancel button
closingCancel() - Method in class weka.gui.PropertySheetPanel: Pass on a CANCEL closing notificiation to the customizer (if one is in use).
closingOK() - Method in interface weka.gui.beans.GOECustomizer: Gets called when the customizer is closing under an OK condition
closingOK() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Actions to perform when the user has closed the dialog with the OK button.
closingOK() - Method in class weka.gui.PropertySheetPanel: Pass on an OK closing notification to the customizer (if one is in use)
Cls - Class in weka.gui.simplecli: Clears the output area.
Cls() - Constructor for class weka.gui.simplecli.Cls
Cluster - Class in weka.core.pmml.jaxbbindings: Java class for Cluster element declaration.
Cluster() - Constructor for class weka.core.pmml.jaxbbindings.Cluster
ClusterDefinition - Class in weka.datagenerators: Ancestor to all ClusterDefinitions, i.e., subclasses that handle their own parameters that the cluster generator only passes on.
ClusterDefinition() - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster, without a parent cluster (necessary for GOE)
ClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.ClusterDefinition: initializes the cluster by setting the parent and the defaults
clusterDefinitionsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
Clusterer - Interface in weka.clusterers: Interface for clusterers.
Clusterer - Class in weka.gui.beans: Bean that wraps around weka.clusterers
Clusterer() - Constructor for class weka.gui.beans.Clusterer: Creates a new Clusterer instance.
Clusterer - Class in weka.knowledgeflow.steps: Step that wraps a Weka clusterer.
Clusterer() - Constructor for class weka.knowledgeflow.steps.Clusterer
ClustererAssignmentsPlotInstances - Class in weka.gui.explorer: A class for generating plottable cluster assignments.
ClustererAssignmentsPlotInstances() - Constructor for class weka.gui.explorer.ClustererAssignmentsPlotInstances
ClustererBeanInfo - Class in weka.gui.beans: BeanInfo class for the Clusterer wrapper bean
ClustererBeanInfo() - Constructor for class weka.gui.beans.ClustererBeanInfo
ClustererCustomizer - Class in weka.gui.beans: GUI customizer for the Clusterer wrapper bean
ClustererCustomizer() - Constructor for class weka.gui.beans.ClustererCustomizer
ClustererPanel - Class in weka.gui.explorer: This panel allows the user to select and configure a clusterer, and evaluate the clusterer using a number of testing modes (test on the training data, train/test on a percentage split, test on a separate split).
ClustererPanel() - Constructor for class weka.gui.explorer.ClustererPanel: Creates the clusterer panel
ClustererPanel.TestMode - Enum in weka.gui.explorer
ClustererPanelLaunchHandlerPlugin - Interface in weka.gui.explorer: Interface to plugin that can take the current state of the Clusterer panel and execute it.
ClustererPerformanceEvaluator - Class in weka.gui.beans: A bean that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluator
ClustererPerformanceEvaluator - Class in weka.knowledgeflow.steps: A step that evaluates the performance of batch trained clusterers
ClustererPerformanceEvaluator() - Constructor for class weka.knowledgeflow.steps.ClustererPerformanceEvaluator
ClustererPerformanceEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the clusterer performance evaluator
ClustererPerformanceEvaluatorBeanInfo() - Constructor for class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
clustererTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the tip text for this property
clustererTipText() - Method in class weka.clusterers.SingleClustererEnhancer: Returns the tip text for this property
clustererTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the tip text for this property
clustererTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the tip text for this property.
ClusterEvaluation - Class in weka.clusterers: Class for evaluating clustering models.
ClusterEvaluation() - Constructor for class weka.clusterers.ClusterEvaluation: Constructor.
ClusterGenerator - Class in weka.datagenerators: Abstract class for cluster data generators.
ClusterGenerator() - Constructor for class weka.datagenerators.ClusterGenerator: initializes the generator
ClusteringField - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringField element declaration.
ClusteringField() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringField
ClusteringModel - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModel element declaration.
ClusteringModel() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModel
ClusteringModelQuality - Class in weka.core.pmml.jaxbbindings: Java class for ClusteringModelQuality element declaration.
ClusteringModelQuality() - Constructor for class weka.core.pmml.jaxbbindings.ClusteringModelQuality
clusterInstance(Instance) - Method in class weka.clusterers.AbstractClusterer: Classifies a given instance.
clusterInstance(Instance) - Method in interface weka.clusterers.Clusterer: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.Cobweb: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.FarthestFirst: Classifies a given instance.
clusterInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
clusterInstance(Instance) - Method in class weka.clusterers.SimpleKMeans: Classifies a given instance.
ClusterMembership - Class in weka.filters.unsupervised.attribute: A filter that uses a density-based clusterer to generate cluster membership values; filtered instances are composed of these values plus the class attribute (if set in the input data).
ClusterMembership() - Constructor for class weka.filters.unsupervised.attribute.ClusterMembership
clusterPriors() - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in interface weka.clusterers.DensityBasedClusterer: Returns the prior probability of each cluster.
clusterPriors() - Method in class weka.clusterers.EM: Returns the cluster priors.
clusterPriors() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the cluster priors.
clusterResultsToString() - Method in class weka.clusterers.ClusterEvaluation: return the results of clustering.
clusterSubTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
clusterTypeTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
CNode(int) - Constructor for class weka.clusterers.Cobweb.CNode: Creates an empty CNode instance.
CNode(int, Instance) - Constructor for class weka.clusterers.Cobweb.CNode: Creates a new leaf CNode instance.
Cobweb - Class in weka.clusterers: Class implementing the Cobweb and Classit clustering algorithms.

Note: the application of node operators (merging, splitting etc.) in terms of ordering and priority differs (and is somewhat ambiguous) between the original Cobweb and Classit papers.
Cobweb() - Constructor for class weka.clusterers.Cobweb: default constructor
Cobweb.CNode - Class in weka.clusterers: Inner class handling node operations for Cobweb.
cochransCriterion(double[][]) - Static method in class weka.core.ContingencyTables: Tests if Cochran's criterion is fullfilled for the given contingency table.
codingCost() - Method in class weka.classifiers.trees.j48.C45Split: Returns coding cost for split (used in rule learner).
codingCost() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns coding costs of model.
Coefficient - Class in weka.core.pmml.jaxbbindings: Java class for Coefficient element declaration.
Coefficient() - Constructor for class weka.core.pmml.jaxbbindings.Coefficient
coefficients() - Method in class weka.classifiers.functions.LinearRegression: Returns the coefficients for this linear model.
coefficients() - Method in class weka.classifiers.functions.Logistic: Returns the coefficients for this logistic model.
coefficients() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Return the array of coefficients
Coefficients - Class in weka.core.pmml.jaxbbindings: Java class for Coefficients element declaration.
Coefficients() - Constructor for class weka.core.pmml.jaxbbindings.Coefficients
collapse() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Collapses a tree to a node if training error doesn't increase.
collapseTreeTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
colNameWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
COLON - Static variable in interface weka.core.json.sym
COLOR_STDERR - Static variable in class weka.gui.LogWindow: the Color of the style for stderr
COLOR_STDOUT - Static variable in class weka.gui.LogWindow: the color of the style for stdout
ColorEditor - Class in weka.gui: A property editor for colors that uses JColorChooser as the underlying editor.
ColorEditor() - Constructor for class weka.gui.ColorEditor
Colors - Class in weka.gui.treevisualizer: This class maintains a list that contains all the colornames from the dotty standard and what color (in RGB) they represent
Colors() - Constructor for class weka.gui.treevisualizer.Colors
combinationRuleTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
combinedDL(double, double) - Method in class weka.classifiers.rules.RuleStats: Compute the combined DL of the ruleset in this class, i.e.
combSort11(double[], int[]) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch: sorts the two given arrays.
COMMA - Static variable in interface weka.core.expressionlanguage.parser.sym
COMMA - Static variable in interface weka.core.json.sym
CommandlineCompletion() - Constructor for class weka.gui.SimpleCLIPanel.CommandlineCompletion: default constructor.
CommandlineRunnable - Interface in weka.core: Interface to something that can be run from the command line.
compactify() - Method in class weka.core.Instances: Compactifies the set of instances.
compare(String, String) - Method in class weka.core.ClassDiscovery.StringCompare: Compares its two arguments for order.
compare(Instance, Instance) - Method in class weka.core.InstanceComparator: compares the two instances, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(String, String) - Static method in class weka.core.packageManagement.VersionPackageConstraint: Returns a VersionComparison that represents the comparison between the supplied version 1 and version 2.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseInsensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(String, String) - Method in class weka.filters.unsupervised.attribute.SortLabels.CaseSensitiveComparator: compares the two strings, returns -1 if o1 is smaller than o2, 0 if equal and +1 if greater.
compare(Sorter.InstanceHolder, Sorter.InstanceHolder) - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Compare two instances according to the rule
COMPAREFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for COMPARE-FUNCTION.
compareTo(AssociationRule) - Method in class weka.associations.AssociationRule: Compare this rule to the supplied rule.
compareTo(Item) - Method in class weka.associations.Item: Ensures that items will be sorted in descending order of frequency.
compareTo(SplitCandidate) - Method in class weka.classifiers.trees.ht.SplitCandidate
compareTo(AttributeLocator) - Method in class weka.core.AttributeLocator: Compares this object with the specified object for order.
compareTo(String) - Method in class weka.core.Version: checks the version of this class against the given version-string
compareTo(AbstractSetupPanel) - Method in class weka.gui.experiment.AbstractSetupPanel: Uses the name for comparison.
compareTo(AbstractCommand) - Method in class weka.gui.simplecli.AbstractCommand: Performs comparison just on the name.
compareTo(SortedTableModel.SortContainer) - Method in class weka.gui.SortedTableModel.SortContainer: Compares this object with the specified object for order.
ComparisonMeasure - Class in weka.core.pmml.jaxbbindings: Java class for ComparisonMeasure element declaration.
ComparisonMeasure() - Constructor for class weka.core.pmml.jaxbbindings.ComparisonMeasure
Comparisons - Class in weka.core.pmml.jaxbbindings: Java class for Comparisons element declaration.
Comparisons() - Constructor for class weka.core.pmml.jaxbbindings.Comparisons
ComponentHelper - Class in weka.gui: A helper class for some common tasks with Dialogs, Icons, etc.
ComponentHelper() - Constructor for class weka.gui.ComponentHelper
componentHidden(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentMoved(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentResized(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
componentShown(ComponentEvent) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer
CompoundPredicate - Class in weka.core.pmml.jaxbbindings: Java class for CompoundPredicate element declaration.
CompoundPredicate() - Constructor for class weka.core.pmml.jaxbbindings.CompoundPredicate
CompoundRule - Class in weka.core.pmml.jaxbbindings: Java class for CompoundRule element declaration.
CompoundRule() - Constructor for class weka.core.pmml.jaxbbindings.CompoundRule
compressOutputTipText() - Method in class weka.core.converters.ArffSaver: Returns the tip text for this property
compressOutputTipText() - Method in class weka.core.converters.JSONSaver: Returns the tip text for this property.
compressOutputTipText() - Method in class weka.core.converters.XRFFSaver: Returns the tip text for this property
Compute - Interface in weka.experiment: Interface to something that can accept remote connections and execute a task.
computeAttributeImportanceTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
computeAverageImpurityDecreasePerAttribute(double[]) - Method in class weka.classifiers.trees.RandomForest: Computes the average impurity decrease per attribute over the trees
computeMinMaxAtts() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set up the bounds of our graphic based by finding the smallest reasonable area in the instance space to surround our data points.
Con1 - Class in weka.core.pmml.jaxbbindings: Java class for Con element declaration.
Con1() - Constructor for class weka.core.pmml.jaxbbindings.Con1
CON_AUX_DATA_BATCH_ASSOCIATION_RULES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_DATA_POINT - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_LEGEND - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_MAX - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CHART_MIN - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_CLASS_ATTRIBUTE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_PROPERTIES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_RESULTS - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_ENVIRONMENT_VARIABLES - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_GRAPH_TITLE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_GRAPH_TYPE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_INCREMENTAL_STREAM_END - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_IS_INCREMENTAL - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_LABEL - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_MAX_SET_NUM - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_PRIMARY_PAYLOAD_NOT_THREAD_SAFE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_SET_NUM - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TEST_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TESTSET - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TEXT_TITLE - Static variable in interface weka.knowledgeflow.StepManager
CON_AUX_DATA_TRAININGSET - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_ASSOCIATOR - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_CLASSIFIER - Static variable in interface weka.knowledgeflow.StepManager
CON_BATCH_CLUSTERER - Static variable in interface weka.knowledgeflow.StepManager
CON_CHART - Static variable in interface weka.knowledgeflow.StepManager
CON_DATASET - Static variable in interface weka.knowledgeflow.StepManager
CON_ENVIRONMENT - Static variable in interface weka.knowledgeflow.StepManager
CON_GRAPH - Static variable in interface weka.knowledgeflow.StepManager
CON_IMAGE - Static variable in interface weka.knowledgeflow.StepManager
CON_INCREMENTAL_CLASSIFIER - Static variable in interface weka.knowledgeflow.StepManager
CON_INCREMENTAL_CLUSTERER - Static variable in interface weka.knowledgeflow.StepManager
CON_INFO - Static variable in interface weka.knowledgeflow.StepManager
CON_INSTANCE - Static variable in interface weka.knowledgeflow.StepManager
CON_JOB_FAILURE - Static variable in interface weka.knowledgeflow.StepManager
CON_JOB_SUCCESS - Static variable in interface weka.knowledgeflow.StepManager
CON_TESTSET - Static variable in interface weka.knowledgeflow.StepManager
CON_TEXT - Static variable in interface weka.knowledgeflow.StepManager
CON_THRESHOLD_DATA - Static variable in interface weka.knowledgeflow.StepManager
CON_TRAININGSET - Static variable in interface weka.knowledgeflow.StepManager
CON_VISUALIZABLE_ERROR - Static variable in interface weka.knowledgeflow.StepManager
cond() - Method in class weka.core.matrix.Matrix: Matrix condition (2 norm)
cond() - Method in class weka.core.matrix.SingularValueDecomposition: Two norm condition number
ConditionalDensityEstimator - Interface in weka.classifiers: Interface for numeric prediction schemes that can output conditional density estimates.
ConditionalEstimator - Interface in weka.estimators: Interface for conditional probability estimators.
ConditionalSufficientStats - Class in weka.classifiers.trees.ht: Records sufficient stats for an attribute
ConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.ConditionalSufficientStats
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.Split: Returns the condition for the supplied branch name
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit
conditionForBranch(String) - Method in class weka.classifiers.trees.ht.UnivariateNumericBinarySplit
confidenceFactorTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
confidenceFactorTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
confidenceForRule(AprioriItemSet, AprioriItemSet) - Static method in class weka.associations.AprioriItemSet: Outputs the confidence for a rule.
CONFIG - Static variable in class weka.core.Debug: the log level Vonfig
ConfigurationEvent - Class in weka.gui.beans: Matching event for ConfigurationListener.
ConfigurationEvent(Object) - Constructor for class weka.gui.beans.ConfigurationEvent
ConfigurationListener - Interface in weka.gui.beans: Matching listener for ConfigurationEvent.
ConfigurationProducer - Interface in weka.gui.beans: Marker interface for components that can share their configuration.
configureRangeFromRangeStringOrAttributeNameList(Instances, String) - Static method in class weka.core.Utils: Returns a configured Range object given a 1-based range index string (such as 1-20,35,last) or a comma-separated list of attribute names.
ConfusionMatrix - Class in weka.classifiers.evaluation: Cells of this matrix correspond to counts of the number (or weight) of predictions for each actual value / predicted value combination.
confusionMatrix() - Method in class weka.classifiers.Evaluation: Returns a copy of the confusion matrix.
ConfusionMatrix(String[]) - Constructor for class weka.classifiers.evaluation.ConfusionMatrix: Creates the confusion matrix with the given class names.
confusionMatrix() - Method in class weka.classifiers.evaluation.Evaluation: Returns a copy of the confusion matrix.
ConfusionMatrix - Class in weka.core.pmml.jaxbbindings: Java class for ConfusionMatrix element declaration.
ConfusionMatrix() - Constructor for class weka.core.pmml.jaxbbindings.ConfusionMatrix
ConjugateGradientOptimization - Class in weka.core: This subclass of Optimization.java implements conjugate gradient descent rather than BFGS updates, by overriding findArgmin(), with the same tests for convergence, and applies the same line search code.
ConjugateGradientOptimization() - Constructor for class weka.core.ConjugateGradientOptimization: Constructor that sets MAXITS to 2000 by default and the parameter in the second weak Wolfe condition to 0.1.
connect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection: Connects two units together.
CONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent: it was a connect try
CONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This flag is set once the unit has a connection.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractDataSink: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(String) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractEvaluator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Appender: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Associator: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in interface weka.gui.beans.BeanCommon: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassAssigner: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Classifier: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ClassValuePicker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.DataVisualizer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection with respect to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Filter: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(String) - Method in class weka.gui.beans.FlowByExpression
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(String) - Method in class weka.gui.beans.ImageSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(String) - Method in class weka.gui.beans.ImageViewer
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at this time, the object will accept a connection with respect to the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(String) - Method in class weka.gui.beans.Join: Returns true if the named connection can be made at this time
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.Loader: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Returns true if, at this time, the object will accept a connection with respect to the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.MetaBean
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied event name
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.PredictionAppender: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor.
connectionAllowed(String) - Method in class weka.gui.beans.SerializedModelSaver: Returns true if, at this time, the object will accept a connection according to the supplied event name.
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.Sorter: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.StripChart: Returns true if, at this time, the object will accept a connection according to the supplied EventSetDescriptor
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(String) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at this time, the object will accept a connection via the named event
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextSaver
connectionAllowed(String) - Method in class weka.gui.beans.TextSaver
connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the supplied EventSetDescriptor
connectionAllowed(String) - Method in class weka.gui.beans.TextViewer: Returns true if, at this time, the object will accept a connection via the named event
connectionChange(ConnectionEvent) - Method in interface weka.gui.sql.event.ConnectionListener: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.QueryPanel: This method gets called when the connection is either established or disconnected.
connectionChange(ConnectionEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when the connection is either established or disconnected.
ConnectionEvent - Class in weka.gui.sql.event: An event that is generated when a connection is established or dropped.
ConnectionEvent(Object, int, DbUtils) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionEvent(Object, int, DbUtils, Exception) - Constructor for class weka.gui.sql.event.ConnectionEvent: constructs the event
ConnectionListener - Interface in weka.gui.sql.event: A listener for connect/disconnect events.
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Appender: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Associator: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Classifier: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.CrossValidationFoldMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.DataVisualizer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.Filter: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.FlowByExpression
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.ImageViewer
connectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Notify this object that it has been registered as a listener with a source with respect to the named event
connectionNotification(String, Object) - Method in class weka.gui.beans.Join: Deals with a new connection
connectionNotification(String, Object) - Method in class weka.gui.beans.Loader: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean: Notify this object that it has been registered as a listener with a source with respect to the named event.
connectionNotification(String, Object) - Method in class weka.gui.beans.ModelPerformanceChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
connectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver: Notify this object that it has been registered as a listener with a source with respect to the supplied event name.
connectionNotification(String, Object) - Method in class weka.gui.beans.Sorter: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.StripChart: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringLabeler: Notify this object that it has been registered as a listener with a source for receiving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.SubstringReplacer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TextSaver
connectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer: Notify this object that it has been registered as a listener with a source for recieving events described by the named event This object is responsible for recording this fact.
connectionNotification(String, Object) - Method in class weka.gui.beans.TrainTestSplitMaker: Notify this object that it has been registered as a listener with a source with respect to the supplied event name
ConnectionNotificationConsumer - Interface in weka.gui.beans: Interface for Beans that can receive (dis-)connection events generated when (dis-)connecting data processing nodes in the Weka KnowledgeFlow.
ConnectionPanel - Class in weka.gui.sql: Enables the user to insert a database URL, plus user/password to connect to this database.
ConnectionPanel(JFrame) - Constructor for class weka.gui.sql.ConnectionPanel: initializes the panel.
CONNECTIONS - Static variable in class weka.knowledgeflow.JSONFlowUtils
connectSteps(StepManagerImpl, StepManagerImpl, String) - Method in class weka.gui.knowledgeflow.VisibleLayout: Connect the supplied source step to the supplied target step using the specified connection type
connectSteps(StepManagerImpl, StepManagerImpl, String) - Method in class weka.knowledgeflow.Flow: Connect the supplied source and target steps using the given connectionType.
connectSteps(StepManagerImpl, StepManagerImpl, String, boolean) - Method in class weka.knowledgeflow.Flow: Connect the supplied source and target steps using the given connectionType.
connectToDatabase() - Method in class weka.core.converters.DatabaseLoader: Opens a connection to the database
connectToDatabase() - Method in class weka.core.converters.DatabaseSaver: Opens a connection to the database.
connectToDatabase() - Method in class weka.experiment.DatabaseUtils: Opens a connection to the database.
ConsequentSequence - Class in weka.core.pmml.jaxbbindings: Java class for ConsequentSequence element declaration.
ConsequentSequence() - Constructor for class weka.core.pmml.jaxbbindings.ConsequentSequence
conservativeForwardSelectionTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
ConsoleLogger - Class in weka.core.logging: A simple logger that outputs the logging information in the console.
ConsoleLogger() - Constructor for class weka.core.logging.ConsoleLogger
CONST - Static variable in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateKernelEstimator: Constant for Gaussian density.
CONST - Static variable in class weka.estimators.UnivariateNormalEstimator: Constant for Gaussian density
CONST_AUTOMATIC_SHAPE - Static variable in class weka.gui.visualize.Plot2D
CONSTANT - Static variable in class weka.classifiers.lazy.LWL
Constant - Class in weka.core.pmml: Class encapsulating a Constant Expression.
Constant(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Constant: Construct an new Constant Expression.
Constant - Class in weka.core.pmml.jaxbbindings: Java class for Constant element declaration.
Constant() - Constructor for class weka.core.pmml.jaxbbindings.Constant
Constraints - Class in weka.core.pmml.jaxbbindings: Java class for Constraints element declaration.
Constraints() - Constructor for class weka.core.pmml.jaxbbindings.Constraints
constructMappedInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
constructWithCopy(double[][]) - Static method in class weka.core.matrix.Matrix: Construct a matrix from a copy of a 2-D array.
containChildBallsTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the tip text for this property.
containedBy(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
containedByTreatZeroAsMissing(Instance) - Method in class weka.associations.ItemSet: Checks if an instance contains an item set.
contains(int) - Method in class weka.classifiers.bayes.net.ParentSet: test if node is contained in parent set
contains(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Checks whether an element is in the set.
contains(String) - Method in class weka.core.pmml.Array: Returns true if the array contains this string value.
contains(int) - Method in class weka.core.pmml.Array: Returns true if the array contains this integer value.
contains(double) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(float) - Method in class weka.core.pmml.Array: Returns true if the array contains this real value.
contains(PrintStream) - Method in class weka.core.Tee: checks whether the given PrintStream is already in the list.
contains(Object) - Method in class weka.core.Trie: Returns true if this collection contains the specified element.
contains(String) - Method in class weka.core.Trie.TrieNode: checks whether a suffix can be found in its children
contains(String) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given property
contains(Class<?>) - Method in class weka.core.xml.MethodHandler: checks whether a method is stored for the given class
contains(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Tests whether the specified object is a component in this list.
contains(String) - Method in class weka.gui.HierarchyPropertyParser: Whether the HierarchyPropertyParser contains the given string
containsAll(Collection<?>) - Method in class weka.core.Trie: Returns true if this collection contains all of the elements in the specified collection.
containsEnvVariables(String) - Static method in class weka.core.Environment: Tests for the presence of environment variables.
containsItems(ArrayList<Item>, boolean) - Method in class weka.associations.AssociationRule
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Tests if the specified double is a key in this hashtable.
containsKey(double) - Method in class weka.classifiers.lazy.kstar.KStarCache: Checks if the specified key maps with an entry in the cache table
containsPrefix(String) - Method in class weka.core.Trie: checks whether the given prefix is stored in the trie
containsValue(double) - Method in class weka.core.pmml.FieldMetaInfo.Interval: Returns true if this interval contains the supplied value.
containsWindow(Class<?>) - Method in class weka.gui.Main: checks, whether an instance of the given window class is already in the Window list.
containsWindow(String) - Method in class weka.gui.Main: checks, whether a window with the given title is already in the Window list.
context() - Method in class weka.gui.HierarchyPropertyParser: The context of the current node, i.e.
ContingencyTables - Class in weka.core: Class implementing some statistical routines for contingency tables.
ContingencyTables() - Constructor for class weka.core.ContingencyTables
CONTINUOUS - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster subtype: continuous
CONTSCORINGMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for CONT-SCORING-METHOD.
ContStats - Class in weka.core.pmml.jaxbbindings: Java class for ContStats element declaration.
ContStats() - Constructor for class weka.core.pmml.jaxbbindings.ContStats
ConverterFileChooser - Class in weka.gui: A specialized JFileChooser that lists all available file Loaders and Savers.
ConverterFileChooser() - Constructor for class weka.gui.ConverterFileChooser: onstructs a FileChooser pointing to the user's default directory.
ConverterFileChooser(File) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given File as the path.
ConverterFileChooser(String) - Constructor for class weka.gui.ConverterFileChooser: Constructs a FileChooser using the given path.
ConverterResources - Class in weka.core.converters: Helper class for dealing with Converter resources.
ConverterResources() - Constructor for class weka.core.converters.ConverterResources
ConverterUtils - Class in weka.core.converters: Utility routines for the converter package.
ConverterUtils() - Constructor for class weka.core.converters.ConverterUtils
ConverterUtils.DataSink - Class in weka.core.converters: Helper class for saving data to files.
ConverterUtils.DataSource - Class in weka.core.converters: Helper class for loading data from files and URLs.
convertInstance(Instance) - Method in interface weka.attributeSelection.AttributeTransformer: Transforms an instance in the format of the original data to the transformed space
convertInstance(Instance) - Method in class weka.attributeSelection.PrincipalComponents: Transform an instance in original (unormalized) format.
convertNewLines(String) - Static method in class weka.core.Utils: Converts carriage returns and new lines in a string into \r and \n.
convertNominalTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
convertNumericAttToNominal(int, ArrayList<String>) - Method in class weka.core.pmml.MiningSchema: Convert a numeric attribute in the mining schema to nominal.
convertStringAttsToNominal() - Method in class weka.core.pmml.MiningSchema: Method to convert any string attributes in the mining schema Instances to nominal attributes.
convertToAttribX(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel x coordinate to a raw x value.
convertToAttribY(double) - Method in class weka.gui.visualize.Plot2D: convert a Panel y coordinate to a raw y value.
convertToPanelX(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw x value to Panel x coordinate.
convertToPanelY(double) - Method in class weka.gui.visualize.Plot2D: Convert an raw y value to Panel y coordinate.
convertToRelativePath(File) - Static method in class weka.core.Utils: Converts a File's absolute path to a path relative to the user (ie start) directory.
convictionForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet: Outputs the conviction for a rule.
COORDINATES - Static variable in class weka.knowledgeflow.JSONFlowUtils
copy(ParentSet) - Method in class weka.classifiers.bayes.net.ParentSet: Copy makes current parents set equal to other parent set
copy() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Return a shallow copy of this kernel
copy() - Method in class weka.classifiers.rules.JRip.Antd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NominalAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.NumericAntd: Implements Copyable
copy() - Method in class weka.classifiers.rules.JRip.RipperRule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.rules.Rule: Get a shallow copy of this rule
copy() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Makes a copy of this CorrelationSplitInfo object
copy() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: makes a copy of the SplitEvaluate object
copy() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Makes a copy of this SplitInfo object
copy() - Method in class weka.core.Attribute: Produces a shallow copy of this attribute.
copy(String) - Method in class weka.core.Attribute: Produces a shallow copy of this attribute with a new name.
copy() - Method in class weka.core.BinarySparseInstance: Produces a shallow copy of this instance.
copy(double[]) - Method in class weka.core.BinarySparseInstance: Copies the instance but fills up its values based on the given array of doubles.
copy() - Method in interface weka.core.Copyable: This method produces a shallow copy of an object.
copy() - Method in class weka.core.DenseInstance: Produces a shallow copy of this instance.
copy(double[]) - Method in class weka.core.DenseInstance: Copies the instance but fills up its values based on the given array of doubles.
copy() - Method in class weka.core.FastVector: Deprecated.

Produces a shallow copy of this vector.
copy(double[]) - Method in interface weka.core.Instance: Copies the instance but fills up its values based on the given array of doubles.
copy() - Method in class weka.core.matrix.DoubleVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.IntVector: Makes a deep copy of the vector
copy() - Method in class weka.core.matrix.Matrix: Make a deep copy of a matrix
copy() - Method in class weka.core.SparseInstance: Produces a shallow copy of this instance.
copy(double[]) - Method in class weka.core.SparseInstance: Copies the instance but fills up its values based on the given array of doubles.
Copy - Class in weka.filters.unsupervised.attribute: An instance filter that copies a range of attributes in the dataset.
Copy() - Constructor for class weka.filters.unsupervised.attribute.Copy
copy(File, File) - Static method in class weka.gui.scripting.ScriptUtils: Copies the file/directory (recursively).
Copyable - Interface in weka.core: Interface implemented by classes that can produce "shallow" copies of their objects.
copyArea(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
copyContent() - Method in class weka.gui.arffviewer.ArffPanel: copies the content of the selection to the clipboard
copyContent() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: copies the content of the selection to the clipboard
copyElements() - Method in class weka.core.FastVector: Deprecated.

Clones the vector and shallow copies all its elements.
copyFlow() - Method in class weka.knowledgeflow.Flow: Make a copy of this Flow
copyFlowToClipboard(Flow) - Method in class weka.gui.knowledgeflow.MainKFPerspective
copyInto(Object[]) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Copies the components of this list into the specified array.
copyRelationalValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Copies relational values contained in the instance copied to a new dataset.
copyRelationalValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.RelationalLocator: Takes relational values referenced by an Instance and copies them from a source dataset to a destination dataset.
Copyright - Class in weka.core: A class for providing centralized Copyright information.
Copyright() - Constructor for class weka.core.Copyright
copyStepsToClipboard(List<StepVisual>) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Copy the supplied steps to the clipboard
copyStringValues(Instance, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Copies string values contained in the instance copied to a new dataset.
copyStringValues(Instance, boolean, Instances, AttributeLocator, Instances, AttributeLocator) - Static method in class weka.core.StringLocator: Takes string values referenced by an Instance and copies them from a source dataset to a destination dataset.
copyToBuffer(Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp: Utility routine that serializes the supplied Vector of BeanInstances to XML
copyToClipboard() - Method in class weka.gui.sql.InfoPanel: copies the currently selected error message to the clipboard
CORE_FILE_LOADERS - Static variable in class weka.core.converters.ConverterResources: the core loaders - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
CORE_FILE_SAVERS - Static variable in class weka.core.converters.ConverterResources: the core savers - hardcoded list necessary for RMI/Remote Experiments (comma-separated list).
correct() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of correct classifications (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correct() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances correctly classified (that is, for which a correct prediction was made).
correlation(double[], double[], int) - Static method in class weka.core.Utils: Returns the correlation coefficient of two double vectors.
correlation - Variable in class weka.experiment.PairedStats: The correlation coefficient
CorrelationAttributeEval - Class in weka.attributeSelection: CorrelationAttributeEval :

Evaluates the worth of an attribute by measuring the correlation (Pearson's) between it and the class.

Nominal attributes are considered on a value by value basis by treating each value as an indicator.
CorrelationAttributeEval() - Constructor for class weka.attributeSelection.CorrelationAttributeEval
correlationCoefficient() - Method in class weka.classifiers.Evaluation: Returns the correlation coefficient if the class is numeric.
correlationCoefficient() - Method in class weka.classifiers.evaluation.Evaluation: Returns the correlation coefficient if the class is numeric.
CorrelationFields - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationFields element declaration.
CorrelationFields() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationFields
CorrelationMethods - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationMethods element declaration.
CorrelationMethods() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationMethods
Correlations - Class in weka.core.pmml.jaxbbindings: Java class for Correlations element declaration.
Correlations() - Constructor for class weka.core.pmml.jaxbbindings.Correlations
CorrelationSplitInfo - Class in weka.classifiers.trees.m5: Finds split points using correlation.
CorrelationSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.CorrelationSplitInfo: Constructs an object which contains the split information
CorrelationValues - Class in weka.core.pmml.jaxbbindings: Java class for CorrelationValues element declaration.
CorrelationValues() - Constructor for class weka.core.pmml.jaxbbindings.CorrelationValues
CostBenefitAnalysis - Class in weka.gui.beans: Bean that aids in analyzing cost/benefit tradeoffs.
CostBenefitAnalysis() - Constructor for class weka.gui.beans.CostBenefitAnalysis: Constructor.
CostBenefitAnalysis - Class in weka.knowledgeflow.steps: Step for storing and viewing threshold data in a cost-benefit visualization
CostBenefitAnalysis() - Constructor for class weka.knowledgeflow.steps.CostBenefitAnalysis
CostBenefitAnalysisBeanInfo - Class in weka.gui.beans: Bean info class for the cost/benefit analysis
CostBenefitAnalysisBeanInfo() - Constructor for class weka.gui.beans.CostBenefitAnalysisBeanInfo
CostBenefitAnalysisInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive view for the CostBenefitAnalysis step
CostBenefitAnalysisInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.CostBenefitAnalysisInteractiveView
CostBenefitAnalysisPanel - Class in weka.gui: Panel for displaying the cost-benefit plots and all control widgets.
CostBenefitAnalysisPanel() - Constructor for class weka.gui.CostBenefitAnalysisPanel
CostCurve - Class in weka.classifiers.evaluation: Generates points illustrating probablity cost tradeoffs that can be obtained by varying the threshold value between classes.
CostCurve() - Constructor for class weka.classifiers.evaluation.CostCurve
CostMatrix - Class in weka.classifiers: Class for storing and manipulating a misclassification cost matrix.
CostMatrix(int) - Constructor for class weka.classifiers.CostMatrix: Creates a default cost matrix of a particular size.
CostMatrix(CostMatrix) - Constructor for class weka.classifiers.CostMatrix: Creates a cost matrix that is a copy of another.
CostMatrix(Reader) - Constructor for class weka.classifiers.CostMatrix: Reads a matrix from a reader.
CostMatrixEditor - Class in weka.gui: Class for editing CostMatrix objects.
CostMatrixEditor() - Constructor for class weka.gui.CostMatrixEditor: Constructs a new CostMatrixEditor.
costMatrixSourceTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
costMatrixTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
CostSensitiveClassifier - Class in weka.classifiers.meta: A metaclassifier that makes its base classifier cost sensitive.
CostSensitiveClassifier() - Constructor for class weka.classifiers.meta.CostSensitiveClassifier: Default constructor.
CostSensitiveClassifierSplitEvaluator - Class in weka.experiment: SplitEvaluator that produces results for a classification scheme on a nominal class attribute, including weighted misclassification costs.
CostSensitiveClassifierSplitEvaluator() - Constructor for class weka.experiment.CostSensitiveClassifierSplitEvaluator
Count(double) - Constructor for class weka.classifiers.functions.SGDText.Count
count - Variable in class weka.experiment.PairedStats: The number of data points seen
count - Variable in class weka.experiment.Stats: The number of values seen
countData() - Method in class weka.classifiers.rules.RuleStats: Filter the data according to the ruleset and compute the basic stats: coverage/uncoverage, true/false positive/negatives of each rule
countData(int, Instances, double[][]) - Method in class weka.classifiers.rules.RuleStats: Count data from the position index in the ruleset assuming that given data are not covered by the rules in position 0...(index-1), and the statistics of these rules are provided.
This procedure is typically useful when a temporary object of RuleStats is constructed in order to efficiently calculate the relative DL of rule in position index, thus all other stuff is not needed.
counter() - Method in class weka.associations.ItemSet: Gets the counter
Counts - Class in weka.core.pmml.jaxbbindings: Java class for Counts element declaration.
Counts() - Constructor for class weka.core.pmml.jaxbbindings.Counts
countsForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet: Calculates the counts for Dirichlet distribution for the class membership probabilities for the given test instance.
COUNTTABLETYPE - Class in weka.core.pmml.jaxbbindings: Java class for COUNT-TABLE-TYPE complex type.
COUNTTABLETYPE() - Constructor for class weka.core.pmml.jaxbbindings.COUNTTABLETYPE
countWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
Covariances - Class in weka.core.pmml.jaxbbindings: Java class for Covariances element declaration.
Covariances() - Constructor for class weka.core.pmml.jaxbbindings.Covariances
CovariateList - Class in weka.core.pmml.jaxbbindings: Java class for CovariateList element declaration.
CovariateList() - Constructor for class weka.core.pmml.jaxbbindings.CovariateList
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
coverageOfTestCasesByPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation: Gets the coverage of the test cases by the predicted regions at the confidence level specified when evaluation was performed.
covers(Instance) - Method in class weka.classifiers.rules.JRip.Antd
covers(Instance) - Method in class weka.classifiers.rules.JRip.NominalAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.NumericAntd: Whether the instance is covered by this antecedent
covers(Instance) - Method in class weka.classifiers.rules.JRip.RipperRule: Whether the instance covered by this rule
covers(Instance) - Method in class weka.classifiers.rules.Rule: Whether the instance covered by this rule
CoverTree - Class in weka.core.neighboursearch: Class implementing the CoverTree datastructure.
The class is very much a translation of the c source code made available by the authors.

For more information and original source code see:

Alina Beygelzimer, Sham Kakade, John Langford: Cover trees for nearest neighbor.
CoverTree() - Constructor for class weka.core.neighboursearch.CoverTree: default constructor.
CoverTree.CoverTreeNode - Class in weka.core.neighboursearch: class representing a node of the cover tree.
CoverTreeNode() - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor for the class.
CoverTreeNode(Integer, double, double, Stack<CoverTree.CoverTreeNode>, int, int) - Constructor for class weka.core.neighboursearch.CoverTree.CoverTreeNode: Constructor.
CramersV(double[][]) - Static method in class weka.core.ContingencyTables: Computes Cramer's V for a contingency table.
create() - Static method in class weka.core.packageManagement.PackageManager
create(List<Object>, List<Integer>) - Static method in class weka.core.pmml.Array
create(Element) - Static method in class weka.core.pmml.Array: Static factory method for creating non-sparse or sparse array types as needed.
create(Reader) - Method in class weka.gui.treevisualizer.TreeBuild: This will build A node structure from the dotty format passed.
create() - Method in class weka.gui.visualize.PostscriptGraphics: Clone a PostscriptGraphics object
createAggregate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Aggregate
createAlternate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Alternate
createAnnotation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Annotation
createAnova() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Anova
createAnovaRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnovaRow
createAntecedentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AntecedentSequence
createAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AnyDistribution
createApplication() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Application
createApply() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Apply
createARIMA(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<ArrayType>}
createArrayType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ArrayType
createAssociationModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationModel
createAssociationRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of AssociationRule
createAttribute() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Attribute
createBaseCumHazardTables() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaseCumHazardTables
createBaseline() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Baseline
createBaselineCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineCell
createBaselineModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineModel
createBaselineStratum() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BaselineStratum
createBayesInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInput
createBayesInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesInputs
createBayesOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BayesOutput
createBinarySimilarity() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BinarySimilarity
createBoundaryValueMeans() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValueMeans
createBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of BoundaryValues
createCategoricalPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CategoricalPredictor
createCategories() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Categories
createCategory() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Category
createCharacteristic() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristic
createCharacteristics() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Characteristics
createChebychev() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Chebychev
createChildParent() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ChildParent
createCityBlock() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CityBlock
createClassLabels() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClassLabels
createCluster() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Cluster
createClusteringField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringField
createClusteringModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModel
createClusteringModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ClusteringModelQuality
createCoefficient() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficient
createCoefficients() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Coefficients
createComparisonMeasure() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ComparisonMeasure
createComparisons() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Comparisons
createCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundPredicate
createCompoundRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CompoundRule
createCon() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Con1
createConfusionMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConfusionMatrix
createConsequentSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ConsequentSequence
createConstant() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constant
createConstraints() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Constraints
createContStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ContStats
createCorrelationFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationFields
createCorrelationMethods() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationMethods
createCorrelations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Correlations
createCorrelationValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CorrelationValues
createCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Counts
createCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createCOUNTTABLETYPE() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of COUNTTABLETYPE
createCovariances() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Covariances
createCovariateList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of CovariateList
createDataDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataDictionary
createDataField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DataField
createDecision() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decision
createDecisions() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Decisions
createDecisionTree() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DecisionTree
createDefineFunction() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DefineFunction
createDelimiter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Delimiter
createDerivedField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DerivedField
createDiscretize() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Discretize
createDiscretizeBin() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscretizeBin
createDiscrStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DiscrStats
createDocumentTermMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of DocumentTermMatrix
createEuclidean() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Euclidean
createEventValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of EventValues
createExperimentIndex() - Method in class weka.experiment.DatabaseUtils: Attempts to create the experiment index table.
createExperimentIndexEntry(ResultProducer) - Method in class weka.experiment.DatabaseUtils: Attempts to insert a results entry for the table into the experiment index.
createExponentialSmoothing() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ExponentialSmoothing
createExtension() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Extension
createFactorList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FactorList
createFalse() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of False
createFieldColumnPair() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldColumnPair
createFieldRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldRef
createFieldValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValue
createFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of FieldValueCount
createGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GaussianDistribution
createGeneralRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of GeneralRegressionModel
createHeader() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Header
createIndices(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInlineTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InlineTable
createInstanceField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceField
createInstanceFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of InstanceFields
createINTEntries(List<Integer>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Integer>>}
createInterval() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Interval
createINTSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of INTSparseArray
createItem() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Item
createItemRef() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ItemRef
createItemset() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Itemset
createJaccard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Jaccard
createKNNInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInput
createKNNInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KNNInputs
createKohonenMap() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of KohonenMap
createLevel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Level
createLiftData() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftData
createLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LiftGraph
createLinearKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearKernelType
createLinearNorm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LinearNorm
createLink(String, String) - Static method in class weka.gui.BrowserHelper: Generates a label with a clickable link.
createLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of LocalTransformations
createMapValues() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MapValues
createMatCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MatCell
createMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Matrix
createMiningBuildTask() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningBuildTask
createMiningField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningField
createMiningModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningModel
createMiningSchema() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MiningSchema
createMinkowski() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Minkowski
createMissingValueWeights() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MissingValueWeights
createModelExplanation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelExplanation
createModelLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelLiftGraph
createModelStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelStats
createModelVerification() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ModelVerification
createMultivariateStat() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStat
createMultivariateStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of MultivariateStats
createNaiveBayesModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NaiveBayesModel
createNamedIndexedStore(String) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Create a indexed store with a given name
createNearestNeighborModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NearestNeighborModel
createNeuralInput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInput
createNeuralInputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralInputs
createNeuralLayer() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralLayer
createNeuralNetwork() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralNetwork
createNeuralOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutput
createNeuralOutputs() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NeuralOutputs
createNeuron() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Neuron
createNewVisualizerWindow(Classifier, Instances) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Creates a new GUI window with all of the BoundaryVisualizer trappings,
createNode() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Node
createNormalizedCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<COUNTTABLETYPE>}
createNormContinuous() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormContinuous
createNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NormDiscrete
createNumericInfo() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericInfo
createNumericPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of NumericPredictor
createOptimumLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OptimumLiftGraph
createOutput() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Output
createOutputField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of OutputField
createPairCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PairCounts
createParameter() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Parameter
createParameterField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterField
createParameterList() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParameterList
createParamMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ParamMatrix
createPartition() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Partition
createPartitionFieldStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PartitionFieldStats
createPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCell
createPCovCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovCell
createPCovMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PCovMatrix
createPMML() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PMML
createPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PoissonDistribution
createPolynomialKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PolynomialKernelType
createPPCell() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPCell
createPPMatrix() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PPMatrix
createPredictiveModelQuality() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictiveModelQuality
createPredictor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Predictor
createPredictorTerm() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of PredictorTerm
createQuantile() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Quantile
createRadialBasisKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RadialBasisKernelType
createRandomLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RandomLiftGraph
createREALEntries(List<Double>) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<List<Double>>}
createREALSparseArray() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of REALSparseArray
createRegression() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Regression
createRegressionModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionModel
createRegressionTable() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RegressionTable
createResultField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ResultField
createResultsTable(ResultProducer, String) - Method in class weka.experiment.DatabaseUtils: Creates a results table for the supplied result producer.
createROC() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROC
createROCGraph() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ROCGraph
createRow() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Row
createRuleSelectionMethod() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSelectionMethod
createRuleSet() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSet
createRuleSetModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of RuleSetModel
createScorecard() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Scorecard
createScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of ScoreDistribution
createSeasonalityExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SeasonalityExpoSmooth
createSeasonalTrendDecomposition(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createSegment() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segment
createSegmentation() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Segmentation
createSequence() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Sequence
createSequenceModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceModel
createSequenceReference() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceReference
createSequenceRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SequenceRule
createSetPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SetPredicate
createSetReference() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SetReference
createSigmoidKernelType() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SigmoidKernelType
createSimpleMatching() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleMatching
createSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimplePredicate
createSimpleRule() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleRule
createSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SimpleSetPredicate
createSingleSettingsEditor(Map<Settings.SettingKey, Object>) - Static method in class weka.gui.SettingsEditor: Creates a single stand-alone settings editor panel
createSingleton(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp: Create the singleton instance of the KnowledgeFlow
createSingleton() - Static method in class weka.gui.GUIChooserApp: Create a singleton instance of the GUIChooser
createSingleton(String[]) - Static method in class weka.gui.Main: Create the singleton instance of the Main GUI.
createSpectralAnalysis(Object) - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of JAXBElement<Object>}
createSquaredEuclidean() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SquaredEuclidean
createStore(String) - Method in interface weka.core.metastore.MetaStore: Create a named store
createStore(String) - Method in class weka.core.metastore.XMLFileBasedMetaStore
createSupportVector() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVector
createSupportVectorMachine() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectorMachine
createSupportVectorMachineModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectorMachineModel
createSupportVectors() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of SupportVectors
createTableLocator() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TableLocator
createTanimoto() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Tanimoto
createTarget() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Target
createTargets() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Targets
createTargetValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValue
createTargetValueCount() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValueCount
createTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TargetValueCounts
createTaxonomy() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Taxonomy
createTestDistributions() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TestDistributions
createTextCorpus() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextCorpus
createTextDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextDictionary
createTextDocument() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextDocument
createTextModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModel
createTextModelNormalization() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModelNormalization
createTextModelSimiliarity() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TextModelSimiliarity
createTime() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Time
createTimeAnchor() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeAnchor
createTimeCycle() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeCycle
createTimeException() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeException
createTimeSeries() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeSeries
createTimeSeriesModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeSeriesModel
createTimestamp() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Timestamp
createTimeValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TimeValue
createTrainingInstances() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TrainingInstances
createTransformationDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TransformationDictionary
createTreeModel() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TreeModel
createTrendExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of TrendExpoSmooth
createTrue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of True
createUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of UniformDistribution
createUnivariateStats() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of UnivariateStats
createValue() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of Value
createVectorDictionary() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorDictionary
createVectorFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorFields
createVectorInstance() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VectorInstance
createVerificationField() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VerificationField
createVerificationFields() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of VerificationFields
createVisual(StepManagerImpl) - Static method in class weka.gui.knowledgeflow.StepVisual: Create a visual for the step managed by the supplied step manager.
createVisual(StepManagerImpl, ImageIcon) - Static method in class weka.gui.knowledgeflow.StepVisual: Create a visual for the step managed by the supplied step manager using the supplied icon.
createXCoordinates() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of XCoordinates
createYCoordinates() - Method in class weka.core.pmml.jaxbbindings.ObjectFactory: Create an instance of YCoordinates
crossValidate(NaiveBayesUpdateable, Instances, Random) - Static method in class weka.classifiers.trees.j48.NBTreeNoSplit: Utility method for fast 5-fold cross validation of a naive bayes model
CrossValidateAttributes() - Method in class weka.attributeSelection.AttributeSelection: Perform a cross validation for attribute selection.
crossValidateModel(Classifier, Instances, int, Random) - Method in class weka.classifiers.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(Classifier, Instances, int, Random) - Method in class weka.classifiers.evaluation.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(Classifier, Instances, int, Random, Object...) - Method in class weka.classifiers.evaluation.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Method in class weka.classifiers.evaluation.Evaluation: Performs a (stratified if class is nominal) cross-validation for a classifier on a set of instances.
crossValidateModel(DensityBasedClusterer, Instances, int, Random) - Static method in class weka.clusterers.ClusterEvaluation: Perform a cross-validation for DensityBasedClusterer on a set of instances.
crossValidateModel(String, Instances, int, String[], Random) - Static method in class weka.clusterers.ClusterEvaluation: Performs a cross-validation for a DensityBasedClusterer clusterer on a set of instances.
crossValidateTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
CrossValidationFoldMaker - Class in weka.gui.beans: Bean for splitting instances into training ant test sets according to a cross validation
CrossValidationFoldMaker() - Constructor for class weka.gui.beans.CrossValidationFoldMaker
CrossValidationFoldMaker - Class in weka.knowledgeflow.steps: Step for generating cross-validation splits
CrossValidationFoldMaker() - Constructor for class weka.knowledgeflow.steps.CrossValidationFoldMaker
CrossValidationFoldMakerBeanInfo - Class in weka.gui.beans: BeanInfo class for the cross validation fold maker bean
CrossValidationFoldMakerBeanInfo() - Constructor for class weka.gui.beans.CrossValidationFoldMakerBeanInfo
CrossValidationFoldMakerCustomizer - Class in weka.gui.beans: GUI Customizer for the cross validation fold maker bean
CrossValidationFoldMakerCustomizer() - Constructor for class weka.gui.beans.CrossValidationFoldMakerCustomizer
CrossValidationResultProducer - Class in weka.experiment: Generates for each run, carries out an n-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationResultProducer() - Constructor for class weka.experiment.CrossValidationResultProducer
CrossValidationSplitResultProducer - Class in weka.experiment: Carries out one split of a repeated k-fold cross-validation, using the set SplitEvaluator to generate some results.
CrossValidationSplitResultProducer() - Constructor for class weka.experiment.CrossValidationSplitResultProducer
crossValTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
CSV - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions as CSV.
CSV() - Constructor for class weka.classifiers.evaluation.output.prediction.CSV
CSVLoader - Class in weka.core.converters: Reads a source that is in comma separated format (the default).
CSVLoader() - Constructor for class weka.core.converters.CSVLoader: default constructor.
CSVResultListener - Class in weka.experiment: Takes results from a result producer and assembles them into comma separated value form.
CSVResultListener() - Constructor for class weka.experiment.CSVResultListener: Sets temporary file.
CSVSaver - Class in weka.core.converters: Writes to a destination that is in CSV (comma-separated values) format.
CSVSaver() - Constructor for class weka.core.converters.CSVSaver: Constructor.
cTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
cTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
cumulate() - Method in class weka.core.matrix.DoubleVector: Returns a vector that stores the cumulated values of the original vector
cumulateInPlace() - Method in class weka.core.matrix.DoubleVector: Cumulates the original vector in place
cumulativeCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: CumulativeCV returns the accuracy calculated using cumulative cross validation.
CUMULATIVELINKFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for CUMULATIVE-LINK-FUNCTION.
currentPlotRowCompleted(int) - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Called when a row of the image being plotted has been completed
currentPlotRowCompleted(int) - Method in interface weka.knowledgeflow.steps.BoundaryPlotter.RenderingUpdateListener: Called when rendering of a row in the current plot has completed
CustomDisplayStringProvider - Interface in weka.core: For classes that do not implement the OptionHandler interface and want to provide a custom display string in the GenericObjectEditor, which is more descriptive than the class name.
customizePopupMenu(JPopupMenu, Object, GenericObjectEditorHistory.HistorySelectionListener) - Method in class weka.gui.GenericObjectEditorHistory: Adds a menu item with the history to the popup menu.
CustomizerCloseRequester - Interface in weka.gui.beans: Customizers who want to be able to close the customizer window themselves can implement this window.
customizerClosing() - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.ClassAssignerCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassifierCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer
customizerClosing() - Method in class weka.gui.beans.ClassValuePickerCustomizer
customizerClosing() - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
customizerClosing() - Method in interface weka.gui.beans.CustomizerClosingListener: Customizer classes that want to know when they are being disposed of can implement this method.
customizerClosing() - Method in class weka.gui.beans.DataVisualizerCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.ImageSaverCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
customizerClosing() - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the ImageSaver to its previous state.
customizerClosing() - Method in class weka.gui.beans.NoteCustomizer
customizerClosing() - Method in class weka.gui.beans.PredictionAppenderCustomizer
customizerClosing() - Method in class weka.gui.beans.SerializedModelSaverCustomizer
customizerClosing() - Method in class weka.gui.beans.TextSaverCustomizer: Gets called if the use closes the dialog via the close widget on the window - is treated as cancel, so restores the TextSaver to its previous state.
CustomizerClosingListener - Interface in weka.gui.beans
CustomPanelSupplier - Interface in weka.gui: An interface for objects that are capable of supplying their own custom GUI components.
customPropsFileTipText() - Method in class weka.core.converters.DatabaseLoader: The tip text for this property.
customPropsFileTipText() - Method in class weka.core.converters.DatabaseSaver: The tip text for this property.
customPropsFileTipText() - Method in class weka.experiment.InstanceQuery: The tip text for this property.
cutoffTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
cutpointsToString(double[], boolean[]) - Static method in class weka.estimators.EstimatorUtils: Returns a string representing the cutpoints.
CVParameterSelection - Class in weka.classifiers.meta: Class for performing parameter selection by cross-validation for any classifier.

For more information, see:

R.
CVParameterSelection() - Constructor for class weka.classifiers.meta.CVParameterSelection
CVParametersTipText() - Method in class weka.classifiers.meta.CVParameterSelection: Returns the tip text for this property
CVResultsString() - Method in class weka.attributeSelection.AttributeSelection: returns a string summarizing the results of repeated attribute selection runs on splits of a dataset.
CVTypeTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm

D

DATA - Static variable in class weka.core.json.JSONInstances: the data section.
Data - Class in weka.knowledgeflow: Class for encapsulating data to be transferred between Knowledge Flow steps over a particular connection type.
Data() - Constructor for class weka.knowledgeflow.Data: Empty constructor - no connection name; no payload
Data(String) - Constructor for class weka.knowledgeflow.Data: Construct a Data object with just a connection name
Data(String, Object) - Constructor for class weka.knowledgeflow.Data: Construct a Data object with a connection name and a primary payload object to associate with the connection name
DatabaseConnection - Class in weka.core.converters: Connects to a database.
DatabaseConnection() - Constructor for class weka.core.converters.DatabaseConnection: Sets up the database drivers.
DatabaseConnection(File) - Constructor for class weka.core.converters.DatabaseConnection: Reads the properties from the specified file and sets up the database drivers.
DatabaseConnection(Properties) - Constructor for class weka.core.converters.DatabaseConnection: Uses the specified properties to set up the database drivers.
DatabaseConnectionDialog - Class in weka.gui: A dialog to enter URL, username and password for a database connection.
DatabaseConnectionDialog(Frame) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConnectionDialog(Frame, String, String, boolean) - Constructor for class weka.gui.DatabaseConnectionDialog: Create database connection dialog.
DatabaseConverter - Interface in weka.core.converters: Marker interface for a loader/saver that uses a database
DatabaseLoader - Class in weka.core.converters: Reads Instances from a Database.
DatabaseLoader() - Constructor for class weka.core.converters.DatabaseLoader: Constructor
DatabaseResultListener - Class in weka.experiment: Takes results from a result producer and sends them to a database.
DatabaseResultListener() - Constructor for class weka.experiment.DatabaseResultListener: Sets up the database drivers
DatabaseResultProducer - Class in weka.experiment: Examines a database and extracts out the results produced by the specified ResultProducer and submits them to the specified ResultListener.
DatabaseResultProducer() - Constructor for class weka.experiment.DatabaseResultProducer: Creates the DatabaseResultProducer, letting the parent constructor do it's thing.
DatabaseSaver - Class in weka.core.converters: Writes to a database (tested with MySQL, InstantDB, HSQLDB).
DatabaseSaver() - Constructor for class weka.core.converters.DatabaseSaver: Constructor.
databaseURLTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
DatabaseUtils - Class in weka.experiment: DatabaseUtils provides utility functions for accessing the experiment database.
DatabaseUtils() - Constructor for class weka.experiment.DatabaseUtils: Reads properties and sets up the database drivers.
DatabaseUtils(File) - Constructor for class weka.experiment.DatabaseUtils: Reads the properties from the specified file and sets up the database drivers.
DatabaseUtils(Properties) - Constructor for class weka.experiment.DatabaseUtils: Uses the specified properties to set up the database drivers.
DataCollector - Interface in weka.knowledgeflow.steps: Auxiliary interface for steps that collect data results of some type - e.g.
DataDictionary - Class in weka.core.pmml.jaxbbindings: Java class for DataDictionary element declaration.
DataDictionary() - Constructor for class weka.core.pmml.jaxbbindings.DataDictionary
dataDL(double, double, double, double, double) - Static method in class weka.classifiers.rules.RuleStats: The description length of data given the parameters of the data based on the ruleset.
DataField - Class in weka.core.pmml.jaxbbindings: Java class for DataField element declaration.
DataField() - Constructor for class weka.core.pmml.jaxbbindings.DataField
DataField(String, OPTYPE) - Constructor for class weka.core.pmml.jaxbbindings.DataField
DataFormatListener - Interface in weka.gui.beans: Listener interface that customizer classes that are interested in data format changes can implement.
dataFromStep(Data) - Method in interface weka.knowledgeflow.StepOutputListener: Process data produced by a knowledge flow step
DataGenerator - Class in weka.datagenerators: Abstract superclass for data generators that generate data for classifiers and clusterers.
DataGenerator() - Constructor for class weka.datagenerators.DataGenerator: initializes with default settings.
DataGenerator - Interface in weka.gui.boundaryvisualizer: Interface to something that can generate new instances based on a set of input instances
DataGenerator - Class in weka.knowledgeflow.steps: Step that wraps a Weka DataGenerator.
DataGenerator() - Constructor for class weka.knowledgeflow.steps.DataGenerator
DataGeneratorPanel - Class in weka.gui.explorer: A panel for generating artificial data via DataGenerators.
DataGeneratorPanel() - Constructor for class weka.gui.explorer.DataGeneratorPanel: creates the panel
DataGrid - Class in weka.knowledgeflow.steps: A step that allows the user to define instances to output
DataGrid() - Constructor for class weka.knowledgeflow.steps.DataGrid
DataGridStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the data grid
DataGridStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.DataGridStepEditorDialog
dataset() - Method in class weka.core.AbstractInstance: Returns the dataset this instance has access to.
dataset() - Method in interface weka.core.Instance: Returns the dataset this instance has access to.
DATASET_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the key field containing the dataset name
DATASET_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer: The name of the key field containing the dataset name.
DATASET_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer: The name of the key field containing the dataset name
DataSetEvent - Class in weka.gui.beans: Event encapsulating a data set
DataSetEvent(Object, Instances) - Constructor for class weka.gui.beans.DataSetEvent
DatasetListPanel - Class in weka.gui.experiment: This panel controls setting a list of datasets for an experiment to iterate over.
DatasetListPanel(Experiment) - Constructor for class weka.gui.experiment.DatasetListPanel: Creates the dataset list panel with the given experiment.
DatasetListPanel() - Constructor for class weka.gui.experiment.DatasetListPanel: Create the dataset list panel initially disabled.
DataSink(String) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data to the given file.
DataSink(Saver) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data to the given Saver (expected to be fully configured).
DataSink(OutputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSink: initializes the sink to save the data in the stream (always in ARFF format).
DataSink - Interface in weka.gui.beans: Indicator interface to something that can store instances to some destination
DataSource(String) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Tries to load the data from the file.
DataSource(Instances) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given dataset.
DataSource(Loader) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given Loader.
DataSource(InputStream) - Constructor for class weka.core.converters.ConverterUtils.DataSource: Initializes the datasource with the given input stream.
DataSource - Interface in weka.gui.beans: Interface to something that is capable of being a source for data - either batch or incremental data
DataSourceListener - Interface in weka.gui.beans: Interface to something that can accept DataSetEvents
DATATYPE - Enum in weka.core.pmml.jaxbbindings: Java class for DATATYPE.
DATATYPE_LAYOUT - Static variable in class weka.gui.beans.xml.XMLBeans: the data that is about to be read/written contains a complete layout
DATATYPE_USERCOMPONENTS - Static variable in class weka.gui.beans.xml.XMLBeans: the data that is about to be read/written contains user-components, i.e., Metabeans
DataVisualizer - Class in weka.gui.beans: Bean that encapsulates weka.gui.visualize.VisualizePanel
DataVisualizer() - Constructor for class weka.gui.beans.DataVisualizer
DataVisualizer - Class in weka.knowledgeflow.steps: A step that provides a visualization based on weka.gui.visualize.VisualizePanel
DataVisualizer() - Constructor for class weka.knowledgeflow.steps.DataVisualizer
DataVisualizerBeanInfo - Class in weka.gui.beans: Bean info class for the data visualizer
DataVisualizerBeanInfo() - Constructor for class weka.gui.beans.DataVisualizerBeanInfo
DataVisualizerCustomizer - Class in weka.gui.beans: GUI customizer for data visualizer.
DataVisualizerCustomizer() - Constructor for class weka.gui.beans.DataVisualizerCustomizer: Constructor
DataVisualizerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the DataVisualizer step
DataVisualizerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView
DataVisualizerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the DataVisualizer step
DataVisualizerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.DataVisualizerStepEditorDialog
DATE - Static variable in class weka.core.Attribute: Constant set for attributes with date values.
DATE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for DATE used for reading experiment results.
DateAttributeInfo - Class in weka.core: Stores information for date attributes.
DateAttributeInfo(String) - Constructor for class weka.core.DateAttributeInfo: Constructs info based on argument.
dateAttributesTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
DATEFORMAT - Static variable in class weka.core.json.JSONInstances: the dateformat attribute.
dateFormatTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.NumericToDate
dateFormatTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
dateReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
dateToMillis(String, String) - Static method in class weka.core.Utils: Turns a given date string into Java's internal representation (milliseconds from 1 January 1970).
DateToNumeric - Class in weka.filters.unsupervised.attribute: A filter for turning date attributes into numeric ones.
DateToNumeric() - Constructor for class weka.filters.unsupervised.attribute.DateToNumeric
DbConnectionDialog(String, String) - Method in class weka.gui.DatabaseConnectionDialog: Display the database connection dialog
DbConnectionDialog(String, String, boolean) - Method in class weka.gui.DatabaseConnectionDialog: Display the database connection dialog
DBO() - Constructor for class weka.core.Debug.DBO
DbUtils - Class in weka.gui.sql: A little bit extended DatabaseUtils class.
DbUtils() - Constructor for class weka.gui.sql.DbUtils: initializes the object.
dchisq(double) - Static method in class weka.core.matrix.Maths: Returns the density of the Chi-squared distribution.
dchisq(double, double) - Static method in class weka.core.matrix.Maths: Returns the density of the noncentral Chi-squared distribution.
dchisq(double, DoubleVector) - Static method in class weka.core.matrix.Maths: Returns the density of the noncentral Chi-squared distribution.
dchisqLog(double) - Static method in class weka.core.matrix.Maths: Returns the log-density of the noncentral Chi-square distribution.
dchisqLog(double, double) - Static method in class weka.core.matrix.Maths: Returns the log-density value of a noncentral Chi-square distribution.
dchisqLog(double, DoubleVector) - Static method in class weka.core.matrix.Maths: Returns the log-density of a set of noncentral Chi-squared distributions.
DDConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a discrete domain.
DDConditionalEstimator() - Constructor for class weka.estimators.DDConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
DDConditionalEstimator(int, int, boolean) - Constructor for class weka.estimators.DDConditionalEstimator: Constructor
Debug - Class in weka.core: A helper class for debug output, logging, clocking, etc.
Debug() - Constructor for class weka.core.Debug: default constructor, prints only to stdout
Debug(String) - Constructor for class weka.core.Debug: logs the output to the specified file (and stdout).
Debug(String, int, int) - Constructor for class weka.core.Debug: logs the output
DEBUG - Static variable in class weka.gui.LogWindow: whether we're debugging - enables output on stdout
Debug.Clock - Class in weka.core: A little helper class for clocking and outputting times.
Debug.DBO - Class in weka.core: contains debug methods
Debug.Log - Class in weka.core: A helper class for logging stuff.
Debug.Random - Class in weka.core: This extended Random class enables one to print the generated random numbers etc., before they are returned.
Debug.SimpleLog - Class in weka.core: A little, simple helper class for logging stuff.
Debug.Timestamp - Class in weka.core: A class that can be used for timestamps in files, The toString() method simply returns the associated Date object in a timestamp format.
debuggingOutputTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
debugTipText() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
debugTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.AbstractClusterer: Returns the tip text for this property
debugTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
debugTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
debugTipText() - Method in class weka.core.stopwords.AbstractStopwords: Returns the tip text for this property
debugTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
debugTipText() - Method in class weka.estimators.Estimator: Returns the tip text for this property
debugTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
debugTipText() - Method in class weka.filters.Filter: Returns the tip text for this property
debugTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the tip text for this property
decayTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
decimalsTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
Decision - Class in weka.core.pmml.jaxbbindings: Java class for Decision element declaration.
Decision() - Constructor for class weka.core.pmml.jaxbbindings.Decision
Decisions - Class in weka.core.pmml.jaxbbindings: Java class for Decisions element declaration.
Decisions() - Constructor for class weka.core.pmml.jaxbbindings.Decisions
DecisionStump - Class in weka.classifiers.trees: Class for building and using a decision stump.
DecisionStump() - Constructor for class weka.classifiers.trees.DecisionStump
DecisionTable - Class in weka.classifiers.rules: Class for building and using a simple decision table majority classifier.

For more information see:

Ron Kohavi: The Power of Decision Tables.
DecisionTable() - Constructor for class weka.classifiers.rules.DecisionTable: Constructor for a DecisionTable
DecisionTableHashKey - Class in weka.classifiers.rules: Class providing hash table keys for DecisionTable
DecisionTableHashKey(Instance, int, boolean) - Constructor for class weka.classifiers.rules.DecisionTableHashKey: Constructor for a hashKey
DecisionTableHashKey(double[]) - Constructor for class weka.classifiers.rules.DecisionTableHashKey: Constructor for a hashKey
DecisionTree - Class in weka.core.pmml.jaxbbindings: Java class for DecisionTree element declaration.
DecisionTree() - Constructor for class weka.core.pmml.jaxbbindings.DecisionTree
decompose() - Method in class weka.classifiers.BVDecompose: Carry out the bias-variance decomposition
decompose() - Method in class weka.classifiers.BVDecomposeSegCVSub: Carry out the bias-variance decomposition using the sub-sampled cross-validation method.
decreaseFontSize() - Method in class weka.gui.beans.Note: Decrease the font size by one
decreaseFontSize() - Method in class weka.gui.knowledgeflow.NoteVisual: Decrease the font size by one
decreaseFrequency(int) - Method in class weka.associations.Item: Decrease the frequency of this item.
decreaseFrequency() - Method in class weka.associations.Item: Decrement the frequency of this item.
DEFAULT_COLORS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel: default colours for classes
DEFAULT_COLORS - Static variable in class weka.knowledgeflow.steps.BoundaryPlotter: default colours for classes
DEFAULT_COMMENT - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for comments.
DEFAULT_EXPRESSION - Static variable in class weka.filters.unsupervised.attribute.RemoveByName: the default expression.
DEFAULT_FILE - Static variable in class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
DEFAULT_FILE - Static variable in class weka.knowledgeflow.steps.TextSaver.TextSaverDefaults
DEFAULT_FILE_KEY - Static variable in class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
DEFAULT_FILE_KEY - Static variable in class weka.knowledgeflow.steps.TextSaver.TextSaverDefaults
DEFAULT_FONT_FAMILY - Static variable in class weka.gui.scripting.SyntaxDocument: the font family.
DEFAULT_FONT_SIZE - Static variable in class weka.gui.scripting.SyntaxDocument: the font size.
DEFAULT_FORMAT - Static variable in class weka.core.Debug.Timestamp: the default format
DEFAULT_FORMAT - Static variable in class weka.gui.SimpleDateFormatEditor: the default format
DEFAULT_FORMAT - Static variable in class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
DEFAULT_FORMAT_KEY - Static variable in class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
DEFAULT_HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for height
DEFAULT_KEYWORD - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for keywords.
DEFAULT_LEFT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for left
DEFAULT_NORMAL - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for normal code.
DEFAULT_PACKAGE - Static variable in class weka.core.ClassCache: the key for the default package.
DEFAULT_SEPARATORS - Static variable in class weka.core.TestInstances: the default word separators used in strings
DEFAULT_SHAPE_SIZE - Static variable in class weka.gui.visualize.Plot2D
DEFAULT_STORE_LOCATION - Static variable in class weka.core.metastore.XMLFileBasedMetaStore: The default location for the XML files
DEFAULT_STRING - Static variable in class weka.gui.scripting.SyntaxDocument: the attribute set for strings.
DEFAULT_SUFFIX - Static variable in class weka.experiment.ExplicitTestsetResultProducer: the default suffix.
DEFAULT_T1 - Static variable in class weka.clusterers.Canopy
DEFAULT_T2 - Static variable in class weka.clusterers.Canopy
DEFAULT_TOP - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for top
DEFAULT_WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: the default for width
DEFAULT_WORDS - Static variable in class weka.core.TestInstances: the default list of words used in strings
DefaultAssociationRule - Class in weka.associations: Class for storing and manipulating an association rule.
DefaultAssociationRule(Collection<Item>, Collection<Item>, DefaultAssociationRule.METRIC_TYPE, int, int, int, int) - Constructor for class weka.associations.DefaultAssociationRule: Construct a new default association rule.
DefaultAssociationRule.METRIC_TYPE - Enum in weka.associations: Enum for holding different metric types
DefaultCallbackNotifierDelegate - Class in weka.knowledgeflow: Default implementation of a CallbackNotifierDelegate.
DefaultCallbackNotifierDelegate() - Constructor for class weka.knowledgeflow.DefaultCallbackNotifierDelegate
defaultOutput() - Method in class weka.datagenerators.DataGenerator: Gets writer, which is used for outputting to stdout.
DefaultPackage - Class in weka.core.packageManagement: A concrete implementation of Package that uses Java properties files/classes to manage package meta data.
DefaultPackage(File, PackageManager, Map<?, ?>) - Constructor for class weka.core.packageManagement.DefaultPackage: Constructs an new DefaultPackage.
DefaultPackage(File, PackageManager) - Constructor for class weka.core.packageManagement.DefaultPackage: Constructs a new DefaultPackage.
DefaultPackageManager - Class in weka.core.packageManagement: A concrete implementation of PackageManager that uses Java properties files/class to manage package meta data.
DefaultPackageManager() - Constructor for class weka.core.packageManagement.DefaultPackageManager: Constructor
Defaults - Class in weka.core: Base class for providing a set of default settings for an application.
Defaults(String) - Constructor for class weka.core.Defaults: Construct a new empty Defaults
Defaults(String, Map<Settings.SettingKey, Object>) - Constructor for class weka.core.Defaults: Construct a new Defaults
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.LED24: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.classification.RDG1: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.Expression: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Initializes the format for the dataset produced.
defineDataFormat() - Method in class weka.datagenerators.DataGenerator: Constructs the Instances object representing the format of the generated data.
DefineFunction - Class in weka.core.pmml: Class encapsulating DefineFunction (used in TransformationDictionary).
DefineFunction(Element, TransformationDictionary) - Constructor for class weka.core.pmml.DefineFunction
DefineFunction - Class in weka.core.pmml.jaxbbindings: Java class for DefineFunction element declaration.
DefineFunction() - Constructor for class weka.core.pmml.jaxbbindings.DefineFunction
del(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Deletes given instance from given bag.
DelayedCallbackNotifierDelegate - Class in weka.knowledgeflow: Implementation of a CallbackNotifierDelegate that stores the ExecutionResult and only notifies the callback when the notifyNow() method is called.
DelayedCallbackNotifierDelegate() - Constructor for class weka.knowledgeflow.DelayedCallbackNotifierDelegate
delete(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Deletes an element from the set.
delete() - Method in class weka.core.Instances: Removes all instances from the set.
delete(int) - Method in class weka.core.Instances: Removes an instance at the given position from the set.
deleteArc(String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete arc between two nodes.
deleteArc(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete arc between two nodes.
deleteAttribute() - Method in class weka.gui.arffviewer.ArffPanel: deletes the currently selected attribute
deleteAttribute(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: deletes the current selected Attribute or several chosen ones
deleteAttributeAt(int) - Method in class weka.core.AbstractInstance: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in interface weka.core.Instance: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.core.Instances: Deletes an attribute at the given position (0 to numAttributes() - 1).
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the attribute at the given col index
deleteAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attribute at the given col index.
deleteAttributeAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attribute at the given col index
deleteAttributes() - Method in class weka.gui.arffviewer.ArffPanel: deletes the chosen attributes
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the attributes at the given indices
deleteAttributes(int[]) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the attributes at the given indices
deleteAttributeType(int) - Method in class weka.core.Instances: Deletes all attributes of the given type in the dataset.
deleteDir(File, PrintStream...) - Static method in class weka.core.packageManagement.DefaultPackageManager
deleteEmptyBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
deleteFlagString(List<String>, String) - Static method in class weka.core.Option: Removes an option from a given list of strings that specifies options.
deleteInstance() - Method in class weka.gui.arffviewer.ArffPanel: deletes the currently selected instance
deleteInstance(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: deletes the current selected Instance or several chosen ones
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the instance at the given index
deleteInstanceAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instance at the given index
deleteInstanceAt(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instance at the given index
deleteInstances() - Method in class weka.gui.arffviewer.ArffPanel: deletes all the currently selected instances
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffSortedTableModel: deletes the instances at the given positions
deleteInstances(int[]) - Method in class weka.gui.arffviewer.ArffTableModel: deletes the instances at the given positions
deleteItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.ItemSet: Deletes all item sets that don't have minimum support.
deleteItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.LabeledItemSet: Deletes all item sets that don't have minimum support and have more than maximum support
deleteLastParent(Instances) - Method in class weka.classifiers.bayes.net.ParentSet: Delete last added parent from parent set and update internals (specifically the cardinality of the parent set)
deleteNode(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteNode(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteOption(List<Option>, String) - Static method in class weka.core.Option: Removes an option from a given list of options.
deleteOptionString(List<String>, String) - Static method in class weka.core.Option: Removes an option from a given list of strings that specifies options.
deleteParent(int, Instances) - Method in class weka.classifiers.bayes.net.ParentSet: delete node from parent set
deleteSelection(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete nodes with indexes in selection from the network, updating instances, parentsets, distributions Conditional distributions are condensed by taking the values for the target node to be its first value.
deleteStringAttributes() - Method in class weka.core.Instances: Deletes all string attributes in the dataset.
deleteWithMissing(int) - Method in class weka.core.Instances: Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissing(Attribute) - Method in class weka.core.Instances: Removes all instances with missing values for a particular attribute from the dataset.
deleteWithMissingClass() - Method in class weka.core.Instances: Removes all instances with a missing class value from the dataset.
Delimiter - Class in weka.core.pmml.jaxbbindings: Java class for Delimiter element declaration.
Delimiter() - Constructor for class weka.core.pmml.jaxbbindings.Delimiter
DELIMITER2 - Enum in weka.core.pmml.jaxbbindings: Java class for DELIMITER.
delimitersTipText() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Returns the tip text for this property
delNodeValue(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Delete node value from a node.
delRange(int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Deletes all instances in given range from given bag.
deltaTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
deltaTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
deltaTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
deltaTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
DenseInstance - Class in weka.core: Class for handling an instance.
DenseInstance(Instance) - Constructor for class weka.core.DenseInstance: Constructor that copies the attribute values and the weight from the given instance.
DenseInstance(double, double[]) - Constructor for class weka.core.DenseInstance: Constructor that inititalizes instance variable with given values.
DenseInstance(int) - Constructor for class weka.core.DenseInstance: Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
DensityBasedClusterer - Interface in weka.clusterers: Interface for clusterers that can estimate the density for a given instance.
DensityBasedClustererSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a density based clusterer.
DensityBasedClustererSplitEvaluator() - Constructor for class weka.experiment.DensityBasedClustererSplitEvaluator
densityBasedClustererTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns a description of this option suitable for display as a tip text in the gui.
dependencies() - Method in class weka.core.Capabilities: Returns an Iterator over the stored dependencies
Dependency - Class in weka.core.packageManagement: Class that encapsulates a dependency between two packages
Dependency(Package, PackageConstraint) - Constructor for class weka.core.packageManagement.Dependency: Construct a new Dependency from a supplied source package and PackageConstraint containing the target package.
depth() - Method in class weka.gui.HierarchyPropertyParser: Get the depth of the tree, i.e.
DerivedField - Class in weka.core.pmml.jaxbbindings: Java class for DerivedField element declaration.
DerivedField() - Constructor for class weka.core.pmml.jaxbbindings.DerivedField
DerivedField(String, DATATYPE, OPTYPE) - Constructor for class weka.core.pmml.jaxbbindings.DerivedField
DerivedFieldMetaInfo - Class in weka.core.pmml
DerivedFieldMetaInfo(Element, ArrayList<Attribute>, TransformationDictionary) - Constructor for class weka.core.pmml.DerivedFieldMetaInfo
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
descendantPopulationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
description() - Method in class weka.core.Option: Returns the option's description.
DESCRIPTION - Static variable in class weka.knowledgeflow.BaseExecutionEnvironment: Description of the default execution environment
deserialize(InputStream) - Static method in class weka.core.scripting.Jython: deserializes the Python Object from the stream
deSerialize(String) - Static method in class weka.core.xml.XStream: Deserializes an object from the supplied XML string
DesignPanel - Class in weka.gui.knowledgeflow: Panel that contains the tree view of steps and the search field.
DesignPanel(StepTree) - Constructor for class weka.gui.knowledgeflow.DesignPanel: Constructor
desiredWeightOfInstancesPerIntervalTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
dest - Variable in class weka.gui.graphvisualizer.GraphEdge: The index of target node in Nodes vector
destLbl - Variable in class weka.gui.graphvisualizer.GraphEdge: Label of target node
det() - Method in class weka.core.matrix.LUDecomposition: Determinant
det() - Method in class weka.core.matrix.Matrix: Matrix determinant
detectionPerAttributeTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
determineBounds() - Method in class weka.gui.visualize.Plot2D: Determine the min and max values for axis and colouring attributes
determineClasses() - Static method in class weka.gui.GenericObjectEditor
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.AveragingResultProducer: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.CSVResultListener: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.DatabaseResultListener: Determines if there are any constraints (imposed by the destination) on any additional measures produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer: Determines if there are any constraints (imposed by the destination) on the result columns to be produced by resultProducers.
determineColumnConstraints(ResultProducer) - Method in interface weka.experiment.ResultListener: Determines if there are any constraints (imposed by the destination) on additional result columns to be produced by resultProducers.
determineValues(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: determines the values to retain, it is always at least 1 and up to the maximum number of distinct values
DIAMOND_SHAPE - Static variable in class weka.gui.visualize.Plot2D
DictionaryBuilder - Class in weka.core: Class for building and maintaining a dictionary of terms.
DictionaryBuilder() - Constructor for class weka.core.DictionaryBuilder
dictionaryFileToSaveToTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Tip text for this property
DictionarySaver - Class in weka.core.converters: Writes a dictionary constructed from string attributes in incoming instances to a destination.
DictionarySaver() - Constructor for class weka.core.converters.DictionarySaver
differencesProbability - Variable in class weka.experiment.PairedStats: The probability of obtaining the observed differences
differencesSignificance - Variable in class weka.experiment.PairedStats: A significance indicator: 0 if the differences are not significant > 0 if x significantly greater than y < 0 if x significantly less than y
differencesStats - Variable in class weka.experiment.PairedStats: The stats associated with the paired differences
DIRECTED - Static variable in interface weka.gui.graphvisualizer.GraphConstants: Types of Edges
directionTipText() - Method in class weka.attributeSelection.BestFirst: Returns the tip text for this property
DirectoryFilter() - Constructor for class weka.core.ClassCache.DirectoryFilter
disable(Capabilities.Capability) - Method in class weka.core.Capabilities: disables the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: disables the given capability.
DISABLE_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for package disablement
disableAll() - Method in class weka.core.Capabilities: disables all attribute and class types (including dependencies)
disableAllAttributeDependencies() - Method in class weka.core.Capabilities: disables all attribute type dependencies
disableAllAttributes() - Method in class weka.core.Capabilities: disables all attribute types
disableAllClassDependencies() - Method in class weka.core.Capabilities: disables all class type dependencies
disableAllClasses() - Method in class weka.core.Capabilities: disables all class types
disableAllPerspectiveTabs() - Method in class weka.gui.PerspectiveManager: Disable the tab/button for each visible perspective
DISABLED_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for package disablement
disableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: disables the dependency of the given capability Disabling NOMINAL_ATTRIBUTES also disables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
disableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: disables the given "not to have" capability.
disableWidgets(String...) - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar
disconnect(NeuralConnection, NeuralConnection) - Static method in class weka.classifiers.functions.neural.NeuralConnection: Disconnects two units.
DISCONNECT - Static variable in class weka.gui.sql.event.ConnectionEvent: it was a disconnect
disconnectFromDatabase() - Method in class weka.experiment.DatabaseUtils: Closes the connection to the database.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractDataSink: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractEvaluator: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event named
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTestSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Appender: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Associator: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.BeanCommon: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassAssigner: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Classifier: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ClassValuePicker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Clusterer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in interface weka.gui.beans.ConnectionNotificationConsumer: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name This method should be implemented synchronized.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.CostBenefitAnalysis: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.CrossValidationFoldMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.DataVisualizer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Filter: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.FlowByExpression
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ImageSaver
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ImageViewer
disconnectionNotification(String, Object) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Join: Handles cleanup when an upstream step disconnects
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Loader: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.MetaBean: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.ModelPerformanceChart: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.PredictionAppender: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SerializedModelSaver: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.Sorter: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.StripChart: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SubstringLabeler: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.SubstringReplacer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TextSaver
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TextViewer: Notify this object that it has been deregistered as a listener with a source for named event.
disconnectionNotification(String, Object) - Method in class weka.gui.beans.TrainTestSplitMaker: Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name
disconnectStep(Step) - Method in class weka.knowledgeflow.StepManagerImpl: Remove the supplied step from connections (both incoming and outgoing of all types) for the step managed by this manager.
disconnectStepWithConnection(Step, String) - Method in class weka.knowledgeflow.StepManagerImpl: Disconnect the supplied step under the associated connection type from both the incoming and outgoing connections for the step managed by this manager.
DiscreteEstimator - Class in weka.estimators: Simple symbolic probability estimator based on symbol counts.
DiscreteEstimator() - Constructor for class weka.estimators.DiscreteEstimator: No-arg constructor needed to make WEKA's forName() work.
DiscreteEstimator(int, boolean) - Constructor for class weka.estimators.DiscreteEstimator: Constructor
DiscreteEstimator(int, double) - Constructor for class weka.estimators.DiscreteEstimator: Constructor
DiscreteEstimatorBayes - Class in weka.classifiers.bayes.net.estimate: Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorBayes(int, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Constructor
DiscreteEstimatorFullBayes - Class in weka.classifiers.bayes.net.estimate: Symbolic probability estimator based on symbol counts and a prior.
DiscreteEstimatorFullBayes(int, double, double, DiscreteEstimatorBayes, DiscreteEstimatorBayes, double) - Constructor for class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes: Constructor
Discretize - Class in weka.core.pmml: Class encapsulating a Discretize Expression.
Discretize(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Discretize: Constructs a Discretize Expression
Discretize - Class in weka.core.pmml.jaxbbindings: Java class for Discretize element declaration.
Discretize() - Constructor for class weka.core.pmml.jaxbbindings.Discretize
Discretize - Class in weka.filters.supervised.attribute: An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.supervised.attribute.Discretize: Constructor - initialises the filter
Discretize - Class in weka.filters.unsupervised.attribute: An instance filter that discretizes a range of numeric attributes in the dataset into nominal attributes.
Discretize() - Constructor for class weka.filters.unsupervised.attribute.Discretize: Constructor - initialises the filter
Discretize(String) - Constructor for class weka.filters.unsupervised.attribute.Discretize: Another constructor, sets the attribute indices immediately
DiscretizeBin - Class in weka.core.pmml.jaxbbindings: Java class for DiscretizeBin element declaration.
DiscretizeBin() - Constructor for class weka.core.pmml.jaxbbindings.DiscretizeBin
DiscrStats - Class in weka.core.pmml.jaxbbindings: Java class for DiscrStats element declaration.
DiscrStats() - Constructor for class weka.core.pmml.jaxbbindings.DiscrStats
displayModelInOldFormatTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
displayModelInOldFormatTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
displayResultset(int) - Method in class weka.experiment.PairedTTester: Checks whether the resultset with the given index shall be displayed.
displayResultset(int) - Method in interface weka.experiment.Tester: Checks whether the resultset with the given index shall be displayed.
displayRulesTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
displayStdDevsTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
dispose() - Method in class weka.gui.GUIChooserApp.ChildFrameSDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameMDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.Main.ChildFrameSDI: de-registers the child frame with the parent first.
dispose() - Method in class weka.gui.PropertyDialog: We need to extend the dispose method so that the member variables are set to null and the corresponding objects can be garbage collected.
dispose() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
disposeSingleton() - Static method in class weka.gui.beans.KnowledgeFlowApp
disposeSplash() - Static method in class weka.gui.SplashWindow: Closes the splash window.
disposeWindow(JFrame, WindowAdapter) - Method in class weka.gui.GUIChooserApp: Disposes the given JFrame and removes it from the list of frames maintained by the GUIChooserApp.
distance(Instance, Instance) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in interface weka.core.DistanceFunction: Calculates the distance between two instances.
distance(Instance, Instance) - Method in class weka.core.EuclideanDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.EuclideanDistance: Calculates the distance (or similarity) between two instances.
distance(Instance, Instance) - Method in class weka.core.FilteredDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.FilteredDistance: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in class weka.core.FilteredDistance: Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.FilteredDistance: Calculates the distance between two instances.
distance(Instance, Instance) - Method in class weka.core.MinkowskiDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.MinkowskiDistance: Calculates the distance (or similarity) between two instances.
distance(Instance, Instance) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, PerformanceStats) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, double) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
distance(Instance, Instance, double, PerformanceStats) - Method in class weka.core.NormalizableDistance: Calculates the distance between two instances.
DistanceFunction - Interface in weka.core: Interface for any class that can compute and return distances between two instances.
distanceFunctionTipText() - Method in class weka.clusterers.HierarchicalClusterer
distanceFunctionTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
distanceFunctionTipText() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the tip text for this property.
distanceIsBranchLengthTipText() - Method in class weka.clusterers.HierarchicalClusterer
distanceTipText() - Method in class weka.core.FilteredDistance: Returns the tip text for this property
distanceWeightingTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
distinctCount - Variable in class weka.core.AttributeStats: The number of distinct values
distMultTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
distributedExperimentSelected() - Method in class weka.gui.experiment.DistributeExperimentPanel: Returns true if the distribute experiment checkbox is selected
DistributeExperimentPanel - Class in weka.gui.experiment: This panel enables an experiment to be distributed to multiple hosts; it also allows remote host names to be specified.
DistributeExperimentPanel() - Constructor for class weka.gui.experiment.DistributeExperimentPanel: Constructor
DistributeExperimentPanel(Experiment) - Constructor for class weka.gui.experiment.DistributeExperimentPanel: Creates the panel with the supplied initial experiment.
distribution() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the predicted probabilities
distribution() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns the distribution of class values induced by the model.
Distribution - Class in weka.classifiers.trees.j48: Class for handling a distribution of class values.
Distribution(int, int) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates and initializes a new distribution.
Distribution(double[][]) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates and initializes a new distribution using the given array.
Distribution(Instances) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates a distribution with only one bag according to instances in source.
Distribution(Instances, ClassifierSplitModel) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates a distribution according to given instances and split model.
Distribution(Distribution) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates distribution with only one bag by merging all bags of given distribution.
Distribution(Distribution, int) - Constructor for class weka.classifiers.trees.j48.Distribution: Creates distribution with two bags by merging all bags apart of the indicated one.
distributionForInstance(Instance) - Method in class weka.classifiers.AbstractClassifier: Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.BayesNet: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayes: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in interface weka.classifiers.Classifier: Predicts the class memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.Logistic: Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.MultilayerPerceptron: Call this function to predict the class of an instance once a classification model has been built with the buildClassifier call.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SGD: Computes the distribution for a given instance
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SGDText
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SimpleLogistic: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.SMO: Estimates class probabilities for given instance.
distributionForInstance(Instance) - Method in class weka.classifiers.functions.VotedPerceptron: Outputs the distribution for the given output.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.IBk: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.KStar: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.lazy.LWL: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AdaBoostM1: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Classifies a given instance after attribute selection
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Bagging: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.CVParameterSelection: Predicts the class distribution for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.FilteredClassifier: Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.LogitBoost: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Returns the distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.MultiScheme: Returns class probabilities.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomCommittee: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.RandomSubSpace: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Stacking: Returns estimated class probabilities for the given instance if the class is nominal and a one-element array containing the numeric prediction if the class is numeric.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.Vote: Classifies a given instance using the selected combination rule.
distributionForInstance(Instance) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.misc.InputMappedClassifier
distributionForInstance(Instance) - Method in class weka.classifiers.misc.SerializedClassifier: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.GeneralRegression: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.NeuralNetwork: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.Regression: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.RuleSetModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.pmml.consumer.TreeModel: Classifies the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.DecisionTable: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.JRip: Classify the test instance with the rule learner and provide the class distributions
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.PART: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.part.MakeDecList: Returns the class distribution for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.rules.ZeroR: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.DecisionStump: Calculates the class membership probabilities for the given test instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.HoeffdingTree: Returns class probabilities for an instance.
distributionForInstance(Instance, boolean) - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns class probabilities for a weighted instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.J48: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.LMT: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the class probabilities for an instance given by the logistic model tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns class probabilities for an instance.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.RandomTree: Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.classifiers.trees.REPTree: Computes class distribution of an instance using the tree.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractClusterer: Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.clusterers.Canopy
distributionForInstance(Instance) - Method in interface weka.clusterers.Clusterer: Predicts the cluster memberships for a given instance.
distributionForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer: Returns the cluster probability distribution for an instance.
distributionForInstance(Instance) - Method in class weka.clusterers.FilteredClusterer: Classifies a given instance after filtering.
distributionForInstance(Instance) - Method in class weka.clusterers.HierarchicalClusterer
distributionsByOriginalIndex(double[]) - Method in class weka.filters.supervised.attribute.ClassOrder: Convert the given class distribution back to the distributions with the original internal class index
distributionsForInstances(Instances) - Method in class weka.classifiers.AbstractClassifier: Batch prediction method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.Bagging: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns predictions for a whole set of instances.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.LogitBoost: Calculates the class membership probabilities for the given test instances.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.RandomCommittee: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.RandomSubSpace: Batch scoring method.
distributionsForInstances(Instances) - Method in class weka.classifiers.meta.Stacking: Returns class probabilities for all given instances if the class is nominal or corresponding predicted numeric values if the class is numeric.
distributionsForInstances(Instances) - Method in interface weka.core.BatchPredictor: Batch scoring method
distributionSpreadTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
distributionTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
divergence(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: calculates the divergence between the probability distribution represented by this network and that of another, that is, \sum_{x\in X} P(x)log P(x)/Q(x) where X is the set of values the nodes in the network can take, P(x) the probability of this network for configuration x Q(x) the probability of the other network for configuration x
divide(Instances, boolean) - Static method in class weka.associations.LabeledItemSet: Splits the class attribute away.
dividedBy(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Divided by another DoubleVector element by element
dividedByEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Divided by another DoubleVector element by element in place
division(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '/' division operator
DIVISION - Static variable in interface weka.core.expressionlanguage.parser.sym
DKConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DKConditionalEstimator() - Constructor for class weka.estimators.DKConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
DKConditionalEstimator(int, double) - Constructor for class weka.estimators.DKConditionalEstimator: Constructor
dl(int) - Method in class weka.core.Debug.DBO: Return true if the debug level is set same method as outpuTypeSet but better name
DNConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a discrete domain conditional upon a numeric domain.
DNConditionalEstimator() - Constructor for class weka.estimators.DNConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
DNConditionalEstimator(int, double) - Constructor for class weka.estimators.DNConditionalEstimator: Constructor
dnorm(double) - Static method in class weka.core.matrix.Maths: Returns the density of the standard normal.
dnorm(double, double, double) - Static method in class weka.core.matrix.Maths: Returns the density value of a standard normal.
dnorm(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths: Returns the density values of a set of normal distributions with different means.
dnormLog(double) - Static method in class weka.core.matrix.Maths: Returns the log-density of the standard normal.
dnormLog(double, double, double) - Static method in class weka.core.matrix.Maths: Returns the log-density value of a standard normal.
dnormLog(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths: Returns the log-density values of a set of normal distributions with different means.
do_action(int, lr_parser, Stack, int) - Method in class weka.core.expressionlanguage.parser.Parser: Invoke a user supplied parse action.
do_action(int, lr_parser, Stack, int) - Method in class weka.core.json.Parser: Invoke a user supplied parse action.
DO_NOT_LOAD_IF_CLASS_NOT_PRESENT_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if a class is not available
DO_NOT_LOAD_IF_CLASS_NOT_PRESENT_MESSAGE_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if a class is not available
DO_NOT_LOAD_IF_ENV_VAR_NOT_SET_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if an environment variable is not set
DO_NOT_LOAD_IF_ENV_VAR_NOT_SET_MESSAGE_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if an environment variable is not set
DO_NOT_LOAD_IF_FILE_NOT_PRESENT_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if a file is not present
DO_NOT_LOAD_IF_FILE_NOT_PRESENT_MESSAGE_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for preventing load if a file is not present
doCommandlineCompletion(KeyEvent) - Method in class weka.gui.SimpleCLIPanel: performs commandline completion on packages and classnames.
DOCTYPE - Static variable in class weka.core.xml.XMLInstances: the DTD
DOCTYPE - Static variable in class weka.core.xml.XMLOptions: the DTD for the XML file.
DOCTYPE - Static variable in class weka.core.xml.XMLSerialization: the DOCTYPE for the serialization
DocumentPrinting - Class in weka.gui: DocumentPrinting is a class that lets you print documents on the fly for free ;) Printing in JDK 1.2 - 1.5 is hard.
DocumentPrinting() - Constructor for class weka.gui.DocumentPrinting: Initializes the printing.
DocumentTermMatrix - Class in weka.core.pmml.jaxbbindings: Java class for DocumentTermMatrix element declaration.
DocumentTermMatrix() - Constructor for class weka.core.pmml.jaxbbindings.DocumentTermMatrix
doHistory(KeyEvent) - Method in class weka.gui.SimpleCLIPanel: Changes the currently displayed command line when certain keys are pressed.
doLayout() - Method in class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
doLayout() - Method in class weka.gui.EnvironmentField.WideComboBox
doLayout() - Method in class weka.gui.knowledgeflow.LayoutPanel
doMetaConnection(BeanInstance, BeanInstance, EventSetDescriptor, JComponent, int) - Static method in class weka.gui.beans.BeanConnection
done() - Method in class weka.classifiers.functions.MultilayerPerceptron: Signal end of iterating, useful for any house-keeping/cleanup
done() - Method in interface weka.classifiers.IterativeClassifier: Signal end of iterating, for either the time being or permanently if setFinalized(true) has been called.
done() - Method in class weka.classifiers.meta.AdaBoostM1: Clean up after boosting.
done() - Method in class weka.classifiers.meta.AdditiveRegression: Clean up.
done() - Method in class weka.classifiers.meta.FilteredClassifier: Signal end of iterating, useful for any house-keeping/cleanup (If the base classifier supports this.)
done() - Method in class weka.classifiers.meta.LogitBoost: Clean up after boosting.
done() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Signal that a scoring run has been completed.
doNotCheckCapabilities() - Method in class weka.core.Capabilities: Does owner implement CapabilitiesIgnorer and does it not want capability checking to be performed?
doNotCheckCapabilitiesTipText() - Method in class weka.associations.AbstractAssociator: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.attributeSelection.ASEvaluation: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.clusterers.AbstractClusterer: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.core.converters.AbstractSaver: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.estimators.Estimator: Returns the tip text for this property
doNotCheckCapabilitiesTipText() - Method in class weka.filters.Filter: Returns the tip text for this property
doNotCheckForModifiedClassAttributeTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
doNotMakeSplitPointActualValueTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
doNotOperateOnPerClassBasisTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
doNotOperateOnPerClassBasisTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
doNotPrintModelsTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
doNotStandardizeAttributesTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
dontFilterAfterFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property.
dontNormalizeTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
dontNormalizeTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
dontReplaceMissingTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
dontReplaceMissingValuesTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
dontShowOKCancelButtons() - Method in interface weka.gui.beans.GOECustomizer: Tells the customizer not to display its own OK and CANCEL buttons
dontShowOKCancelButtons() - Method in class weka.gui.filters.AddUserFieldsCustomizer: Tell this customizer not to show its own OK and Cancel buttons.
doRun(int) - Method in class weka.experiment.AveragingResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.DatabaseResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.LearningRateResultProducer: Gets the results for a specified run number.
doRun(int) - Method in class weka.experiment.RandomSplitResultProducer: Gets the results for a specified run number.
doRun(int) - Method in interface weka.experiment.ResultProducer: Gets the results for a specified run number.
doRunKeys(int) - Method in class weka.experiment.AveragingResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.DatabaseResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.LearningRateResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in class weka.experiment.RandomSplitResultProducer: Gets the keys for a specified run number.
doRunKeys(int) - Method in interface weka.experiment.ResultProducer: Gets the keys for a specified run number.
doTests() - Method in class weka.associations.CheckAssociator: Begin the tests, reporting results to System.out
doTests() - Method in class weka.attributeSelection.CheckAttributeSelection: Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.CheckClassifier: Begin the tests, reporting results to System.out
doTests() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Begin the tests, reporting results to System.out
doTests() - Method in class weka.clusterers.CheckClusterer: Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.Check: Begin the tests, reporting results to System.out
doTests() - Method in class weka.core.CheckGOE: Runs some diagnostic tests on the object.
doTests() - Method in class weka.core.CheckOptionHandler: Runs some diagnostic tests on an optionhandler object.
doTests() - Method in class weka.core.CheckScheme: Begin the tests, reporting results to System.out
doTests() - Method in class weka.estimators.CheckEstimator: Begin the tests, reporting results to System.out
dotMultiply(AlgVector) - Method in class weka.core.AlgVector: Returns the inner (or dot) product of two vectors
DotParser - Class in weka.gui.graphvisualizer: This class parses input in DOT format, and builds the datastructures that are passed to it.
DotParser(Reader, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Constructor for class weka.gui.graphvisualizer.DotParser: Dot parser Constructor
dotProduct(VectorInstance) - Method in class weka.core.pmml.VectorInstance: Computes the dot product between this vector instance and the argument
dotProduct(double[]) - Method in class weka.core.pmml.VectorInstance: Computes the dot product between this vector instance and the supplied array of values
DOUBLE - Static variable in interface weka.core.json.sym
DOUBLE - Static variable in class weka.experiment.DatabaseUtils: Type mapping for DOUBLE used for reading experiment results.
DOUBLE - Static variable in interface weka.gui.graphvisualizer.GraphConstants: Types of Edges
DoubleConstant(double) - Constructor for class weka.core.expressionlanguage.common.Primitives.DoubleConstant
doubleToString(double, int) - Static method in class weka.core.Utils: Rounds a double and converts it into String.
doubleToString(double, int, int) - Static method in class weka.core.Utils: Rounds a double and converts it into a formatted decimal-justified String.
DoubleVariable(String) - Constructor for class weka.core.expressionlanguage.common.Primitives.DoubleVariable
DoubleVector - Class in weka.core.matrix: A vector specialized on doubles.
DoubleVector() - Constructor for class weka.core.matrix.DoubleVector: Constructs a null vector.
DoubleVector(int) - Constructor for class weka.core.matrix.DoubleVector: Constructs an n-vector of zeros.
DoubleVector(int, double) - Constructor for class weka.core.matrix.DoubleVector: Constructs a constant n-vector.
DoubleVector(double[]) - Constructor for class weka.core.matrix.DoubleVector: Constructs a vector directly from a double array
dp(String) - Method in class weka.core.Debug.DBO: prints out text if verbose is on.
dp(int, String) - Method in class weka.core.Debug.DBO: prints out text but only if debug level is set.
dpln(String) - Method in class weka.core.Debug.DBO: prints out text + endofline if verbose is on.
dpln(int, String) - Method in class weka.core.Debug.DBO: prints out text + endofline but only if parameter debug type is set.
draw(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
draw3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an outlined rectangle with 3D effect in current pen color.
Drawable - Interface in weka.core: Interface to something that can be drawn as a graph.
drawArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawBytes(byte[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: simply calls drawString(String,int,int)
drawChars(char[], int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: simply calls drawString(String,int,int)
drawGlyphVector(GlyphVector, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawHighlight(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the node highlighted.
drawImage(Image, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,Color,ImageObserver)
drawImage(Image, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(Image, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: PS see http://astronomy.swin.edu.au/~pbourke/geomformats/postscript/ Java http ://show.docjava.com:8086/book/cgij/doc/ip/graphics/SimpleImageFrame.java .html
drawImage(Image, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,Color,ImageObserver) with the color WHITE as background
drawImage(Image, int, int, int, int, int, int, int, int, Color, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawImage(Image, int, int, int, int, int, int, int, int, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics: calls drawImage(Image,int,int,int,int,int,int,int,int,Color,ImageObserver) with Color.WHITE as background color
drawImage(BufferedImage, BufferedImageOp, int, int) - Method in class weka.gui.visualize.PostscriptGraphics
drawImage(Image, AffineTransform, ImageObserver) - Method in class weka.gui.visualize.PostscriptGraphics
drawInputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the nodes input connections.
drawLine(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a line in current pen color.
drawNode(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the node.
drawOutputLines(Graphics, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to draw the nodes output connections.
drawOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an Oval outline in current pen color.
drawPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawPolyline(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw an outlined rectangle in current pen color.
drawRenderableImage(RenderableImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRenderedImage(RenderedImage, AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
drawRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawSortedDenseSample(int, int, Random) - Static method in class weka.core.RandomSample: Draws a sorted list of n distinct integers from 0, 1, ..., N - 1 based on the simple Algorithm A in
drawSortedSample(int, int, Random) - Static method in class weka.core.RandomSample: Returns a sorted list of n distinct integers that are randomly chosen from 0, 1, ..., N - 1.
drawSortedSparseSample(int, int, Random) - Static method in class weka.core.RandomSample: Draws a sorted list of n distinct integers from 0, 1, ..., N - 1 based on drawSparseSample() followed by radix sort.
drawSparseSample(int, int, Random) - Static method in class weka.core.RandomSample: Draws n distinct integers from 0, 1, ..., N - 1, randomly ordered, using a partial Fisher-Yates shuffle and a hash map.
drawString(AttributedCharacterIterator, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
drawString(String, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw text in current pen color.
drawString(AttributedCharacterIterator, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
drawString(String, float, float) - Method in class weka.gui.visualize.PostscriptGraphics
DTD - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the DTD.
DTD_ANY - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the ANY placeholder.
DTD_ANY - Static variable in class weka.core.xml.XMLDocument: the ANY placeholder.
DTD_AT_LEAST_ONE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the at least one marker.
DTD_AT_LEAST_ONE - Static variable in class weka.core.xml.XMLDocument: the at least one marker.
DTD_ATTLIST - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the AttList definition.
DTD_ATTLIST - Static variable in class weka.core.xml.XMLDocument: the AttList definition.
DTD_CDATA - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the CDATA placeholder.
DTD_CDATA - Static variable in class weka.core.xml.XMLDocument: the CDATA placeholder.
DTD_DOCTYPE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the DocType definition.
DTD_DOCTYPE - Static variable in class weka.core.xml.XMLDocument: the DocType definition.
DTD_ELEMENT - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the Element definition.
DTD_ELEMENT - Static variable in class weka.core.xml.XMLDocument: the Element definition.
DTD_IMPLIED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #IMPLIED placeholder.
DTD_IMPLIED - Static variable in class weka.core.xml.XMLDocument: the #IMPLIED placeholder.
DTD_OPTIONAL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the optional marker.
DTD_OPTIONAL - Static variable in class weka.core.xml.XMLDocument: the optional marker.
DTD_PCDATA - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #PCDATA placeholder.
DTD_PCDATA - Static variable in class weka.core.xml.XMLDocument: the #PCDATA placeholder.
DTD_REQUIRED - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the #REQUIRED placeholder.
DTD_REQUIRED - Static variable in class weka.core.xml.XMLDocument: the #REQUIRED placeholder.
DTD_SEPARATOR - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the option separator.
DTD_SEPARATOR - Static variable in class weka.core.xml.XMLDocument: the option separator.
DTD_ZERO_OR_MORE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the zero or more marker.
DTD_ZERO_OR_MORE - Static variable in class weka.core.xml.XMLDocument: the zero or more marker.
Dummy - Class in weka.knowledgeflow.steps: A "dummy" no-op step
Dummy() - Constructor for class weka.knowledgeflow.steps.Dummy
dumpDistribution() - Method in class weka.classifiers.trees.j48.Distribution: Prints distribution.
dumpLabel(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints label for subset index of instances (eg class).
dumpModel(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints the split model.

E

EAST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
Echo - Class in weka.gui.simplecli: Outputs a message.
Echo() - Constructor for class weka.gui.simplecli.Echo
Edge - Class in weka.gui.treevisualizer: This class is used in conjunction with the Node class to form a tree structure.
Edge(String, String, String) - Constructor for class weka.gui.treevisualizer.Edge: This constructs an Edge with the specified label and parent , child serial tags.
edges - Variable in class weka.gui.graphvisualizer.GraphNode: The indices of nodes to which there are edges from this node, plus the type of edge
edit() - Method in class weka.gui.explorer.PreprocessPanel: edits the current instances object in the viewer
EditableBayesNet - Class in weka.classifiers.bayes.net: Bayes Network learning using various search algorithms and quality measures.
Base class for a Bayes Network classifier.
EditableBayesNet() - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: standard constructor *
EditableBayesNet(Instances) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor, creates empty network with nodes based on the attributes in a data set
EditableBayesNet(BIFReader) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor, copies Bayesian network structure from a Bayesian network encapsulated in a BIFReader
EditableBayesNet(boolean) - Constructor for class weka.classifiers.bayes.net.EditableBayesNet: constructor that potentially initializes instances as well
editableProperties() - Method in class weka.gui.PropertySheetPanel: Gets the number of editable properties for the current target.
eig() - Method in class weka.core.matrix.Matrix: Eigenvalue Decomposition
EigenvalueDecomposition - Class in weka.core.matrix: Eigenvalues and eigenvectors of a real matrix.
eigenvalueDecomposition(double[][], double[]) - Method in class weka.core.Matrix: Deprecated.

Performs Eigenvalue Decomposition using Householder QR Factorization Matrix must be symmetrical.
EigenvalueDecomposition(Matrix) - Constructor for class weka.core.matrix.EigenvalueDecomposition: Check for symmetry, then construct the eigenvalue decomposition
element(int) - Method in class weka.core.neighboursearch.covertrees.Stack: Returns the ith element in the stack.
elementAt(int) - Method in class weka.core.FastVector: Deprecated.

Returns the element at the given position.
elementAt(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the component at the specified index.
elements() - Method in class weka.core.FastVector: Deprecated.

Returns an enumeration of this vector.
elements(int) - Method in class weka.core.FastVector: Deprecated.

Returns an enumeration of this vector, skipping the element with the given index.
elements - Variable in class weka.core.neighboursearch.covertrees.Stack: The elements inside the stack.
elements() - Method in class weka.core.Stopwords: Returns a sorted enumeration over all stored stopwords
eliminateColinearAttributesTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
EM - Class in weka.clusterers: Simple EM (expectation maximisation) class.

EM assigns a probability distribution to each instance which indicates the probability of it belonging to each of the clusters.
EM() - Constructor for class weka.clusterers.EM: Constructor.
empty() - Method in class weka.core.Queue: Checks if queue is empty.
empty() - Method in class weka.gui.scripting.Script: Empties the document.
enable(Capabilities.Capability) - Method in class weka.core.Capabilities: enables the given capability.
enable(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: enables the given capability.
ENABLE_UNDO - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
ENABLE_UNDO_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
enableAll() - Method in class weka.core.Capabilities: enables all attribute and class types (including dependencies)
enableAllAttributeDependencies() - Method in class weka.core.Capabilities: enables all attribute type dependencies
enableAllAttributes() - Method in class weka.core.Capabilities: enables all attribute types
enableAllClassDependencies() - Method in class weka.core.Capabilities: enables all class type dependencies
enableAllClasses() - Method in class weka.core.Capabilities: enables all class types
enableAllPerspectiveTabs() - Method in class weka.gui.PerspectiveManager: Enable the tab/button for each visible perspective
enableDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: enables the dependency flag for the given capability Enabling NOMINAL_ATTRIBUTES also enables BINARY_ATTRIBUTES, UNARY_ATTRIBUTES and EMPTY_NOMINAL_ATTRIBUTES.
enableNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: enables the given "not to have" capability.
enableWidget(String, boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar: Enable/disable a named widget
enableWidgets(String...) - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar
enclosureCharactersTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
entriesDeleted(List<String>, List<Integer>) - Method in interface weka.gui.ResultHistoryPanel.RDeleteListener
entropicAutoBlendTipText() - Method in class weka.classifiers.lazy.KStar: Returns the tip text for this property
ENTROPY - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
entropy(double[]) - Static method in class weka.core.ContingencyTables: Computes the entropy of the given array.
EntropyBasedSplitCrit - Class in weka.classifiers.trees.j48: "Abstract" class for computing splitting criteria based on the entropy of a class distribution.
EntropyBasedSplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropyBasedSplitCrit
entropyConditionedOnColumns(double[][]) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the rows given the columns.
entropyConditionedOnRows(double[][]) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the columns given the rows.
entropyConditionedOnRows(double[][], double[][], double) - Static method in class weka.core.ContingencyTables: Computes conditional entropy of the columns given the rows of the test matrix with respect to the train matrix.
entropyGain() - Method in class weka.classifiers.trees.lmt.ResidualSplit: Computes entropy gain for current split.
entropyOverColumns(double[][]) - Static method in class weka.core.ContingencyTables: Computes the columns' entropy for the given contingency table.
entropyOverRows(double[][]) - Static method in class weka.core.ContingencyTables: Computes the rows' entropy for the given contingency table.
EntropySplitCrit - Class in weka.classifiers.trees.j48: Class for computing the entropy for a given distribution.
EntropySplitCrit() - Constructor for class weka.classifiers.trees.j48.EntropySplitCrit
entryDeleted(String, int) - Method in interface weka.gui.ResultHistoryPanel.RDeleteListener: Called when an entry in the list is deleted
ENUM_HELPER - Static variable in class weka.knowledgeflow.JSONFlowUtils
enumerateAttributes() - Method in class weka.core.AbstractInstance: Returns an enumeration of all the attributes.
enumerateAttributes() - Method in interface weka.core.Instance: Returns an enumeration of all the attributes.
enumerateAttributes() - Method in class weka.core.Instances: Returns an enumeration of all the attributes.
enumerateColNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
enumerateInstances() - Method in class weka.core.Instances: Returns an enumeration of all instances in the dataset.
enumerateMeasures() - Method in class weka.classifiers.bayes.BayesNet: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.functions.SimpleLogistic: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.functions.SMOreg: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.classifiers.lazy.IBk: Returns an enumeration of the additional measure names produced by the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
enumerateMeasures() - Method in class weka.classifiers.lazy.LWL: Returns an enumeration of the additional measure names produced by the neighbour search algorithm.
enumerateMeasures() - Method in class weka.classifiers.meta.AdditiveRegression: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.meta.Bagging: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.DecisionTable: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.JRip: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.rules.PART: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.J48: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.LMT: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.m5.M5Base: Returns an enumeration of the additional measure names
enumerateMeasures() - Method in class weka.classifiers.trees.REPTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in interface weka.core.AdditionalMeasureProducer: Returns an enumeration of the measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.BallTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.CoverTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.KDTree: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.PerformanceStats: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns an enumeration of the additional measure names.
enumerateMeasures() - Method in class weka.experiment.AveragingResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures() - Method in class weka.experiment.CrossValidationResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.DatabaseResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateMeasures() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator.
enumerateMeasures() - Method in class weka.experiment.LearningRateResultProducer: Returns an enumeration of any additional measure names that might be in the result producer
enumerateMeasures() - Method in class weka.experiment.RandomSplitResultProducer: Returns an enumeration of any additional measure names that might be in the SplitEvaluator
enumerateMeasures() - Method in class weka.experiment.RegressionSplitEvaluator: Returns an enumeration of any additional measure names that might be in the classifier
enumerateRequests() - Method in class weka.gui.beans.Associator: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.AttributeSummarizer: Return an enumeration of actions that the user can ask this bean to perform
enumerateRequests() - Method in class weka.gui.beans.Classifier: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.Clusterer: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Return an enumeration of user activated requests for this bean
enumerateRequests() - Method in class weka.gui.beans.CostBenefitAnalysis
enumerateRequests() - Method in class weka.gui.beans.CrossValidationFoldMaker: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.DataVisualizer: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.Filter: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.GraphViewer: Return an enumeration of user requests
enumerateRequests() - Method in class weka.gui.beans.ImageViewer
enumerateRequests() - Method in class weka.gui.beans.MetaBean: Return an enumeration of requests that can be made by the user
enumerateRequests() - Method in class weka.gui.beans.ModelPerformanceChart: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.StripChart: Describe enumerateRequests method here.
enumerateRequests() - Method in class weka.gui.beans.TextViewer: Get a list of user requests
enumerateRequests() - Method in class weka.gui.beans.TrainTestSplitMaker: Get list of user requests
enumerateRequests() - Method in interface weka.gui.beans.UserRequestAcceptor: Get a list of performable requests
enumerateRowNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
enumerateValues() - Method in class weka.core.Attribute: Returns an enumeration of all the attribute's values if the attribute is nominal, string, or relation-valued, null otherwise.
EnumHelper - Class in weka.core: Helper/wrapper class for obtaining an arbitrary enum value from an arbitrary enum type.
EnumHelper(Enum) - Constructor for class weka.core.EnumHelper: Constructor
EnumHelper() - Constructor for class weka.core.EnumHelper: No-op constructor (for beans conformity)
enumToVector(Enumeration<Option>) - Method in class weka.datagenerators.DataGenerator: Convenience method.
Environment - Class in weka.core: This class encapsulates a map of all environment and java system properties.
Environment() - Constructor for class weka.core.Environment: Constructs a new Environment object with all environment variables and java properties set.
Environment(Environment) - Constructor for class weka.core.Environment: Constructor that makes a new Environment object containing all the entries in the supplied one
EnvironmentField - Class in weka.gui.beans: Deprecated.
EnvironmentField() - Constructor for class weka.gui.beans.EnvironmentField: Deprecated.

Construct an EnvironmentField with no label.
EnvironmentField(Environment) - Constructor for class weka.gui.beans.EnvironmentField: Deprecated.

Construct an EnvironmentField with no label.
EnvironmentField(String, Environment) - Constructor for class weka.gui.beans.EnvironmentField: Deprecated.

Constructor.
EnvironmentField(String) - Constructor for class weka.gui.beans.EnvironmentField: Deprecated.

Constructor.
EnvironmentField - Class in weka.gui: Widget that displays a label and a combo box for selecting environment variables.
EnvironmentField() - Constructor for class weka.gui.EnvironmentField: Construct an EnvironmentField with no label.
EnvironmentField(Environment) - Constructor for class weka.gui.EnvironmentField: Construct an EnvironmentField with no label.
EnvironmentField(String, Environment) - Constructor for class weka.gui.EnvironmentField: Constructor.
EnvironmentField(String) - Constructor for class weka.gui.EnvironmentField: Constructor.
EnvironmentField.WideComboBox - Class in weka.gui.beans: Deprecated.

Combo box that allows the drop-down list to be wider than the component itself.
EnvironmentField.WideComboBox - Class in weka.gui: Combo box that allows the drop-down list to be wider than the component itself.
EnvironmentHandler - Interface in weka.core: Interface for something that can utilize environment variables.
EnvironmentProperties - Class in weka.core: Extends Properties to allow the value of a system property (if set) to override that which has been loaded/set.
EnvironmentProperties() - Constructor for class weka.core.EnvironmentProperties
EnvironmentProperties(Properties) - Constructor for class weka.core.EnvironmentProperties
environmentSubstitute(String) - Method in class weka.gui.knowledgeflow.StepEditorDialog: Substitute the values of any environment variables present in the supplied string
environmentSubstitute(String) - Method in class weka.gui.knowledgeflow.VisibleLayout
environmentSubstitute(String) - Method in interface weka.knowledgeflow.StepManager: Substitute all known environment variables in the given string
environmentSubstitute(String) - Method in class weka.knowledgeflow.StepManagerImpl: Substitute the values of environment variables in the given string
environmentSubstitute(String) - Method in class weka.knowledgeflow.steps.BaseStep: Substitute the values of environment variables in the given string
EOF - Static variable in interface weka.core.expressionlanguage.parser.sym
EOF - Static variable in interface weka.core.json.sym
EOF_sym() - Method in class weka.core.expressionlanguage.parser.Parser: EOF Symbol index.
EOF_sym() - Method in class weka.core.json.Parser: EOF Symbol index.
EPANECHNIKOV - Static variable in class weka.classifiers.lazy.LWL
epochsTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
epochsTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
EPSILON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
EPSILON_INSENSITIVE - Static variable in class weka.classifiers.functions.SGD: The epsilon insensitive loss function
epsilonParameterTipText() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
epsilonTipText() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns the tip text for this property
eq(double, double) - Static method in class weka.core.Utils: Tests if a is equal to b.
equal(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '=' equal operator
EQUAL - Static variable in interface weka.core.expressionlanguage.parser.sym
equalCondset(Object) - Method in class weka.associations.LabeledItemSet: Compares two item sets
equalHeaders(Instance) - Method in class weka.core.AbstractInstance: Tests if the headers of two instances are equivalent.
equalHeaders(Instance) - Method in interface weka.core.Instance: Tests if the headers of two instances are equivalent.
equalHeaders(Instances) - Method in class weka.core.Instances: Checks if two headers are equivalent.
equalHeadersMsg(Instance) - Method in class weka.core.AbstractInstance: Checks if the headers of two instances are equivalent.
equalHeadersMsg(Instance) - Method in interface weka.core.Instance: Checks if the headers of two instances are equivalent.
equalHeadersMsg(Instances) - Method in class weka.core.Instances: Checks if two headers are equivalent.
equals(Object) - Method in class weka.associations.AssociationRule: Return true if this rule is equal to the supplied one.
equals(Object) - Method in class weka.associations.AssociatorEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.associations.BinaryItem: Equals.
equals(Object) - Method in class weka.associations.Item: Equals.
equals(Object) - Method in class weka.associations.ItemSet: Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.LabeledItemSet: Tests if two item sets are equal.
equals(Object) - Method in class weka.associations.NominalItem: Equals.
equals(Object) - Method in class weka.associations.NumericItem: Equals.
equals(Object) - Method in class weka.classifiers.Evaluation: Tests whether the current evaluation object is equal to another evaluation object.
equals(Object) - Method in class weka.classifiers.evaluation.Evaluation: Tests whether the current evaluation object is equal to another evaluation object.
equals(Object) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.classifiers.rules.DecisionTableHashKey: Tests if two instances are equal
equals(Object) - Method in class weka.clusterers.ClusterEvaluation: Tests whether the current evaluation object is equal to another evaluation object
equals(Object) - Method in class weka.core.Attribute: Tests if given attribute is equal to this attribute.
equals(Object) - Method in class weka.core.AttributeLocator: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class weka.core.ClassDiscovery.StringCompare: Indicates whether some other object is "equal to" this Comparator.
equals(Package) - Method in class weka.core.packageManagement.Package: Compare the supplied package to this package.
equals(Object) - Method in class weka.core.SelectedTag: Returns true if this SelectedTag equals another object
equals(Object) - Method in class weka.core.SerializedObject
equals(Object) - Method in class weka.core.Settings.SettingKey: Compares two setting keys for equality
equals(Object) - Method in class weka.core.Trie: Compares the specified object with this collection for equality.
equals(Object) - Method in class weka.core.Trie.TrieNode: Indicates whether some other object is "equal to" this one.
equals(Object) - Method in class weka.core.Version: whether the given version string is equal to this version
equals(Object) - Method in class weka.estimators.Estimator: Tests whether the current estimation object is equal to another estimation object
equals(Object) - Method in class weka.gui.graphvisualizer.GraphEdge
equals(Object) - Method in class weka.gui.graphvisualizer.GraphNode: Returns true if passed in argument is an instance of GraphNode and is equal to this node.
equals(Object) - Method in class weka.gui.simplecli.AbstractCommand: Returns true if the object is a command with the same name.
equals(Object) - Method in class weka.gui.SortedTableModel.SortContainer: Indicates whether some other object is "equal to" this one.
equalsMsg(Object) - Method in class weka.core.Attribute: Tests if given attribute is equal to this attribute.
equalTo(Test) - Method in class weka.datagenerators.Test: Compares the test with the test that is given as parameter.
errms(StreamTokenizer, String) - Static method in class weka.core.converters.ConverterUtils: Throws error message with line number and last token read.
errms(StreamTokenizer, String) - Static method in class weka.core.converters.StreamTokenizerUtils: Throws error message with line number and last token read.
error() - Method in class weka.classifiers.evaluation.NumericPrediction: Calculates the prediction error.
error - Static variable in interface weka.core.expressionlanguage.parser.sym
error - Static variable in interface weka.core.json.sym
ERROR_SHAPE - Static variable in class weka.gui.visualize.Plot2D
error_sym() - Method in class weka.core.expressionlanguage.parser.Parser: error Symbol index.
error_sym() - Method in class weka.core.json.Parser: error Symbol index.
ErrorBasedMeritEvaluator - Interface in weka.attributeSelection: Interface for evaluators that calculate the "merit" of attributes/subsets as the error of a learning scheme
errorFunction(double) - Static method in class weka.core.Statistics: Returns the error function of the normal distribution.
errorFunctionComplemented(double) - Static method in class weka.core.Statistics: Returns the complementary Error function of the normal distribution.
errorOnProbabilitiesTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
errorOnProbabilitiesTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
errorPlotPointSizeProportionalToMarginTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
errorRate() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Returns the estimated error rate.
errorRate() - Method in class weka.classifiers.Evaluation: Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorRate() - Method in class weka.classifiers.evaluation.Evaluation: Returns the estimated error rate or the root mean squared error (if the class is numeric).
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit: This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod: This function calculates what the error value should be.
errorValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to get the error value of this unit.
errorValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit: This function calculates what the error value should be.
ErrorVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier errors in the explorer.
escapeQuote(String) - Method in class weka.gui.scripting.SyntaxDocument: Escapes the quote delimiter.
establishCacheIfNeeded(PrintStream...) - Static method in class weka.core.WekaPackageManager: Establish the local copy of the package meta data if needed
establishProxy() - Method in class weka.core.packageManagement.PackageManager: Tries to configure a Proxy object for use in an Authenticator if there is a proxy defined by the properties http.proxyHost and http.proxyPort, and if the user has set values for the properties (note, these are not standard java properties) http.proxyUser and http.proxyPassword.
estimate(double[][], double[]) - Method in interface weka.estimators.MultivariateEstimator: Fits the value to the density estimator.
estimate(double[][], double[]) - Method in class weka.estimators.MultivariateGaussianEstimator: Generates the estimator based on the given observations and weight vector.
estimateCPTs() - Method in class weka.classifiers.bayes.BayesNet: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimateCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: estimateCPTs estimates the conditional probability tables for the Bayes Net using the network structure.
estimatePooled(double[][][], double[][]) - Method in class weka.estimators.MultivariateGaussianEstimator: Generates pooled estimator for linear discriminant analysis based on the given groups of observations and weight vectors.
Estimator - Class in weka.estimators: Abstract class for all estimators.
Estimator() - Constructor for class weka.estimators.Estimator
estimatorTipText() - Method in class weka.classifiers.bayes.BayesNet: This will return a string describing the BayesNetEstimator.
estimatorTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
EstimatorUtils - Class in weka.estimators: Contains static utility functions for Estimators.
EstimatorUtils() - Constructor for class weka.estimators.EstimatorUtils
EstTypes() - Constructor for class weka.estimators.CheckEstimator.EstTypes: Constructor
EstTypes(boolean, boolean, boolean) - Constructor for class weka.estimators.CheckEstimator.EstTypes: Constructor
ETable - Class in weka.gui: A better-looking table than JTable.
ETable() - Constructor for class weka.gui.ETable
Euclidean - Class in weka.core.pmml.jaxbbindings: Java class for euclidean element declaration.
Euclidean() - Constructor for class weka.core.pmml.jaxbbindings.Euclidean
EuclideanDistance - Class in weka.core: Implementing Euclidean distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.
EuclideanDistance() - Constructor for class weka.core.EuclideanDistance: Constructs an Euclidean Distance object, Instances must be still set.
EuclideanDistance(Instances) - Constructor for class weka.core.EuclideanDistance: Constructs an Euclidean Distance object and automatically initializes the ranges.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.CachedKernel: Implements the abstract function of Kernel using the cache.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.Kernel: Computes the result of the kernel function for two instances.
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
eval(int, int, Instance) - Method in class weka.classifiers.functions.supportVector.StringKernel: Computes the result of the kernel function for two instances.
EVAL_ACCURACY - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_ACCURACY - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_ACCURACY - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_AUC - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_AUC - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_AUC - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_AUPRC - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_AUPRC - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_CORRELATION - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_CORRELATION - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_DEFAULT - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_DEFAULT - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_DEFAULT - Static variable in class weka.classifiers.rules.DecisionTable: default is accuracy for discrete class and RMSE for numeric class
EVAL_FMEASURE - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_FMEASURE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_MAE - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_MAE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_MAE - Static variable in class weka.classifiers.rules.DecisionTable
EVAL_PLUGIN - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_PLUGIN - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_RMSE - Static variable in class weka.attributeSelection.ClassifierSubsetEval
EVAL_RMSE - Static variable in class weka.attributeSelection.WrapperSubsetEval
EVAL_RMSE - Static variable in class weka.classifiers.rules.DecisionTable
evalBoolean(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the boolean result of the XPath expression.
evalDouble(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the double result of the XPath expression.
evalString(String) - Method in class weka.core.xml.XMLDocument: Evaluates and returns the boolean result of the XPath expression.
evaluate(String, String[]) - Static method in class weka.associations.AssociatorEvaluation: Evaluates an associator with the options given in an array of strings.
evaluate(Associator, String[]) - Static method in class weka.associations.AssociatorEvaluation: Evaluates the associator with the given commandline options and returns the evaluation string.
evaluate(Associator, Instances) - Method in class weka.associations.AssociatorEvaluation: Evaluates the associator with the given commandline options and returns the evaluation string.
evaluate(Kernel, String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates the Kernel with the given commandline options and returns the evaluation string.
evaluate(String, String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates a kernel with the options given in an array of strings.
evaluate(Kernel, Instances) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: Evaluates the Kernel with the given commandline options and returns the evaluation string.
evaluate(Node...) - Method in class weka.core.expressionlanguage.common.IfElseMacro: Evaluates the ifelse macro
evaluate(Node...) - Method in class weka.core.expressionlanguage.common.JavaMacro: Evaluates the java macro on the given arguments
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.BooleanConstant
evaluate() - Method in interface weka.core.expressionlanguage.common.Primitives.BooleanExpression
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.BooleanVariable
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.DoubleConstant
evaluate() - Method in interface weka.core.expressionlanguage.common.Primitives.DoubleExpression
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.DoubleVariable
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.StringConstant
evaluate() - Method in interface weka.core.expressionlanguage.common.Primitives.StringExpression
evaluate() - Method in class weka.core.expressionlanguage.common.Primitives.StringVariable
evaluate(Node...) - Method in interface weka.core.expressionlanguage.core.Macro: Applies a macro to a set of parameter nodes.
evaluate(Node...) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Evaluates the 'ismissing' macro
evaluate(Instance, boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
evaluate(Instance, boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
evaluate(Instance, boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Evaluate this node and combine with the result so far
evaluateAttribute(int) - Method in interface weka.attributeSelection.AttributeEvaluator: evaluates an individual attribute
evaluateAttribute(int) - Method in class weka.attributeSelection.AttributeSetEvaluator: evaluates an individual attribute
evaluateAttribute(int[], int[]) - Method in class weka.attributeSelection.AttributeSetEvaluator: Evaluates a set of attributes
evaluateAttribute(int) - Method in class weka.attributeSelection.ClassifierAttributeEval: Evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.CorrelationAttributeEval: Evaluates an individual attribute by measuring the correlation (Pearson's) between it and the class.
evaluateAttribute(int) - Method in class weka.attributeSelection.GainRatioAttributeEval: evaluates an individual attribute by measuring the gain ratio of the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.InfoGainAttributeEval: evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.OneRAttributeEval: evaluates an individual attribute by measuring the amount of information gained about the class given the attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.PrincipalComponents: Evaluates the merit of a transformed attribute.
evaluateAttribute(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Evaluates an individual attribute using ReliefF's instance based approach.
evaluateAttribute(int) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: evaluates an individual attribute by measuring the symmetrical uncertainty between it and the class.
evaluateClusterer(Instances) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Instances, String) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Instances, String, boolean) - Method in class weka.clusterers.ClusterEvaluation: Evaluate the clusterer on a set of instances.
evaluateClusterer(Clusterer, String[]) - Static method in class weka.clusterers.ClusterEvaluation: Evaluates a clusterer with the options given in an array of strings.
evaluateModel(String, String[]) - Static method in class weka.classifiers.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a given set of instances.
evaluateModel(String, String[]) - Static method in class weka.classifiers.evaluation.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, String[]) - Static method in class weka.classifiers.evaluation.Evaluation: Evaluates a classifier with the options given in an array of strings.
evaluateModel(Classifier, Instances, Object...) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a given set of instances.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied prediction on a single instance.
evaluateModelOnce(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a single instance.
evaluateModelOnce(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnce(double, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied prediction on a single instance.
evaluateModelOnceAndRecordPrediction(Classifier, Instance) - Method in class weka.classifiers.Evaluation: Evaluates the classifier on a single instance and records the prediction.
evaluateModelOnceAndRecordPrediction(double[], Instance) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateModelOnceAndRecordPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the classifier on a single instance and records the prediction.
evaluateModelOnceAndRecordPrediction(double[], Instance) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.GiniSplitMetric
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.InfoGainSplitMetric
evaluateSplit(Map<String, WeightMass>, List<Map<String, WeightMass>>) - Method in class weka.classifiers.trees.ht.SplitMetric: Evaluate the merit of a split
evaluateSubset(BitSet) - Method in class weka.attributeSelection.CfsSubsetEval: evaluates a subset of attributes
evaluateSubset(BitSet) - Method in class weka.attributeSelection.ClassifierSubsetEval: Evaluates a subset of attributes
evaluateSubset(BitSet, Instances) - Method in class weka.attributeSelection.ClassifierSubsetEval: Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instance, boolean) - Method in class weka.attributeSelection.ClassifierSubsetEval: Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet, Instances) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator: Evaluates a subset of attributes with respect to a set of instances.
evaluateSubset(BitSet, Instance, boolean) - Method in class weka.attributeSelection.HoldOutSubsetEvaluator: Evaluates a subset of attributes with respect to a single instance.
evaluateSubset(BitSet) - Method in interface weka.attributeSelection.SubsetEvaluator: evaluates a subset of attributes
evaluateSubset(BitSet) - Method in class weka.attributeSelection.WrapperSubsetEval: Evaluates a subset of attributes
Evaluation - Class in weka.classifiers: Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.Evaluation
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.Evaluation
Evaluation - Class in weka.classifiers.evaluation: Class for evaluating machine learning models.
Evaluation(Instances) - Constructor for class weka.classifiers.evaluation.Evaluation: Initializes all the counters for the evaluation.
Evaluation(Instances, CostMatrix) - Constructor for class weka.classifiers.evaluation.Evaluation: Initializes all the counters for the evaluation and also takes a cost matrix as parameter.
evaluationForSingleInstance(double[], Instance, boolean) - Method in class weka.classifiers.evaluation.Evaluation: Evaluates the supplied distribution on a single instance.
evaluationForSingleInstance(double[], Instance, boolean) - Method in class weka.classifiers.Evaluation: Evaluates the supplied distribution on a single instance.
evaluationMeasureTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
evaluationMeasureTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
evaluationMeasureTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
evaluationMeasureTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
EvaluationMetricHelper - Class in weka.classifiers.evaluation: Helper routines for extracting metric values from built-in and plugin evaluation metrics.
EvaluationMetricHelper(Evaluation) - Constructor for class weka.classifiers.evaluation.EvaluationMetricHelper: Construct a new EvaluationMetricHelper
EvaluationMetricSelectionDialog - Class in weka.gui: A GUI dialog for selecting classification/regression evaluation metrics to be output.
EvaluationMetricSelectionDialog(Dialog, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
EvaluationMetricSelectionDialog(Window, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
EvaluationMetricSelectionDialog(Frame, List<String>) - Constructor for class weka.gui.EvaluationMetricSelectionDialog: Constructor
evaluationMetricsToOutputTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
evaluationMetricTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
EvaluationUtils - Class in weka.classifiers.evaluation: Contains utility functions for generating lists of predictions in various manners.
EvaluationUtils() - Constructor for class weka.classifiers.evaluation.EvaluationUtils
evaluatorTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the tip text for this property
evaluatorTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns the tip text for this property
evalUsingTrainingDataTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
EventConstraints - Interface in weka.gui.beans: Interface for objects that want to be able to specify at any given time whether their current configuration allows a particular event to be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Appender: Returns true if, at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Associator: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Associator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassAssigner: Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Classifier: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Classifier: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClassValuePicker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.Clusterer: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Clusterer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.CrossValidationFoldMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.DataVisualizer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in interface weka.gui.beans.EventConstraints: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Filter: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.FlowByExpression
eventGeneratable(String) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Join
eventGeneratable(String) - Method in class weka.gui.beans.Loader: Returns true if the named event can be generated at this time
eventGeneratable(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Returns true, if at the current time, the event described by the supplied event descriptor could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.MetaBean: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.ModelPerformanceChart: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.PredictionAppender: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.Sorter: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.SubstringLabeler: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.SubstringReplacer: Returns true if, at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TestSetMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TextViewer: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainingSetMaker: Returns true, if at the current time, the named event could be generated.
eventGeneratable(String) - Method in class weka.gui.beans.TrainTestSplitMaker: Returns true, if at the current time, the named event could be generated.
EventValues - Class in weka.core.pmml.jaxbbindings: Java class for EventValues element declaration.
EventValues() - Constructor for class weka.core.pmml.jaxbbindings.EventValues
execute() - Method in class weka.classifiers.CheckSource: performs the comparison test
execute(String) - Method in class weka.experiment.DatabaseUtils: Executes a SQL query.
execute() - Method in class weka.experiment.RemoteExperimentSubTask: Run the experiment
execute() - Method in interface weka.experiment.Task: Execute this task.
execute() - Method in class weka.filters.CheckSource: performs the comparison test
execute() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Perform the sub task
execute() - Method in class weka.gui.explorer.DataGeneratorPanel: generates the instances, returns TRUE if successful stores output as a string
execute(boolean) - Method in class weka.gui.explorer.DataGeneratorPanel: generates the instances, returns TRUE if successful
execute() - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor and stores it
execute(boolean) - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor
execute(boolean, boolean) - Method in class weka.gui.GenericPropertiesCreator: generates the props-file for the GenericObjectEditor and stores it only if the the param store is TRUE.
execute(String[]) - Method in class weka.gui.simplecli.AbstractCommand: Executes the command with the given parameters.
execute() - Method in class weka.gui.sql.QueryPanel: executes the current query.
executeFlow(boolean) - Method in class weka.gui.knowledgeflow.VisibleLayout: Execute the flow managed by this layout
ExecuteProcess - Class in weka.knowledgeflow.steps: Knowledge Flow step that can execute static system commands or commands that are dynamically defined by the values of attributes in incoming instance or environment connections.
ExecuteProcess() - Constructor for class weka.knowledgeflow.steps.ExecuteProcess
ExecuteProcessStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ExecuteProcess step
ExecuteProcessStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ExecuteProcessStepEditorDialog
executeTask(Task) - Method in interface weka.experiment.Compute: Execute a task
executeTask(Task) - Method in class weka.experiment.RemoteEngine: Takes a task object and queues it for execution
EXECUTION_ENV - Static variable in class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults
EXECUTION_ENV_KEY - Static variable in class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults
ExecutionEnvironment - Interface in weka.knowledgeflow: Client (i.e.
executionFinished() - Method in interface weka.knowledgeflow.ExecutionFinishedCallback: Notification of the finish of execution
ExecutionFinishedCallback - Interface in weka.knowledgeflow: Callback interface for receiving notification of a flow finishing execution
ExecutionResult<T> - Class in weka.knowledgeflow: Stores the result generated by a StepTask.
ExecutionResult() - Constructor for class weka.knowledgeflow.ExecutionResult
executionSlotsTipText() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the tip text for this property.
exists(TechnicalInformation.Field) - Method in class weka.core.TechnicalInformation: returns TRUE if the field is stored and has a value different from the empty string.
Exit - Class in weka.gui.simplecli: Closes the Simple CLI window.
Exit() - Constructor for class weka.gui.simplecli.Exit
EXP_INDEX_TABLE - Static variable in class weka.experiment.DatabaseUtils: The name of the table containing the index to experiments.
EXP_RESULT_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the results table name.
EXP_RESULT_PREFIX - Static variable in class weka.experiment.DatabaseUtils: The prefix for result table names.
EXP_SETUP_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the experiment setup (parameters).
EXP_TYPE_COL - Static variable in class weka.experiment.DatabaseUtils: The name of the column containing the experiment type (ResultProducer).
expectedCosts(double[]) - Method in class weka.classifiers.CostMatrix: Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedCosts(double[], Instance) - Method in class weka.classifiers.CostMatrix: Calculates the expected misclassification cost for each possible class value, given class probability estimates.
expectedResultsPerAverageTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
Experiment - Class in weka.experiment: Holds all the necessary configuration information for a standard type experiment.
Experiment() - Constructor for class weka.experiment.Experiment
Experimenter - Class in weka.gui.experiment: The main class for the experiment environment.
Experimenter() - Constructor for class weka.gui.experiment.Experimenter: Creates the experiment environment gui with no initial experiment
Experimenter(boolean) - Constructor for class weka.gui.experiment.Experimenter: Creates the experiment environment gui with no initial experiment
ExperimenterDefaults - Class in weka.gui.experiment: This class offers get methods for the default Experimenter settings in the props file weka/gui/experiment/Experimenter.props.
ExperimenterDefaults() - Constructor for class weka.gui.experiment.ExperimenterDefaults
experimentIndexExists() - Method in class weka.experiment.DatabaseUtils: Returns true if the experiment index exists.
ExplicitTestsetResultProducer - Class in weka.experiment: Loads the external test set and calls the appropriate SplitEvaluator to generate some results.
The filename of the test set is constructed as follows:
<dir> + / + <prefix> + <relation-name> + <suffix>
The relation-name can be modified by using the regular expression to replace the matching sub-string with a specified replacement string.
ExplicitTestsetResultProducer() - Constructor for class weka.experiment.ExplicitTestsetResultProducer
Explorer - Class in weka.gui.explorer: The main class for the Weka explorer.
Explorer() - Constructor for class weka.gui.explorer.Explorer: Creates the experiment environment gui with no initial experiment
Explorer.CapabilitiesFilterChangeEvent - Class in weka.gui.explorer: This event can be fired in case the capabilities filter got changed
Explorer.CapabilitiesFilterChangeListener - Interface in weka.gui.explorer: Interface for classes that listen for filter changes.
Explorer.ExplorerPanel - Interface in weka.gui.explorer: A common interface for panels to be displayed in the Explorer
Explorer.LogHandler - Interface in weka.gui.explorer: A common interface for panels in the explorer that can handle logs
ExplorerDefaults - Class in weka.gui.explorer: This class offers get methods for the default Explorer settings in the props file weka/gui/explorer/Explorer.props.
ExplorerDefaults() - Constructor for class weka.gui.explorer.ExplorerDefaults
ExponentialFormat - Class in weka.core.matrix
ExponentialFormat() - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int, boolean) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialFormat(int, int, boolean, boolean) - Constructor for class weka.core.matrix.ExponentialFormat
ExponentialSmoothing - Class in weka.core.pmml.jaxbbindings: Java class for ExponentialSmoothing element declaration.
ExponentialSmoothing() - Constructor for class weka.core.pmml.jaxbbindings.ExponentialSmoothing
exponentTipText() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the tip text for this property
exponentTipText() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the tip text for this property
Expression - Class in weka.core.pmml
Expression(FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.Expression
Expression - Class in weka.datagenerators.classifiers.regression: A data generator for generating y according to a given expression out of randomly generated x.
E.g., the mexican hat can be generated like this:
sin(abs(a1)) / abs(a1)
In addition to this function, the amplitude can be changed and gaussian noise can be added.
Expression() - Constructor for class weka.datagenerators.classifiers.regression.Expression: initializes the generator
ExpressionClause() - Constructor for class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
ExpressionClause(FlowByExpression.ExpressionClause.ExpressionType, String, String, boolean, boolean) - Constructor for class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Construct a new ExpressionClause
ExpressionNode() - Constructor for class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode
expressionTipText() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the tip text for this property
expressionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the tip text for this property.
expressionTipText() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the tip text for this property.
Extension - Class in weka.core.pmml.jaxbbindings: Java class for Extension element declaration.
Extension() - Constructor for class weka.core.pmml.jaxbbindings.Extension
EXTENSION - Static variable in class weka.knowledgeflow.JSONFlowLoader: The file exetension for JSON-based flows
EXTENSION - Static variable in class weka.knowledgeflow.LegacyFlowLoader: File extension for the format handled by this flow loader
ExtensionFileFilter - Class in weka.gui: Provides a file filter for FileChoosers that accepts or rejects files based on their extension.
ExtensionFileFilter(String, String) - Constructor for class weka.gui.ExtensionFileFilter: Creates the ExtensionFileFilter
ExtensionFileFilter(String[], String) - Constructor for class weka.gui.ExtensionFileFilter: Creates an ExtensionFileFilter that accepts files that have any of the extensions contained in the supplied array.
ExtensionFileFilterWithClass - Class in weka.gui: File filter that stores an associated class alongside name and extension(s).
ExtensionFileFilterWithClass(String, String, Class) - Constructor for class weka.gui.ExtensionFileFilterWithClass: Creates the ExtensionFileFilterWithClass
ExtensionFileFilterWithClass(String[], String, Class) - Constructor for class weka.gui.ExtensionFileFilterWithClass: Creates an ExtensionFileFilterWithClass that accepts files that have any of the extensions contained in the supplied array.
extraArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: Count nr of exta arcs from other network compared to current network Note that an arc is not 'extra' if it is reversed.
extract(RevisionHandler) - Static method in class weka.core.RevisionUtils: Extracts the revision string returned by the RevisionHandler.
extract(String) - Static method in class weka.core.RevisionUtils: Extracts the revision string.
extractPackage(String) - Static method in class weka.core.ClassCache: Extracts the package name from the (clean) classname.
extremeValuesAsOutliersTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
extremeValuesFactorTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property

F

FactorList - Class in weka.core.pmml.jaxbbindings: Java class for FactorList element declaration.
FactorList() - Constructor for class weka.core.pmml.jaxbbindings.FactorList
Factory() - Constructor for class weka.gui.WekaFileChooser.Factory
FAILED - Static variable in class weka.experiment.TaskStatusInfo
failed() - Method in class weka.gui.sql.event.ConnectionEvent: whether an exception happened and is stored
failed() - Method in class weka.gui.sql.event.QueryExecuteEvent: is TRUE in case the exception is not NULL, i.e.
FALLOUT_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Fallout
False - Class in weka.core.pmml.jaxbbindings: Java class for False element declaration.
False() - Constructor for class weka.core.pmml.jaxbbindings.False
FALSE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Negatives
FALSE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Positives
falseNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false negative rate with respect to a particular class.
falseNegativeRate(int, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false negative rate with respect to a particular class.
falseNegativeRate(int) - Method in class weka.classifiers.Evaluation: Calculate the false negative rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false positive rate with respect to a particular class.
falsePositiveRate(int, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the false positive rate with respect to a particular class.
falsePositiveRate(int) - Method in class weka.classifiers.Evaluation: Calculate the false positive rate with respect to a particular class.
FARTHEST_FIRST - Static variable in class weka.clusterers.SimpleKMeans
FarthestFirst - Class in weka.clusterers: Cluster data using the FarthestFirst algorithm.

For more information see:

Hochbaum, Shmoys (1985).
FarthestFirst() - Constructor for class weka.clusterers.FarthestFirst
fastDistanceCalcTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
fastRegressionTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
FastVector<E> - Class in weka.core: Deprecated.
FastVector() - Constructor for class weka.core.FastVector: Deprecated.

Constructs an empty vector with initial capacity zero.
FastVector(int) - Constructor for class weka.core.FastVector: Deprecated.

Constructs a vector with the given capacity.
FieldColumnPair - Class in weka.core.pmml.jaxbbindings: Java class for FieldColumnPair element declaration.
FieldColumnPair() - Constructor for class weka.core.pmml.jaxbbindings.FieldColumnPair
FieldMetaInfo - Class in weka.core.pmml: Abstract superclass for various types of field meta data.
FieldMetaInfo(Element) - Constructor for class weka.core.pmml.FieldMetaInfo: Construct a new FieldMetaInfo.
FieldMetaInfo.Interval - Class in weka.core.pmml: Inner class for an Interval.
FieldMetaInfo.Interval.Closure - Enum in weka.core.pmml: Enumerated type for the closure.
FieldMetaInfo.Optype - Enum in weka.core.pmml: Enumerated type for the Optype
FieldMetaInfo.Value - Class in weka.core.pmml: Inner class for Values
FieldMetaInfo.Value.Property - Enum in weka.core.pmml: Enumerated type for the property.
FieldRef - Class in weka.core.pmml: Class encapsulating a FieldRef Expression.
FieldRef(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.FieldRef
FieldRef - Class in weka.core.pmml.jaxbbindings: Java class for FieldRef element declaration.
FieldRef() - Constructor for class weka.core.pmml.jaxbbindings.FieldRef
fields() - Method in class weka.core.TechnicalInformation: returns an enumeration over all the stored fields
fieldSeparatorTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
fieldSeparatorTipText() - Method in class weka.core.converters.CSVSaver: Returns the tip text for this property.
FIELDUSAGETYPE - Enum in weka.core.pmml.jaxbbindings: Java class for FIELD-USAGE-TYPE.
FieldValue - Class in weka.core.pmml.jaxbbindings: Java class for FieldValue element declaration.
FieldValue() - Constructor for class weka.core.pmml.jaxbbindings.FieldValue
FieldValueCount - Class in weka.core.pmml.jaxbbindings: Java class for FieldValueCount element declaration.
FieldValueCount() - Constructor for class weka.core.pmml.jaxbbindings.FieldValueCount
FILE_EXTENSION - Static variable in class weka.classifiers.CostMatrix: The deafult file extension for cost matrix files
FILE_EXTENSION - Static variable in class weka.core.converters.ArffLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.C45Loader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.CSVLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.JSONLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.LibSVMLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.LibSVMSaver: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.MatlabLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.MatlabSaver: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.SerializedInstancesLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.converters.SVMLightLoader: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.SVMLightSaver: the file extension.
FILE_EXTENSION - Static variable in class weka.core.converters.XRFFLoader: the file extension
FILE_EXTENSION - Static variable in class weka.core.Instances: The filename extension that should be used for arff files
FILE_EXTENSION - Static variable in class weka.core.xml.KOML: the extension for KOML files (including '.')
FILE_EXTENSION - Static variable in class weka.core.xml.XMLInstances: The filename extension that should be used for xrff files
FILE_EXTENSION - Static variable in class weka.core.xml.XStream: the extension for XStream files (including '.')
FILE_EXTENSION - Static variable in class weka.experiment.Experiment: The filename extension that should be used for experiment files
FILE_EXTENSION - Static variable in class weka.gui.beans.Classifier: the extension for serialized models (binary Java serialization)
FILE_EXTENSION - Static variable in class weka.gui.beans.KnowledgeFlowApp: the extension for the serialized setups (Java serialization)
FILE_EXTENSION - Static variable in class weka.gui.beans.SerializedModelSaver: the extension for serialized models (binary Java serialization)
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.AbstractFileLoader: the extension for compressed files
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.ArffLoader
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.JSONLoader: the extension for compressed files.
FILE_EXTENSION_COMPRESSED - Static variable in class weka.core.converters.XRFFLoader: the extension for compressed files
FILE_EXTENSION_JSON - Static variable in class weka.gui.knowledgeflow.MainKFPerspective: File extension for undo point files
FILE_EXTENSION_XML - Static variable in class weka.gui.beans.KnowledgeFlowApp: the extension for the serialized setups (Java serialization)
FileChooserBookmarksPanel() - Constructor for class weka.gui.WekaFileChooser.FileChooserBookmarksPanel
FileEditor - Class in weka.gui: A PropertyEditor for File objects that lets the user select a file.
FileEditor() - Constructor for class weka.gui.FileEditor
FileEnvironmentField - Class in weka.gui.beans: Deprecated.
FileEnvironmentField() - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.

Constructor
FileEnvironmentField(Environment) - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.

Constructor
FileEnvironmentField(String, Environment) - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.
FileEnvironmentField(String, Environment, int) - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.

Constructor
FileEnvironmentField(String, Environment, int, boolean) - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.

Constructor
FileEnvironmentField(String, int, boolean) - Constructor for class weka.gui.beans.FileEnvironmentField: Deprecated.

Constructor
FileEnvironmentField - Class in weka.gui: Widget that displays a label, editable combo box for selecting environment variables and a button for brining up a file browser.
FileEnvironmentField() - Constructor for class weka.gui.FileEnvironmentField: Constructor
FileEnvironmentField(Environment) - Constructor for class weka.gui.FileEnvironmentField: Constructor
FileEnvironmentField(String, Environment) - Constructor for class weka.gui.FileEnvironmentField
FileEnvironmentField(String, Environment, int) - Constructor for class weka.gui.FileEnvironmentField: Constructor
FileEnvironmentField(String, Environment, int, boolean) - Constructor for class weka.gui.FileEnvironmentField: Constructor
FileEnvironmentField(String, int, boolean) - Constructor for class weka.gui.FileEnvironmentField: Constructor
FileHelper - Class in weka.core: Wrapper class for File objects.
FileHelper(File) - Constructor for class weka.core.FileHelper: Constructor
FileHelper() - Constructor for class weka.core.FileHelper: No-op constructor for beans conformity
FileLogger - Class in weka.core.logging: A simple file logger, that just logs to a single file.
FileLogger() - Constructor for class weka.core.logging.FileLogger
filePrefix() - Method in class weka.core.converters.AbstractFileSaver: Gets the file name prefix
filePrefix() - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
filePrefix() - Method in interface weka.core.converters.Saver: Gets the file prefix This method is used in the KnowledgeFlow GUI.
FilePropertyMetadata - Annotation Type in weka.gui: Method annotation that can be used to provide some additional information for handling file properties in the GUI.
FileScriptingPanel - Class in weka.gui.scripting: Supports loading/saving of files.
FileScriptingPanel() - Constructor for class weka.gui.scripting.FileScriptingPanel
FileScriptingPanel.BasicAction - Class in weka.gui.scripting: A slightly extended action class.
FileSourcedConverter - Interface in weka.core.converters: Interface to a loader/saver that loads/saves from a file source.
fill(Shape) - Method in class weka.gui.visualize.PostscriptGraphics
fill3DRect(int, int, int, int, boolean) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle with 3D effect in current pen color.
fillArc(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillFrame(Component) - Method in interface weka.gui.MainMenuExtension: Fills the frame with life, like adding components, window listeners, setting size, location, etc.
fillIn(int[], boolean[][]) - Method in class weka.classifiers.bayes.net.MarginCalculator: Apply Tarjan and Yannakakis (1984) fill in algorithm for graph triangulation.
fillOval(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled Oval in current pen color.
fillPolygon(int[], int[], int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillPolygon(Polygon) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillRect(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Draw a filled rectangle in current pen color.
fillRoundRect(int, int, int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
fillWithMissingTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
Filter - Class in weka.filters: An abstract class for instance filters: objects that take instances as input, carry out some transformation on the instance and then output the instance.
Filter() - Constructor for class weka.filters.Filter
Filter - Class in weka.gui.beans: A wrapper bean for Weka filters
Filter() - Constructor for class weka.gui.beans.Filter
FILTER - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
Filter - Class in weka.knowledgeflow.steps: Step that wraps a Weka filter.
Filter() - Constructor for class weka.knowledgeflow.steps.Filter
FILTER_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
FILTER_NONE - Static variable in class weka.classifiers.functions.GaussianProcesses: no filter
FILTER_NONE - Static variable in class weka.classifiers.functions.SMO: filter: No normalization/standardization
FILTER_NONE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: None
FILTER_NONE - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: No normalization.
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.GaussianProcesses: normalizes the data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMO: filter: Normalize training data
FILTER_NORMALIZE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: Normalzie
FILTER_NORMALIZE_ALL - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: Normalize all data.
FILTER_NORMALIZE_TEST_ONLY - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: normalization: Normalize test data only.
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.GaussianProcesses: standardizes the data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMO: filter: Standardize training data
FILTER_STANDARDIZE - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data: Standardize
filterAfterFirstBatchTipText() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the tip text for this property.
FilterBeanInfo - Class in weka.gui.beans: Bean info class for the Filter bean
FilterBeanInfo() - Constructor for class weka.gui.beans.FilterBeanInfo
FilterCustomizer - Class in weka.gui.beans: GUI customizer for the filter bean
FilterCustomizer() - Constructor for class weka.gui.beans.FilterCustomizer
FilteredAssociationRules - Class in weka.associations: Class encapsulating a list of association rules and the preprocessing filter that was applied before they were generated.
FilteredAssociationRules(String, Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociationRules(Object, Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociationRules(Filter, AssociationRules) - Constructor for class weka.associations.FilteredAssociationRules: Constructs a new FilteredAssociationRules.
FilteredAssociator - Class in weka.associations: Class for running an arbitrary associator on data that has been passed through an arbitrary filter.
FilteredAssociator() - Constructor for class weka.associations.FilteredAssociator: Default constructor.
FilteredClassifier - Class in weka.classifiers.meta: Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
FilteredClassifier() - Constructor for class weka.classifiers.meta.FilteredClassifier: Default constructor.
FilteredClusterer - Class in weka.clusterers: Class for running an arbitrary clusterer on data that has been passed through an arbitrary filter.
FilteredClusterer() - Constructor for class weka.clusterers.FilteredClusterer: Default constructor.
FilteredDistance - Class in weka.core: Applies the given filter before calling the given distance function.
FilteredDistance() - Constructor for class weka.core.FilteredDistance: Default constructor: need to set up Remove filter.
FilteredNeighbourSearch - Class in weka.core.neighboursearch: Applies the given filter before calling the given neighbour search method.
FilteredNeighbourSearch() - Constructor for class weka.core.neighboursearch.FilteredNeighbourSearch
filterFile(Filter, String[]) - Static method in class weka.filters.Filter: Method for testing filters.
filtersTipText() - Method in class weka.filters.MultiFilter: Returns the tip text for this property
filtersTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns the tip text for this property.
filterTipText() - Method in class weka.associations.FilteredAssociator: Returns the tip text for this property
filterTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the tip text for this property
filterTipText() - Method in class weka.clusterers.FilteredClusterer: Returns the tip text for this property.
filterTipText() - Method in class weka.core.FilteredDistance: Returns the tip text for this property
filterTipText() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.GaussianProcesses: Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
filterTypeTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
finalize() - Method in class weka.gui.sql.ResultSetTable: frees up the memory
finalize() - Method in class weka.gui.sql.ResultSetTableModel: frees up the memory.
finalize() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
finalizeAggregation() - Method in class weka.classifiers.bayes.NaiveBayes
finalizeAggregation() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText
finalizeAggregation() - Method in class weka.classifiers.evaluation.AggregateableEvaluation
finalizeAggregation() - Method in class weka.classifiers.functions.Logistic: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.functions.SGD: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.functions.SGDText: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.meta.Bagging: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.classifiers.meta.Vote: Call to complete the aggregation process.
finalizeAggregation() - Method in interface weka.core.Aggregateable: Call to complete the aggregation process.
finalizeAggregation() - Method in class weka.core.DictionaryBuilder
finalizeAggregation() - Method in class weka.estimators.DiscreteEstimator
finalizeAggregation() - Method in class weka.estimators.KernelEstimator
finalizeAggregation() - Method in class weka.estimators.NormalEstimator
finalizeDictionary() - Method in class weka.core.DictionaryBuilder: Performs final pruning and consolidation according to the number of words to keep property.
find(String) - Method in class weka.core.ClassCache: Find all classes that have the supplied matchText String in their suffix.
find(String, String[]) - Static method in class weka.core.ClassDiscovery: Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(String, String) - Static method in class weka.core.ClassDiscovery: Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(Class<?>, String[]) - Static method in class weka.core.ClassDiscovery: Checks the given packages for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find(String) - Static method in class weka.core.ClassDiscovery: Find all classes that have the supplied matchText String in their suffix.
find(Class<?>, String) - Static method in class weka.core.ClassDiscovery: Checks the given package for classes that inherited from the given class, in case it's a class, or implement this class, in case it's an interface.
find() - Method in class weka.core.FindWithCapabilities: returns a list with all the classnames that fit the criteria.
find(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath: returns the property and object associated with the given path, null if a problem occurred.
find(String) - Method in class weka.core.Trie.TrieNode: returns the node with the given suffix
findAllRulesForSupportLevelTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
findArgmin(double[], double[][]) - Method in class weka.core.ConjugateGradientOptimization: Main algorithm.
findArgmin(double[], double[][]) - Method in class weka.core.Optimization: Main algorithm.
findBestLeaf(double[], RuleNode[]) - Method in class weka.classifiers.trees.m5.RuleNode: Find the leaf with greatest coverage
findCentralTendencies(double[]) - Method in class weka.classifiers.BVDecomposeSegCVSub: Finds the central tendency, given the classifications for an instance.
findClassloaderForResource(String) - Method in class weka.core.WekaPackageClassLoaderManager: Get the classloader that covers the jar that contains the named resource.
findInstance(String, Integer...) - Static method in class weka.gui.beans.BeanInstance: Search for a named bean in the indexed flow
findInstance(Point, Integer...) - Static method in class weka.gui.beans.BeanInstance: Looks for a bean (if any) whose bounds contain the supplied point
findInstances(Rectangle, Integer...) - Static method in class weka.gui.beans.BeanInstance: Looks for all beans (if any) located within the supplied bounding box.
findMinDistance(Instances, int) - Static method in class weka.estimators.EstimatorUtils: Find the minimum distance between values.
findNodes(String) - Method in class weka.core.xml.XMLDocument: Returns the nodes that the given xpath expression will find in the document.
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
findNumBinsTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
findPackages() - Static method in class weka.core.ClassDiscovery: Lists all packages it can find in the classpath.
findPotentialStartPoints() - Method in class weka.knowledgeflow.Flow: Get a list of potential start points in this Flow.
findReadMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler: returns the method with the given name that has the same signature as readFromXML() of the XMLSerialiation class.
findResource(String) - Method in class weka.core.WekaPackageClassLoaderManager: Find a named resource.
findResources(String) - Method in class weka.core.WekaPackageClassLoaderManager: Find a named resource.
findSchemeMatch(Class<?>, String, boolean, boolean) - Static method in class weka.Run: Find a scheme that matches the supplied suffix
findSchemeMatch(String, boolean) - Static method in class weka.Run: Find a scheme that matches the supplied suffix
findStep(String) - Method in class weka.knowledgeflow.Flow: Find a Step by name
findStep(String, Class) - Method in class weka.knowledgeflow.StepInjectorFlowRunner: Find a step in the flow
findStepInFlow(String) - Method in interface weka.knowledgeflow.StepManager: Finds a named step in the current flow.
findStepInFlow(String) - Method in class weka.knowledgeflow.StepManagerImpl: Finds a named step in the current flow.
findTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
FindWithCapabilities - Class in weka.core: Locates all classes with certain capabilities.
FindWithCapabilities() - Constructor for class weka.core.FindWithCapabilities
findWriteMethod(Object, String) - Static method in class weka.core.xml.XMLSerializationMethodHandler: returns the method with the given name that has the same signature as writeToXML() of the XMLSerialiation class.
FINE - Static variable in class weka.core.Debug: the log level Fine
FINER - Static variable in class weka.core.Debug: the log level Finer
FINEST - Static variable in class weka.core.Debug: the log level Finest
finished() - Method in class weka.experiment.OutputZipper: Closes the zip file.
FINISHED - Static variable in class weka.experiment.TaskStatusInfo
finished(Logger) - Method in class weka.gui.beans.StreamThroughput: Register the end of measurement.
finished() - Method in class weka.gui.beans.StreamThroughput: Register the end of measurement.
finished() - Method in class weka.gui.visualize.PostscriptGraphics: Finalizes output file.
finished() - Method in interface weka.knowledgeflow.StepManager: Step implementations processing batch data should call this to indicate that they have finished all processing.
finished() - Method in class weka.knowledgeflow.StepManagerImpl: Finished all processing.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Fires a LayoutCompleteEvent.
fireLayoutCompleteEvent(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This fires a LayoutCompleteEvent once a layout has been completed.
FIRST - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner: use the first attribute as class.
firstElement() - Method in class weka.core.FastVector: Deprecated.

Returns the first element of the vector.
firstElement() - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the first component of this list.
firstInstance() - Method in class weka.core.Instances: Returns the first instance in the set.
FirstOrder - Class in weka.filters.unsupervised.attribute: This instance filter takes a range of N numeric attributes and replaces them with N-1 numeric attributes, the values of which are the difference between consecutive attribute values from the original instance.
FirstOrder() - Constructor for class weka.filters.unsupervised.attribute.FirstOrder
firstValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
firstValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
fitToScreen() - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer: Fits the tree to the current screen size.
fitToScreen() - Method in class weka.gui.treevisualizer.TreeVisualizer: Fits the tree to the current screen size.
FixedDictionaryStringToWordVector - Class in weka.filters.unsupervised.attribute: Converts String attributes into a set of attributes representing word occurrence (depending on the tokenizer) information from the text contained in the strings.
FixedDictionaryStringToWordVector() - Constructor for class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector
FlexibleDecimalFormat - Class in weka.core.matrix
FlexibleDecimalFormat() - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(int, boolean, boolean, boolean) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FlexibleDecimalFormat(double) - Constructor for class weka.core.matrix.FlexibleDecimalFormat
FLOAT - Static variable in interface weka.core.expressionlanguage.parser.sym
FLOAT - Static variable in class weka.experiment.DatabaseUtils: Type mapping for FLOAT used for reading experiment results.
FloatingPointFormat - Class in weka.core.matrix: Class for the format of floating point numbers
FloatingPointFormat() - Constructor for class weka.core.matrix.FloatingPointFormat: Default constructor
FloatingPointFormat(int) - Constructor for class weka.core.matrix.FloatingPointFormat
FloatingPointFormat(int, int) - Constructor for class weka.core.matrix.FloatingPointFormat
FloatingPointFormat(int, int, boolean) - Constructor for class weka.core.matrix.FloatingPointFormat
FLOOR - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
FLOOR1 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
Flow - Class in weka.knowledgeflow: Class that encapsulates the Steps involved in a Knowledge Flow process.
Flow() - Constructor for class weka.knowledgeflow.Flow
FLOW_DIRECTORY_KEY - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Flow file directory key
FLOW_FILE_EXTENSIONS - Static variable in class weka.knowledgeflow.Flow: Holds available file extensions for flow files handled
FLOW_NAME - Static variable in class weka.knowledgeflow.JSONFlowUtils
FLOW_PARENT_DIRECTORY_VARIABLE_KEY - Static variable in class weka.gui.knowledgeflow.MainKFPerspective: Key for the environment variable that holds the parent directory of a loaded flow
flowBusy() - Method in class weka.knowledgeflow.FlowRunner: Checks to see if any step(s) are doing work
FlowByExpression - Class in weka.gui.beans: A bean that splits incoming instances (or instance streams) according to the evaluation of a logical expression.
FlowByExpression() - Constructor for class weka.gui.beans.FlowByExpression: Constructor
FlowByExpression - Class in weka.knowledgeflow.steps: A step that splits incoming instances (or instance streams) according to the evaluation of a logical expression.
FlowByExpression() - Constructor for class weka.knowledgeflow.steps.FlowByExpression
FlowByExpression.BracketNode - Class in weka.knowledgeflow.steps: An expression node that encloses other expression nodes in brackets
FlowByExpression.ExpressionClause - Class in weka.knowledgeflow.steps: An expression node that represents a clause of an expression
FlowByExpression.ExpressionClause.ExpressionType - Enum in weka.knowledgeflow.steps
FlowByExpression.ExpressionNode - Class in weka.knowledgeflow.steps: Abstract base class for parts of a boolean expression.
FlowByExpressionBeanInfo - Class in weka.gui.beans: BeanInfo class for FlowByExpression
FlowByExpressionBeanInfo() - Constructor for class weka.gui.beans.FlowByExpressionBeanInfo
FlowByExpressionCustomizer - Class in weka.gui.beans: Customizer for the FlowByExpression node
FlowByExpressionCustomizer() - Constructor for class weka.gui.beans.FlowByExpressionCustomizer: Constructor
FlowByExpressionStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the FlowByExpression step
FlowByExpressionStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.FlowByExpressionStepEditorDialog
FlowExecutor - Interface in weka.knowledgeflow: Interface to something that can execute a Knowledge Flow process
FlowLoader - Interface in weka.knowledgeflow: Interface to something that can load a Knowledge Flow
FlowRunner - Class in weka.gui.beans: Small utility class for executing KnowledgeFlow flows outside of the KnowledgeFlow application
FlowRunner() - Constructor for class weka.gui.beans.FlowRunner: Constructor
FlowRunner(boolean, boolean) - Constructor for class weka.gui.beans.FlowRunner
FlowRunner - Class in weka.knowledgeflow: A FlowExecutor that can launch start points in a flow in parallel or sequentially.
FlowRunner() - Constructor for class weka.knowledgeflow.FlowRunner: Constructor
FlowRunner(Settings) - Constructor for class weka.knowledgeflow.FlowRunner: Constructor
FlowRunner.SimpleLogger - Class in weka.gui.beans
FlowRunner.SimpleLogger - Class in weka.knowledgeflow: A simple logging implementation that writes to standard out
flowToJSON(Flow) - Static method in class weka.knowledgeflow.JSONFlowUtils: Utility routine to serialize a supplied flow to a JSON string
flush() - Method in class weka.core.logging.OutputLogger.OutputPrintStream: ignored.
flush() - Method in class weka.core.Tee: flushes all the printstreams.
fMeasure(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the F-Measure with respect to a particular class.
fMeasure(double, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the F-Measure with respect to a particular class.
fMeasure(int) - Method in class weka.classifiers.Evaluation: Calculate the F-Measure with respect to a particular class.
FMEASURE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: FMeasure
FOLD_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the key field containing the fold number
foldsTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
foldsTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
foldsTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
foldsTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
foldsTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker: Tip text for this property
foldTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the tip text for this property
foldTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the tip text for this property
FontHelper - Class in weka.core: Wrapper class for Font objects.
FontHelper(Font) - Constructor for class weka.core.FontHelper: Constructor
FontHelper() - Constructor for class weka.core.FontHelper: No-op constructor (for beans conformity)
forCapabilities(Capabilities) - Static method in class weka.core.TestInstances: returns a TestInstances instance setup already for the the given capabilities.
FORCE_RESAMPLE_WITH_WEIGHTS - Static variable in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: command-line option for resampling with weights.
forceResampleWithWeightsTipText() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns the tip text for this property
forInstances(Instances) - Static method in class weka.core.Capabilities: returns a Capabilities object specific for this data.
forInstances(Instances, boolean) - Static method in class weka.core.Capabilities: returns a Capabilities object specific for this data.
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.ExponentialFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.FlexibleDecimalFormat
format(double, StringBuffer, FieldPosition) - Method in class weka.core.matrix.FloatingPointFormat
FORMAT_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent
FORMAT_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent: Specifies that the instance format is available
FORMAT_HHMMSS - Static variable in class weka.core.Debug.Clock: the output format in hours:minutes:seconds, with fraction of msecs
FORMAT_MILLISECONDS - Static variable in class weka.core.Debug.Clock: the output format in milli-seconds
FORMAT_SECONDS - Static variable in class weka.core.Debug.Clock: the output format in seconds, with fraction of msecs
formatDate(double) - Method in class weka.core.Attribute: Returns the given amount of milliseconds formatted according to the current Date format.
formatString(String) - Method in class weka.core.matrix.FlexibleDecimalFormat
formatTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
forName(String, String[]) - Static method in class weka.associations.AbstractAssociator: Creates a new instance of a associator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASEvaluation: Creates a new instance of an attribute/subset evaluator given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.attributeSelection.ASSearch: Creates a new instance of a search class given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.classifiers.AbstractClassifier: Creates a new instance of a classifier given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.classifiers.functions.supportVector.Kernel: Creates a new instance of a kernel given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String, String[]) - Static method in class weka.clusterers.AbstractClusterer: Creates a new instance of a clusterer given it's class name and (optional) arguments to pass to it's setOptions method.
forName(Class<?>, String, String[]) - Static method in class weka.core.ResourceUtils: Creates a new instance of an object given it's class name and (optional) arguments to pass to it's setOptions method.
forName(Class<?>, String, String[]) - Static method in class weka.core.Utils: Creates a new instance of an object given it's class name and (optional) arguments to pass to it's setOptions method.
forName(String) - Static method in class weka.core.WekaPackageClassLoaderManager: Return the class object for the supplied class name.
forName(String, boolean) - Static method in class weka.core.WekaPackageClassLoaderManager: Return the class object for the supplied class name.
forName(String, String[]) - Static method in class weka.estimators.Estimator: Creates a new instance of a estimator given it's class name and (optional) arguments to pass to it's setOptions method.
foundUsefulAttribute() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns true if a usable attribute was found.
foundUsefulAttribute() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Returns true if a usable attribute was found.
FP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: False Positive Rate"
FPGrowth - Class in weka.associations: Class implementing the FP-growth algorithm for finding large item sets without candidate generation.
FPGrowth() - Constructor for class weka.associations.FPGrowth: Construct a new FPGrowth object.
FProbability(double, int, int) - Static method in class weka.core.Statistics: Computes probability of F-ratio.
freeNotCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule: Free up memory consumed by the set of instances not covered by this rule.
FREQ_ASCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder: The class values are sorted in ascending order based on their frequencies
FREQ_DESCEND - Static variable in class weka.filters.supervised.attribute.ClassOrder: The class values are sorted in descending order based on their frequencies
fromCommandline(String) - Static method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns a fully configured object from the given commandline.
FromFile - Class in weka.classifiers.bayes.net.search.fixed: The FromFile reads the structure of a Bayes net from a file in BIFF format.
FromFile() - Constructor for class weka.classifiers.bayes.net.search.fixed.FromFile
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.GAP
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE
fromValue(String) - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC
fromXML(Document) - Method in class weka.core.xml.XMLSerialization: returns the given DOM document as an instance of the specified class
fullValue() - Method in class weka.gui.HierarchyPropertyParser: The full value of the current node, i.e.
Function - Class in weka.core.pmml: Abstract superclass for PMML built-in and DefineFunctions.
Function() - Constructor for class weka.core.pmml.Function
FUNCTION_1 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 1
FUNCTION_10 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 10
FUNCTION_2 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 2
FUNCTION_3 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 3
FUNCTION_4 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 4
FUNCTION_5 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 5
FUNCTION_6 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 6
FUNCTION_7 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 7
FUNCTION_8 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 8
FUNCTION_9 - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: function 9
FUNCTION_TAGS - Static variable in class weka.datagenerators.classifiers.classification.Agrawal: the funtion tags
functionTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property

G

gainRatio() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns (C4.5-type) gain ratio for the generated split.
gainRatio() - Method in class weka.classifiers.trees.j48.C45Split: Returns (C4.5-type) gain ratio for the generated split.
gainRatio(double[][]) - Static method in class weka.core.ContingencyTables: Computes gain ratio for contingency table (split on rows).
GainRatioAttributeEval - Class in weka.attributeSelection: GainRatioAttributeEval :

Evaluates the worth of an attribute by measuring the gain ratio with respect to the class.

GainR(Class, Attribute) = (H(Class) - H(Class | Attribute)) / H(Attribute).

Valid options are:
GainRatioAttributeEval() - Constructor for class weka.attributeSelection.GainRatioAttributeEval: Constructor
GainRatioSplitCrit - Class in weka.classifiers.trees.j48: Class for computing the gain ratio for a given distribution.
GainRatioSplitCrit() - Constructor for class weka.classifiers.trees.j48.GainRatioSplitCrit
gamma(double) - Static method in class weka.core.Statistics: Returns the Gamma function of the argument.
gammaTipText() - Method in class weka.classifiers.functions.supportVector.RBFKernel: Returns the tip text for this property
GAP - Enum in weka.core.pmml.jaxbbindings: Java class for GAP.
GAUSS - Static variable in class weka.classifiers.lazy.LWL
GAUSSIAN - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster type: gaussian
GAUSSIAN - Static variable in class weka.filters.unsupervised.attribute.RandomProjection: distribution type: gaussian
GaussianConditionalSufficientStats - Class in weka.classifiers.trees.ht: Maintains sufficient stats for a Gaussian distribution for a numeric attribute
GaussianConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
GaussianDistribution - Class in weka.core.pmml.jaxbbindings: Java class for GaussianDistribution element declaration.
GaussianDistribution() - Constructor for class weka.core.pmml.jaxbbindings.GaussianDistribution
GaussianProcesses - Class in weka.classifiers.functions: * Implements Gaussian processes for regression without hyperparameter-tuning.
GaussianProcesses() - Constructor for class weka.classifiers.functions.GaussianProcesses
GE - Static variable in interface weka.core.expressionlanguage.parser.sym
GeneralRegression - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML General Regression model.
GeneralRegression(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.GeneralRegression: Constructs a GeneralRegression classifier.
GeneralRegressionModel - Class in weka.core.pmml.jaxbbindings: Java class for GeneralRegressionModel element declaration.
GeneralRegressionModel() - Constructor for class weka.core.pmml.jaxbbindings.GeneralRegressionModel
generate() - Method in class weka.core.Javadoc: generates either the plain Javadoc (if no filename specified) or the updated file (if a filename is specified).
generate() - Method in class weka.core.ListOptions: generates the options string.
generate() - Method in class weka.core.TestInstances: Generates a new dataset
generate(String) - Method in class weka.core.TestInstances: generates a new dataset.
generateExample() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.classifiers.classification.LED24: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.classifiers.classification.RDG1: Generate an example of the dataset dataset.
generateExample() - Method in class weka.datagenerators.classifiers.regression.Expression: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Generates one example of the dataset.
generateExample() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Generate an example of the dataset.
generateExample() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Generate an example of the dataset.
generateExample() - Method in class weka.datagenerators.DataGenerator: Generates one example of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.LED24: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.classification.RDG1: Generate all examples of the dataset.
generateExamples(int, Random, Instances) - Method in class weka.datagenerators.classifiers.classification.RDG1: Generate all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.regression.Expression: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Generates all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Generate all examples of the dataset.
generateExamples(Random, Instances) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Generate all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Generate all examples of the dataset.
generateExamples() - Method in class weka.datagenerators.DataGenerator: Generates all examples of the dataset.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.LED24: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.classifiers.classification.RDG1: Compiles documentation about the data generation.
generateFinished() - Method in class weka.datagenerators.classifiers.regression.Expression: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Generates a comment string that documentats the data generator.
generateFinished() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Compiles documentation about the data generation after the generation process
generateFinished() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Compiles documentation about the data generation after the generation process
generateFinished() - Method in class weka.datagenerators.DataGenerator: Generates a comment string that documentates the data generator.
generateHelp() - Method in class weka.core.Javadoc: generates a string to print as help on the console
generateHelp() - Method in class weka.core.ListOptions: generates a string to print as help on the console
generateInstances() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: GenerateInstances generates random instances sampling from the distribution represented by the Bayes network structure.
generateInstances(int[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Generate an instance.
generateInstances(int[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Generates a new instance using one kernel estimator.
generateInstances() - Method in class weka.gui.explorer.PreprocessPanel: sets Instances generated via DataGenerators (pops up a Dialog)
generateOutput() - Method in class weka.gui.visualize.BMPWriter: generates the actual output.
generateOutput() - Method in class weka.gui.visualize.JPEGWriter: generates the actual output.
generateOutput() - Method in class weka.gui.visualize.PNGWriter: generates the actual output.
generateOutput() - Method in class weka.gui.visualize.PostscriptWriter: generates the actual output
generatePartition(Instances) - Method in class weka.classifiers.meta.Bagging: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in class weka.classifiers.meta.RandomCommittee: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in class weka.classifiers.trees.J48: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in class weka.classifiers.trees.RandomTree: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in class weka.classifiers.trees.REPTree: Builds the classifier to generate a partition.
generatePartition(Instances) - Method in interface weka.core.PartitionGenerator: Builds the classifier to generate a partition.
generateRandomNetwork() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Generate random connected Bayesian network with discrete nodes having all the same cardinality.
generateRandomNetworkStructure(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator: GenerateRandomNetworkStructure generate random connected Bayesian network
generateRankingTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
generateRankingTipText() - Method in class weka.attributeSelection.Ranker: Returns the tip text for this property
generateRules(double, ArrayList<Hashtable<ItemSet, Integer>>, int) - Method in class weka.associations.AprioriItemSet: Generates all rules for an item set.
generateRules(double, boolean) - Method in class weka.associations.LabeledItemSet: Generates rules out of item sets
generateRulesBruteForce(double, int, ArrayList<Hashtable<ItemSet, Integer>>, int, int, double) - Method in class weka.associations.AprioriItemSet: Generates all significant rules for an item set.
generateRulesBruteForce(FPGrowth.FrequentItemSets, DefaultAssociationRule.METRIC_TYPE, double, int, int, int) - Static method in class weka.associations.FPGrowth: Generate all association rules, from the supplied frequet item sets, that meet a given minimum metric threshold.
generateRulesTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
generatesOutput() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns whether regular output is generated or not.
generatesOutput() - Method in class weka.classifiers.evaluation.output.prediction.Null: Returns always false.
generateStart() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.classification.LED24: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.classification.RDG1: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.regression.Expression: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Generates a comment string that documentates the data generator.
generateStart() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Compiles documentation about the data generation before the generation process
generateStart() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Compiles documentation about the data generation before the generation process
generateStart() - Method in class weka.datagenerators.DataGenerator: Generates a comment string that documentates the data generator.
GeneratorPropertyIteratorPanel - Class in weka.gui.experiment: This panel controls setting a list of values for an arbitrary resultgenerator property for an experiment to iterate over.
GeneratorPropertyIteratorPanel() - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel: Creates the property iterator panel initially disabled.
GeneratorPropertyIteratorPanel(Experiment) - Constructor for class weka.gui.experiment.GeneratorPropertyIteratorPanel: Creates the property iterator panel and sets the experiment.
GenericArrayEditor - Class in weka.gui: A PropertyEditor for arrays of objects that themselves have property editors.
GenericArrayEditor() - Constructor for class weka.gui.GenericArrayEditor
GenericObjectEditor - Class in weka.gui: A PropertyEditor for objects.
GenericObjectEditor() - Constructor for class weka.gui.GenericObjectEditor: Default constructor.
GenericObjectEditor(boolean) - Constructor for class weka.gui.GenericObjectEditor: Constructor that allows specifying whether it is possible to change the class within the editor dialog.
GenericObjectEditor.CapabilitiesFilterDialog - Class in weka.gui: A dialog for selecting Capabilities to look for in the GOE tree.
GenericObjectEditor.GOEPanel - Class in weka.gui: Handles the GUI side of editing values.
GenericObjectEditor.GOETreeNode - Class in weka.gui: A specialized TreeNode for supporting filtering via Capabilities.
GenericObjectEditor.JTreePopupMenu - Class in weka.gui: Creates a popup menu containing a tree that is aware of the screen dimensions.
GenericObjectEditorHistory - Class in weka.gui: A helper class for maintaining a history of objects selected in the GOE.
GenericObjectEditorHistory() - Constructor for class weka.gui.GenericObjectEditorHistory: Initializes the history.
GenericObjectEditorHistory.HistorySelectionEvent - Class in weka.gui: Event that gets sent when a history item gets selected.
GenericObjectEditorHistory.HistorySelectionListener - Interface in weka.gui: Interface for classes that listen to selections of history items.
GenericPropertiesCreator - Class in weka.gui: This class can generate the properties object that is normally loaded from the GenericObjectEditor.props file (= PROPERTY_FILE).
GenericPropertiesCreator() - Constructor for class weka.gui.GenericPropertiesCreator: initializes the creator, locates the props file with the Utils class.
GenericPropertiesCreator(String) - Constructor for class weka.gui.GenericPropertiesCreator: initializes the creator, the given file overrides the props-file search of the Utils class
GeneticSearch - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.
GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.global.GeneticSearch
GeneticSearch - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses genetic search for finding a well scoring Bayes network structure.
GeneticSearch() - Constructor for class weka.classifiers.bayes.net.search.local.GeneticSearch
get(int) - Method in class weka.core.Instances: Returns the instance at the given position.
get(int) - Method in class weka.core.matrix.DoubleVector: Gets a single element.
get(int) - Method in class weka.core.matrix.IntVector: Gets the value of an element.
get(int, int) - Method in class weka.core.matrix.Matrix: Get a single element.
get(int) - Method in class weka.core.PropertyPath.Path: returns the element at the given index
get(int) - Method in class weka.core.Tee: returns the specified PrintStream from the list.
get(String) - Method in class weka.core.xml.MethodHandler: returns the stored method for the given property
get(Class<?>) - Method in class weka.core.xml.MethodHandler: returns the stored method for the given class
get(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the element at the specified position in this list.
get(String, String) - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the value for the specified property, if non-existent then the default value.
get(String, String) - Static method in class weka.gui.explorer.ExplorerDefaults: returns the value for the specified property, if non-existent then the default value.
GET_PERSPECTIVE_NAMES_KEY - Static variable in class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand: Command ID
getAboutPanel() - Method in class weka.gui.PropertySheetPanel: Return the panel containing global info and help for the object being edited.
getAbsoluteValue() - Method in class weka.core.pmml.jaxbbindings.Coefficients: Gets the value of the absoluteValue property.
getAccu() - Method in class weka.classifiers.rules.JRip.Antd
getAccuRate() - Method in class weka.classifiers.rules.JRip.Antd
getActionListener(JFrame) - Method in interface weka.gui.MainMenuExtension: If the extension has a custom ActionListener for the menu item, then it must be returned here.
getActivationFunction() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the activationFunction property.
getActivationFunction() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the activationFunction property.
getActualIndex(int) - Method in class weka.core.AttributeLocator: returns actual index in the Instances object.
getActualRow(int) - Method in class weka.gui.SortedTableModel: Returns the actual underlying row the given visible one represents.
getActualT1() - Method in class weka.clusterers.Canopy: Get the actual value of T1 (which may be different from the initial value if the heuristic is used)
getActualT2() - Method in class weka.clusterers.Canopy: Get the actual value of T2 (which may be different from the initial value if the heuristic is used)
getAcuity() - Method in class weka.clusterers.Cobweb: get the acuity value
getAdditional() - Method in class weka.gui.scripting.event.ScriptExecutionEvent: Returns the additional information.
getAddMatchingEndBlocks() - Method in class weka.gui.scripting.SyntaxDocument: Returns whether matching block ends are inserted or not.
getAddress() - Static method in class weka.core.Copyright: returns the address of the owner
getAdjRSquared() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the adjRSquared property.
getAdjustWeights() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns true if instance weights will be adjusted to maintain total weight per class.
getADTree() - Method in class weka.classifiers.bayes.BayesNet: get ADTree strucrture containing efficient representation of counts.
getAdvanceDataSetFirst() - Method in class weka.experiment.Experiment: Get the value of m_DataSetFirstFirst.
getAffinity() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the affinity property.
getAggregate() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the aggregate property.
getAggregate() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the aggregate property.
getAggregate() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the aggregate property.
getAIC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the aic property.
getAICc() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the aiCc property.
getAlgorithm() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the algorithm property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.MiningModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the value of the algorithmName property.
getAlgorithmName() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the algorithmName property.
getAllDependenciesForPackage(Package, Map<String, List<Dependency>>) - Method in class weka.core.packageManagement.DefaultPackageManager: Gets a full list of packages (encapsulated in Dependency objects) that are required by directly and indirectly by the named target package.
getAllDependenciesForPackage(Package, Map<String, List<Dependency>>) - Method in class weka.core.packageManagement.PackageManager: Gets a full list of packages (encapsulated in Dependency objects) that are required by directly and indirectly by the named target package.
getAllDependenciesForPackage(Package, Map<String, List<Dependency>>) - Static method in class weka.core.WekaPackageManager: Get a list of dependencies for a given package
getAllEvaluationMetricNames() - Static method in class weka.classifiers.evaluation.Evaluation: Utility method to get a list of the names of all built-in and plugin evaluation metrics
getAllEvaluationMetricNames() - Static method in class weka.classifiers.Evaluation: Utility method to get a list of the names of all built-in and plugin evaluation metrics
getAllMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper: Get a list of all available evaluation metric names
getAllowedIndices() - Method in class weka.core.AttributeLocator: returns the indices that are allowed to check for the attribute type
getAllowMultipleTabs() - Method in class weka.gui.beans.KnowledgeFlowApp
getAllowMultipleTabs() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Returns true if the perspective is allowing multiple tabs to be open
getAllowUnclassifiedInstances() - Method in class weka.classifiers.trees.RandomTree: Gets whether tree is allowed to abstain from making a prediction.
getAllPackages(PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Get all packages that the system knows about (i.e.
getAllPackages(PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Get all packages that the system knows about (i.e.
getAllPackages() - Static method in class weka.core.WekaPackageManager: Get a list of all packages
getAllTheRules() - Method in class weka.associations.Apriori: returns all the rules
getAlpha() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Get prior used in probability table estimation
getAlpha() - Method in class weka.core.pmml.jaxbbindings.Level: Gets the value of the alpha property.
getAlternate() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the alternate property.
getAlternateTargetCategory() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the alternateTargetCategory property.
getAltitude() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the altitude property.
getAltitude() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the altitude property.
getAltitude() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the altitude property.
getAmplitude() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the amplitude multiplier.
getAnimatedIcon() - Method in class weka.gui.beans.BeanVisual: Returns the animated icon
getAnimatedIconPath() - Method in class weka.gui.beans.BeanVisual: returns the path for the animated icon
getAnnotation() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the annotation property.
getAnova() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the anova property.
getAnovaRow() - Method in class weka.core.pmml.jaxbbindings.Anova: Gets the value of the anovaRow property.
getAntds() - Method in class weka.classifiers.rules.JRip.RipperRule: Return the antecedents
getAntecedent() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the antecedent property.
getAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate: Gets the value of the anyDistribution property.
getAnyDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the anyDistribution property.
getAppend() - Method in class weka.gui.beans.TextSaver
getAppend() - Method in class weka.knowledgeflow.steps.TextSaver: get whether the file should be appended to rather than overwritten
getAppendPredictedProbabilities() - Method in class weka.gui.beans.PredictionAppender: Return true if predicted probabilities are to be appended rather than class value
getAppendProbabilities() - Method in class weka.knowledgeflow.steps.PredictionAppender: Get whether to append probability distributions rather than predicted classes
getApplication() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the application property.
getApplicationDefaults() - Method in interface weka.gui.GUIApplication: Get the default values of settings for this application
getApplicationDefaults() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the default settings for this application
getApplicationDefaults() - Method in class weka.gui.WorkbenchApp: Get the default settings for this application
getApplicationID() - Method in interface weka.gui.GUIApplication: Get the ID of this application - any string unique to this application can be used
getApplicationID() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the ID of this application
getApplicationID() - Method in class weka.gui.WorkbenchApp: Get the ID of this application
getApplicationName() - Method in interface weka.gui.GUIApplication: Get the name of this application
getApplicationName() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin: Get the name to display in title bar of the enclosing JFrame for the plugin
getApplicationName() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the name of this application
getApplicationName() - Method in class weka.gui.WorkbenchApp: Get the name of this application
getApplicationSettings() - Method in class weka.gui.AbstractGUIApplication: Get the current settings for this application
getApplicationSettings() - Method in interface weka.gui.GUIApplication: Get the current settings for this application
getApplicationSettings() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the settings for this application
getApply() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the apply property.
getApply() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the apply property.
getApply() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the apply property.
getArffFile() - Method in class weka.gui.streams.InstanceLoader
getArffFile() - Method in class weka.gui.streams.InstanceSavePanel
getArgs() - Method in class weka.gui.scripting.Script.ScriptThread: Returns the commandline args.
getArray() - Method in class weka.core.matrix.DoubleVector: Access the internal one-dimensional array.
getArray() - Method in class weka.core.matrix.IntVector: Access the internal one-dimensional array.
getArray() - Method in class weka.core.matrix.Matrix: Access the internal two-dimensional array.
getArray() - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.BoundaryValues: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.ClassLabels: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.CorrelationFields: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.DiscrStats: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.TextDictionary: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.TimeException: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.XCoordinates: Gets the value of the array property.
getArray() - Method in class weka.core.pmml.jaxbbindings.YCoordinates: Gets the value of the array property.
getArrayClass(Class<?>) - Static method in class weka.core.Utils: Returns the basic class of an array class (handles multi-dimensional arrays).
getArrayCopy() - Method in class weka.core.matrix.DoubleVector: Returns a copy of the DoubleVector usng a double array.
getArrayCopy() - Method in class weka.core.matrix.IntVector: Returns a copy of the internal one-dimensional array.
getArrayCopy() - Method in class weka.core.matrix.Matrix: Copy the internal two-dimensional array.
getArrayDimensions(Class<?>) - Static method in class weka.core.Utils: Returns the dimensions of the given array.
getArrayDimensions(Object) - Static method in class weka.core.Utils: Returns the dimensions of the given array.
getASCrossvalidationFolds() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default number of folds of the CV in the attribute selection panel.
getASEvaluator() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default attribute evalautor (fully configured) for the attribute selection panel.
getAsInstance(Instances, Random) - Method in class weka.core.AlgVector: Gets the elements of the vector as an instance.
getASRandomSeed() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default random seed value in the attribute selection panel.
getASSearch() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default attribute selection search scheme (fully configured) for the attribute selection panel.
getAssignments() - Method in class weka.clusterers.SimpleKMeans: Gets the assignments for each instance.
getAssociatedConnections() - Method in class weka.gui.beans.MetaBean
getAssociationModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the associationModel property.
getAssociationModelOrBaselineModelOrClusteringModels() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the associationModelOrBaselineModelOrClusteringModel property.
getAssociationRules() - Method in class weka.associations.Apriori
getAssociationRules() - Method in interface weka.associations.AssociationRulesProducer: Gets the list of mined association rules.
getAssociationRules() - Method in class weka.associations.FilteredAssociator: Gets the list of mined association rules.
getAssociationRules() - Method in class weka.associations.FPGrowth: Gets the list of mined association rules.
getAssociator() - Method in class weka.associations.CheckAssociator: Get the associator being tested
getAssociator() - Method in class weka.associations.SingleAssociatorEnhancer: Get the associator used as the base associator.
getAssociator() - Method in class weka.gui.beans.Associator: Get the associator currently set for this wrapper
getAssociator() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default associator (fully configured) for the associations panel.
getAssociator() - Method in class weka.knowledgeflow.steps.Associator: Get the associator to use.
getASTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default attribute selection test mode for the attribute selection panel.
getAsText() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getAsText() - Method in class weka.gui.ColorEditor: Not representable as a string
getAsText() - Method in class weka.gui.CostMatrixEditor: Some objects can be represented as text, but a cost matrix cannot.
getAsText() - Method in class weka.gui.EnvironmentField
getAsText() - Method in class weka.gui.GenericArrayEditor: Returns null as we don't support getting/setting values as text.
getAsText() - Method in class weka.gui.GenericObjectEditor: Returns null as we don't support getting/setting values as text.
getAsText() - Method in class weka.gui.PasswordField
getAsText() - Method in class weka.gui.RangeEditor: Gets the current value as text.
getAsText() - Method in class weka.gui.SelectedTagEditor: Gets the current value as text.
getAsText() - Method in class weka.gui.SimpleDateFormatEditor: Returns the date format string.
getAttList_Irr() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the array that defines which of the attributes are seen to be irrelevant.
getAttr() - Method in class weka.classifiers.rules.JRip.Antd
getAttribute() - Method in class weka.associations.Item: Get the attribute that this item originates from.
getAttribute() - Method in class weka.core.pmml.jaxbbindings.Characteristic: Gets the value of the attribute property.
getAttribute() - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Get the name or index of the attribute to sort on
getAttribute1() - Method in class weka.gui.visualize.VisualizePanelEvent
getAttribute2() - Method in class weka.gui.visualize.VisualizePanelEvent
getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the attribute at the given index, can be NULL if not an attribute column
getAttributeAt(int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the attribute at the given index, can be NULL if not an attribute column
getAttributeCapabilities() - Method in class weka.core.Capabilities: returns all attribute capabilities
getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the column of the given attribute name, -1 if not found
getAttributeColumn(String) - Method in class weka.gui.arffviewer.ArffTableModel: returns the column of the given attribute name, -1 if not found
getAttributeID() - Method in class weka.experiment.ClassifierSplitEvaluator: Get the index of Attibute Identifying the instances
getAttributeIndex() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns the index of the attribute used in the regression.
getAttributeIndex() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Returns the index of the attribute used in the regression.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.Add: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.AddNoise: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.AddValues: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Gets the index of the attribute converted.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Get the index of the attribute used.
getAttributeIndex() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Get the index of the attribute used.
getAttributeIndex(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: Returns the attribute index for the given column index.
getAttributeIndex(int) - Method in class weka.gui.arffviewer.ArffTableModel: Returns the attribute index for the given column index.
getAttributeIndexes() - Method in class weka.filters.unsupervised.attribute.NominalToString: Get the index of the attribute used.
getAttributeIndices() - Method in class weka.core.AttributeLocator: Returns the indices of the attributes.
getAttributeIndices() - Method in class weka.core.converters.DictionarySaver: Gets the current range selection.
getAttributeIndices() - Method in class weka.core.DictionaryBuilder: Gets the current range selection.
getAttributeIndices() - Method in interface weka.core.DistanceFunction: Gets the range of attributes used in the calculation of the distance.
getAttributeIndices() - Method in class weka.core.FilteredDistance: Gets the range of attributes used in the calculation of the distance.
getAttributeIndices() - Method in class weka.core.NormalizableDistance: Gets the range of attributes used in the calculation of the distance.
getAttributeIndices() - Method in class weka.filters.supervised.attribute.Discretize: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Get the current range selection.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Copy: Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets the current range selection.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Get the current range selection.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Gets the selection of the columns, e.g., first-last or first-3,5-last
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Remove: Get the current range selection.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Gets the current range selection.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.Reorder: Get the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Gets the current range selection
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.SortLabels: Gets the current selected attributes.
getAttributeIndices() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets the current range selection.
getAttributeName() - Method in class weka.filters.unsupervised.attribute.Add: Get the name of the attribute to be created.
getAttributeName() - Method in class weka.filters.unsupervised.attribute.AddID: Get the name of the attribute to be created
getAttributeNamePrefix() - Method in class weka.core.DictionaryBuilder: Get the attribute name prefix.
getAttributeNamePrefix() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Get the attribute name prefix.
getAttributeNamePrefix() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Get the attribute name prefix.
getAttributeRange() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Get the range of indices of the attributes used.
getAttributes() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the range of attributes to output.
getAttributes() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getAttributes() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Get the list of attributes to consider for replacing missing values
getAttributes() - Method in class weka.gui.arffviewer.ArffPanel: returns a list with the attributes
getAttributeSelectionMethod() - Method in class weka.classifiers.functions.LinearRegression: Gets the method used to select attributes for use in the linear regression.
getAttributeSpecs() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Get the list of attribute specs to use to create the new attributes.
getAttributesToOperateOn() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Get the attributes to operate on
getAttributeType() - Method in class weka.filters.unsupervised.attribute.Add: Gets the type of attribute to generate.
getAttributeType() - Method in class weka.filters.unsupervised.attribute.RemoveType: Gets the attribute type to be deleted by the filter.
getAttrIndexRange() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: returns the attribute range(s).
getAttrValue() - Method in class weka.classifiers.rules.JRip.Antd
getAttsToApplyTo() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get the attributes to apply the rule to
getAttsToApplyTo() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Get the attributes to apply the rule to
getAutoBuild() - Method in class weka.classifiers.functions.MultilayerPerceptron
getAutoKeyGeneration() - Method in class weka.core.converters.DatabaseSaver: Gets whether or not a primary key will be generated automatically.
getAvailableCompatiblePackages() - Static method in class weka.core.WekaPackageManager: Get a list of the most recent version of all available packages (i.e.
getAvailableLookAndFeelClasses() - Static method in class weka.gui.LookAndFeel: Get a list of fully qualified class names of available look and feels
getAvailablePackages() - Method in class weka.core.packageManagement.DefaultPackageManager: Get a list of packages that are not currently installed.
getAvailablePackages() - Method in class weka.core.packageManagement.PackageManager: Get a list of packages that are not currently installed.
getAvailablePackages() - Static method in class weka.core.WekaPackageManager: Get a list of all available packages (i.e.
getAverage(int) - Method in class weka.experiment.ResultMatrix: returns the average of the mean at the given position, if the position is valid, otherwise 0.
getAverageDocLength() - Method in class weka.core.DictionaryBuilder: Get the average document length to use when normalizing
getAverageInstancesPerSecond() - Method in class weka.gui.beans.StreamThroughput: Get the average instances per second
getAvgNumberOfItemsPerTA() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the avgNumberOfItemsPerTA property.
getAvgNumberOfItemsPerTransaction() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the avgNumberOfItemsPerTransaction property.
getAvgNumberOfTAsPerTAGroup() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the avgNumberOfTAsPerTAGroup property.
getBackground() - Method in class weka.gui.visualize.BMPWriter: returns the current background color.
getBackground() - Method in class weka.gui.visualize.JPEGWriter: returns the current background color.
getBackground() - Method in class weka.gui.visualize.PNGWriter: returns the current background color.
getBackground() - Method in class weka.gui.visualize.PostscriptGraphics
getBackgroundColor() - Method in class weka.gui.scripting.SyntaxDocument: Returns the background color.
getBackup() - Method in class weka.gui.GenericObjectEditor: Returns the backup object (may be null if there is no backup.
getBagSizePercent() - Method in class weka.classifiers.meta.Bagging: Gets the size of each bag, as a percentage of the training set size.
getBalanceClass() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Gets whether the class is balanced.
getBallSplitter() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns the BallSplitter algorithm set that would be used by the TopDown BallTree constructor.
getBallTreeConstructor() - Method in class weka.core.neighboursearch.BallTree: Returns the BallTreeConstructor currently in use.
getBase() - Method in class weka.core.neighboursearch.CoverTree: Returns the base in use for expansion constant.
getBaseExperiment() - Method in class weka.experiment.RemoteExperiment: Get the base experiment used by this remote experiment
getBaseForSampling() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the base for sampling
getBaseline() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the baseline property.
getBaselineCell() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables: Gets the value of the baselineCell property.
getBaselineCell() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Gets the value of the baselineCell property.
getBaselineMethod() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the baselineMethod property.
getBaselineModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the baselineModel property.
getBaselineScore() - Method in class weka.core.pmml.jaxbbindings.Characteristic: Gets the value of the baselineScore property.
getBaselineScore() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the baselineScore property.
getBaselineStrataVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the baselineStrataVariable property.
getBaselineStratum() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables: Gets the value of the baselineStratum property.
getBaseSystemDependency() - Method in class weka.core.packageManagement.DefaultPackage: Gets the dependency on the base system that this package requires.
getBaseSystemDependency() - Method in class weka.core.packageManagement.Package: Gets the dependency on the base system that this package requires.
getBaseSystemName() - Method in class weka.core.packageManagement.PackageManager: Get the name of the main software system for which we manage packages.
getBaseSystemVersion() - Method in class weka.core.packageManagement.PackageManager: Get the current installed version of the main system for which we manage packages.
getBatchSize() - Method in class weka.classifiers.AbstractClassifier: Get the preferred batch size for batch prediction.
getBatchSize() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in class weka.classifiers.meta.Bagging: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in class weka.classifiers.meta.FilteredClassifier: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in class weka.classifiers.meta.RandomCommittee: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in class weka.classifiers.meta.RandomSubSpace: Gets the preferred batch size from the base learner if it implements BatchPredictor.
getBatchSize() - Method in interface weka.core.BatchPredictor: Get the batch size to use.
getBayesInput() - Method in class weka.core.pmml.jaxbbindings.BayesInputs: Gets the value of the bayesInput property.
getBean() - Method in class weka.gui.beans.BeanInstance: Gets the bean encapsulated in this instance
getBeanContext() - Method in class weka.gui.beans.AbstractDataSource: Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.CostBenefitAnalysis
getBeanContext() - Method in class weka.gui.beans.DataVisualizer: Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.GraphViewer: Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.ModelPerformanceChart: Return the bean context (if any) that this bean is embedded in
getBeanContext() - Method in class weka.gui.beans.TextViewer: Return the bean context (if any) that this bean is embedded in
getBeanDescriptor() - Method in class weka.filters.unsupervised.attribute.AddUserFieldsBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.AssociatorBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.AttributeSummarizerBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ClassAssignerBeanInfo
getBeanDescriptor() - Method in class weka.gui.beans.ClassifierBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ClassValuePickerBeanInfo
getBeanDescriptor() - Method in class weka.gui.beans.ClustererBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo: Return the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.DataVisualizerBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.FilterBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.FlowByExpressionBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ImageSaverBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo: Return the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.JoinBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.LoaderBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.ModelPerformanceChartBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.NoteBeanInfo
getBeanDescriptor() - Method in class weka.gui.beans.PredictionAppenderBeanInfo: Return the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SaverBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SerializedModelSaverBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SorterBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.StripChartBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SubstringLabelerBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.SubstringReplacerBeanInfo: Get the bean descriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.TextSaverBeanInfo: Get BeanDescriptor for this bean
getBeanDescriptor() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo: Get the bean descriptor for this bean
getBeanInfoInputs() - Method in class weka.gui.beans.MetaBean
getBeanInfoOutputs() - Method in class weka.gui.beans.MetaBean
getBeanInfoSubFlow() - Method in class weka.gui.beans.MetaBean
getBeanInstances(Integer...) - Static method in class weka.gui.beans.BeanInstance: Return the list of displayed beans
getBeanLayout(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getBeansInInputs() - Method in class weka.gui.beans.MetaBean: Return all the beans in the inputs
getBeansInOutputs() - Method in class weka.gui.beans.MetaBean: Return all the beans in the outputs
getBeansInSubFlow() - Method in class weka.gui.beans.MetaBean: Return all the beans in the sub flow
getBestClassifierIndex() - Method in class weka.classifiers.meta.MultiScheme: Get the index of the classifier that was determined as best during cross-validation.
getBestClassifierOptions() - Method in class weka.classifiers.meta.CVParameterSelection: Returns (a copy of) the best options found for the classifier.
getBestFit() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the value of the bestFit property.
getBeta() - Method in class weka.core.pmml.jaxbbindings.PCell: Gets the value of the beta property.
getBias() - Method in class weka.classifiers.BVDecompose: Get the calculated bias squared
getBias() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the bias property.
getBiasToUniformClass() - Method in class weka.filters.supervised.instance.Resample: Gets the bias towards a uniform class.
getBIC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the bic property.
getBIFFile() - Method in class weka.classifiers.bayes.BayesNet: Get name of network in BIF file to compare with
getBIFFile() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Get name of network in BIF file to read structure from
getBIFHeader() - Method in class weka.classifiers.bayes.BayesNet
getBinarizeNumericAttributes() - Method in class weka.attributeSelection.InfoGainAttributeEval: get whether numeric attributes are just being binarized.
getBinaryAttributesNominal() - Method in class weka.filters.supervised.attribute.NominalToBinary: Gets if binary attributes are to be treated as nominal ones.
getBinaryAttributesNominal() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Gets if binary attributes are to be treated as nominal ones.
getBinarySimilarity() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the binarySimilarity property.
getBinarySplits() - Method in class weka.classifiers.rules.PART: Get the value of binarySplits.
getBinarySplits() - Method in class weka.classifiers.trees.J48: Get the value of binarySplits.
getBinRangePrecision() - Method in class weka.filters.supervised.attribute.Discretize: Get the precision for bin boundaries.
getBinRangePrecision() - Method in class weka.filters.unsupervised.attribute.Discretize: Get the precision for bin boundaries.
getBinRangesString(int) - Method in class weka.filters.supervised.attribute.Discretize: Gets the bin ranges string for an attribute
getBinRangesString(int) - Method in class weka.filters.unsupervised.attribute.Discretize: Gets the bin ranges string for an attribute
getBins() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets the number of bins numeric attributes will be divided into
getBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Ignored
getBinValue() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin: Gets the value of the binValue property.
getBlockEnd() - Method in class weka.gui.scripting.SyntaxDocument: Returns the end of a block.
getBlockOnLastFold() - Method in class weka.gui.beans.Classifier: Gets whether we are blocking on the last fold of the last run rather than rejecting any further data until all processing has been completed.
getBlockStart() - Method in class weka.gui.scripting.SyntaxDocument: Returns the start of a block.
getBooleanCols() - Method in class weka.datagenerators.clusterers.SubspaceCluster: returns the range of boolean attributes.
getBooleanOperator() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate: Gets the value of the booleanOperator property.
getBooleanOperator() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Gets the value of the booleanOperator property.
getBorderInsets(Component) - Method in class weka.gui.beans.ShadowBorder: Returns a new Insets instance where the top and left are 1, the bottom and right fields are the border width + 1.
getBorderInsets(Component, Insets) - Method in class weka.gui.beans.ShadowBorder: Reinitializes the insets parameter with this ShadowBorder's current Insets.
getBorderInsets(Component) - Method in class weka.gui.knowledgeflow.ShadowBorder: Returns a new Insets instance where the top and left are 1, the bottom and right fields are the border width + 1.
getBorderInsets(Component, Insets) - Method in class weka.gui.knowledgeflow.ShadowBorder: Reinitialies the insets parameter with this ShadowBorder's current Insets.
getBoundaryValueMeans() - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Gets the value of the boundaryValueMeans property.
getBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Gets the value of the boundaryValues property.
getBoundaryValues() - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Gets the value of the boundaryValues property.
getBreakTiesRandomly() - Method in class weka.classifiers.trees.RandomForest: Get whether to break ties randomly.
getBreakTiesRandomly() - Method in class weka.classifiers.trees.RandomTree: Get whether to break ties randomly.
getBuffer() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the current buffer.
getBufferSize() - Method in class weka.core.converters.CSVLoader: Get the buffer size to use - i.e.
getBufferSize() - Method in class weka.gui.beans.Sorter: Get the size of the in-memory buffer
getBufferSize() - Method in class weka.knowledgeflow.steps.Sorter: Get the size of the in-memory buffer
getBuildCalibrationModels() - Method in class weka.classifiers.functions.SMO: Get the value of buildCalibrationModels.
getBuilder() - Method in class weka.core.xml.XMLDocument: returns the DocumentBuilder.
getBuildRegressionTree() - Method in class weka.classifiers.trees.m5.M5Base: Get the value of regressionTree.
getBuiltInMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper: Get a list of built-in metric names
getBuiltinTemplateDescriptions() - Method in class weka.gui.knowledgeflow.TemplateManager: Get descriptions for the built-in knowledge flow templates
getBuiltinTemplateFlow(String) - Method in class weka.gui.knowledgeflow.TemplateManager: Get the built-in template flow corresponding to the description
getBusinessProblem() - Method in class weka.core.pmml.jaxbbindings.Decisions: Gets the value of the businessProblem property.
getC() - Method in class weka.classifiers.functions.SMO: Get the value of C.
getC() - Method in class weka.classifiers.functions.SMOreg: Get the value of C.
getC00Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the c00Parameter property.
getC01Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the c01Parameter property.
getC10Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the c10Parameter property.
getC11Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the c11Parameter property.
getCacheHits() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: return the number of kernel cache hits
getCacheKeyName() - Method in class weka.experiment.DatabaseResultListener: Get the value of CacheKeyName.
getCacheSize() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Gets the size of the cache
getCacheSize() - Method in class weka.classifiers.functions.supportVector.StringKernel: Gets the size of the cache
getCacheValues(double) - Method in class weka.classifiers.lazy.kstar.KStarCache: Returns the values in the cache mapped by the specified key
getCalcOutOfBag() - Method in class weka.classifiers.meta.Bagging: Get whether the out of bag error is calculated.
getCalculatedNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise: Gets the calculated number of attributes to retain.
getCalculatedNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch: Gets the calculated number of attributes to retain.
getCalculatedNumToSelect() - Method in class weka.attributeSelection.Ranker: Gets the calculated number to select.
getCalculateStdDevs() - Method in class weka.experiment.AveragingResultProducer: Get the value of CalculateStdDevs.
getCalibrator() - Method in class weka.classifiers.functions.SMO: Returns the calibrator to use
getCanChangeClassInDialog() - Method in class weka.gui.GenericObjectEditor: Returns whether the user can change the class in the dialog.
getCanopies() - Method in class weka.clusterers.Canopy: Get the canopies (cluster centers).
getCanopyMaxNumCanopiesToHoldInMemory() - Method in class weka.clusterers.SimpleKMeans: Get the maximum number of candidate canopies to retain in memory during training.
getCanopyMinimumCanopyDensity() - Method in class weka.clusterers.SimpleKMeans: Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.
getCanopyPeriodicPruningRate() - Method in class weka.clusterers.SimpleKMeans: Get the how often to prune low density canopies during training (if using canopy clustering)
getCanopyT1() - Method in class weka.clusterers.SimpleKMeans: Get the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
getCanopyT2() - Method in class weka.clusterers.SimpleKMeans: Get the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
getCapabilities() - Method in class weka.associations.AbstractAssociator: Returns the Capabilities of this associator.
getCapabilities() - Method in class weka.associations.Apriori: Returns default capabilities of the classifier.
getCapabilities() - Method in interface weka.associations.Associator: Returns the Capabilities of this associator.
getCapabilities() - Method in class weka.associations.FilteredAssociator: Returns default capabilities of the associator.
getCapabilities() - Method in class weka.associations.FPGrowth: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.associations.SingleAssociatorEnhancer: Returns default capabilities of the base associator.
getCapabilities() - Method in class weka.attributeSelection.ASEvaluation: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.CorrelationAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.GainRatioAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.OneRAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.PrincipalComponents: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.classifiers.AbstractClassifier: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.bayes.BayesNet: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayes: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns default capabilities of the classifier.
getCapabilities() - Method in interface weka.classifiers.Classifier: Returns the Capabilities of this classifier.
getCapabilities() - Method in class weka.classifiers.functions.GaussianProcesses: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.LinearRegression: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.Logistic: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.MultilayerPerceptron: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SGD: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SGDText: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SimpleLogistic: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SMO: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.SMOreg: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.Puk: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.RBFKernel: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the Capabilities of this kernel.
getCapabilities() - Method in class weka.classifiers.functions.VotedPerceptron: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.lazy.IBk: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.lazy.KStar: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.lazy.LWL: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AdaBoostM1: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AdditiveRegression: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.CVParameterSelection: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.FilteredClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.meta.LogitBoost: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.MultiClassClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.meta.Stacking: Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
getCapabilities() - Method in class weka.classifiers.meta.Vote: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.misc.SerializedClassifier: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.MultipleClassifiersCombiner: Returns combined capabilities of the base classifiers, i.e., the capabilities all of them have in common.
getCapabilities() - Method in class weka.classifiers.rules.DecisionTable: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.rules.JRip: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.rules.OneR: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.rules.PART: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.rules.ZeroR: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.SingleClassifierEnhancer: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.trees.DecisionStump: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.HoeffdingTree: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns default capabilities of the classifier tree.
getCapabilities() - Method in class weka.classifiers.trees.J48: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.LMT: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.m5.M5Base: Returns default capabilities of the classifier, i.e., of LinearRegression.
getCapabilities() - Method in class weka.classifiers.trees.RandomForest: Returns default capabilities of the base classifier.
getCapabilities() - Method in class weka.classifiers.trees.RandomTree: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.classifiers.trees.REPTree: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.clusterers.AbstractClusterer: Returns the Capabilities of this clusterer.
getCapabilities() - Method in class weka.clusterers.Canopy: Returns default capabilities of the clusterer.
getCapabilities() - Method in interface weka.clusterers.Clusterer: Returns the Capabilities of this clusterer.
getCapabilities() - Method in class weka.clusterers.Cobweb: Returns default capabilities of the clusterer.
getCapabilities() - Method in class weka.clusterers.EM: Returns default capabilities of the clusterer (i.e., the ones of SimpleKMeans).
getCapabilities() - Method in class weka.clusterers.FarthestFirst: Returns default capabilities of the clusterer.
getCapabilities() - Method in class weka.clusterers.FilteredClusterer: Returns default capabilities of the clusterer.
getCapabilities() - Method in class weka.clusterers.HierarchicalClusterer
getCapabilities() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns default capabilities of the clusterer (i.e., of the wrapper clusterer).
getCapabilities() - Method in class weka.clusterers.SimpleKMeans: Returns default capabilities of the clusterer.
getCapabilities() - Method in class weka.clusterers.SingleClustererEnhancer: Returns default capabilities of the clusterer.
getCapabilities() - Method in interface weka.core.CapabilitiesHandler: Returns the capabilities of this object.
getCapabilities() - Method in class weka.core.converters.AbstractSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.ArffSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.C45Saver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.CSVSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.DatabaseSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.DictionarySaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.JSONSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.LibSVMSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.MatlabSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.SerializedInstancesSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.SVMLightSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.converters.XRFFSaver: Returns the Capabilities of this saver.
getCapabilities() - Method in class weka.core.FindWithCapabilities: The capabilities to search for.
getCapabilities() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.estimators.DiscreteEstimator: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.estimators.Estimator: Returns the Capabilities of this Estimator.
getCapabilities() - Method in class weka.estimators.KernelEstimator: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.estimators.MahalanobisEstimator: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.estimators.NormalEstimator: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.estimators.PoissonEstimator: Returns default capabilities of the classifier.
getCapabilities() - Method in class weka.filters.AllFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.Filter: Returns the Capabilities of this filter.
getCapabilities(Instances) - Method in class weka.filters.Filter: Returns the Capabilities of this filter, customized based on the data.
getCapabilities() - Method in class weka.filters.MultiFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.RenameRelation: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.Discretize: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.attribute.PartitionMembership: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.instance.ClassBalancer: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.instance.Resample: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Add: Returns the Capabilities of this filter.
getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Center: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns the Capabilities of this filter.
getCapabilities(Instances) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns the Capabilities of this filter, makes sure that the class is never set (for the clusterer).
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Obfuscate: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the capabilities of this evaluator.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
getCapabilities() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Standardize: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.SwapValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.attribute.Transpose: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.Randomize: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.Resample: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the Capabilities of this filter.
getCapabilities() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: returns the currently selected capabilities.
getCapabilitiesFilter() - Method in class weka.gui.ConverterFileChooser: returns the capabilities filter for the savers, can be null if all are listed.
getCapabilitiesFilter() - Method in class weka.gui.GenericObjectEditor: Returns the current Capabilities filter, can be null.
getCar() - Method in class weka.associations.Apriori: Gets whether class association ruels are mined
getCardinality(int) - Method in class weka.classifiers.bayes.BayesNet: get number of values a node can take
getCardinality() - Method in class weka.core.pmml.jaxbbindings.Counts: Gets the value of the cardinality property.
getCardinality() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the cardinality of the attributes (incl class attribute)
getCardinalityOfParents() - Method in class weka.classifiers.bayes.net.ParentSet: returns cardinality of parents
getCaseSensitive() - Method in class weka.gui.scripting.SyntaxDocument: Returns whether blanks are used instead of tabs.
getCastInteger() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the castInteger property.
getCategoricalPredictor() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the categoricalPredictor property.
getCategoricalScoringMethod() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the categoricalScoringMethod property.
getCategories() - Method in class weka.core.pmml.jaxbbindings.Predictor: Gets the value of the categories property.
getCategory() - Method in class weka.core.pmml.jaxbbindings.Categories: Gets the value of the category property.
getCategory() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the category property.
getCell(int, int) - Method in class weka.classifiers.CostMatrix: Return the contents of a particular cell.
getCellEditor(int, int) - Method in class weka.gui.arffviewer.ArffTable: returns the cell editor for the given cell
getCells() - Method in class weka.gui.sql.ResultSetHelper: returns an 2-dimensional array with the content of the resultset, the first dimension is the row, the second the column (i.e., getCells()[y][x]).
getCenter() - Method in class weka.gui.treevisualizer.Node: Get the value of center.
getCenterData() - Method in class weka.attributeSelection.PrincipalComponents: Get whether to center (rather than standardize) the data.
getCenterData() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Get whether to center (rather than standardize) the data.
getChangeInWeights() - Method in class weka.classifiers.functions.neural.NeuralNode: call this function to get the chnage in weights array.
getChar() - Method in class weka.core.Trie.TrieNode: returns the stored character
getCharacteristic() - Method in class weka.core.pmml.jaxbbindings.Characteristics: Gets the value of the characteristic property.
getCharSet() - Method in class weka.core.converters.TextDirectoryLoader: Get the character set to use when reading text files.
getChartingEvalWindowSize() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Get whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).
getChartingEvalWindowSize() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Get whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).
getChebychev() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the chebychev property.
getChecked(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: returns the checked state of the element at the given index
getChecked(int) - Method in class weka.gui.CheckBoxList: returns the checked state of the element at the given index
getCheckedIndices() - Method in class weka.gui.CheckBoxList: returns an array with the indices of all checked items
getCheckErrorRate() - Method in class weka.classifiers.rules.JRip: Gets whether to check for error rate is in stopping criterion
getChecksTurnedOff() - Method in class weka.classifiers.functions.SMO: Returns whether the checks are turned off or not.
getChecksTurnedOff() - Method in class weka.classifiers.functions.supportVector.Kernel
getChecksTurnedOff() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns whether the checks are turned off or not.
getChild(String) - Method in class weka.core.json.JSONNode: Returns the child with the given name.
getChild(Object, int) - Method in class weka.gui.knowledgeflow.InvisibleTreeModel
getChild(int) - Method in class weka.gui.treevisualizer.Node: Get the Edge for the child number 'i'.
getChildAt(int, boolean) - Method in class weka.gui.knowledgeflow.InvisibleNode: Get a child node
getChildCount(boolean) - Method in class weka.gui.knowledgeflow.InvisibleNode: Get the number of children nodes
getChildCount(Object) - Method in class weka.gui.knowledgeflow.InvisibleTreeModel
getChildField() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the childField property.
getChildParent() - Method in class weka.core.pmml.jaxbbindings.Taxonomy: Gets the value of the childParent property.
getChildren(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: return list of children of a node
getChildTags(Node) - Static method in class weka.core.xml.XMLDocument: returns all non tag-children from the given node.
getChildTags(Node, String) - Static method in class weka.core.xml.XMLDocument: returns all non tag-children from the given node.
getChiSquareValue() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the chiSquareValue property.
getChooseClassPopupMenu() - Method in class weka.gui.GenericObjectEditor: Returns a popup menu that allows the user to change the class of object.
getCindex() - Method in class weka.gui.visualize.PlotData2D: Get the currently set colouring index of the data
getCIndex() - Method in class weka.gui.visualize.VisualizePanel: Get the index of the attribute selected for coloring
getCityBlock() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the cityBlock property.
getClassAttribute() - Method in class weka.gui.beans.ThresholdDataEvent: Return the class attribute for which the threshold data was generated for.
getClassCapabilities() - Method in class weka.core.Capabilities: returns all class capabilities
getClassColumn() - Method in class weka.gui.beans.ClassAssigner
getClassColumn() - Method in class weka.knowledgeflow.steps.ClassAssigner: Get the class column to use
getClassCounts() - Method in class weka.filters.supervised.attribute.ClassOrder: Get the class distribution of the sorted class values.
getClassEstimator() - Method in class weka.classifiers.bayes.NaiveBayes: Get the class estimator.
getClassesToClusters() - Method in class weka.clusterers.ClusterEvaluation: Return the array (ordered by cluster number) of minimum error class to cluster mappings
getClassFlag() - Method in class weka.datagenerators.ClusterGenerator: Gets the class flag.
getClassForIRStatistics() - Method in class weka.experiment.ClassifierSplitEvaluator: Get the value of ClassForIRStatistics.
getClassificationMethod() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the classificationMethod property.
getClassificationOutputFormatter() - Method in class weka.gui.explorer.ClassifierPanel: Get the formatter for classifcation output
getClassifier() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the classifier used as the base learner.
getClassifier() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get the classifier used as the base learner.
getClassifier() - Method in class weka.attributeSelection.WrapperSubsetEval: Get the classifier used as the base learner.
getClassifier() - Method in class weka.classifiers.BVDecompose: Gets the name of the classifier being analysed
getClassifier() - Method in class weka.classifiers.BVDecomposeSegCVSub: Gets the name of the classifier being analysed
getClassifier() - Method in class weka.classifiers.CheckClassifier: Get the classifier used as the classifier
getClassifier() - Method in class weka.classifiers.CheckSource: Gets the classifier being used for the tests, can be null.
getClassifier(int) - Method in class weka.classifiers.meta.MultiScheme: Gets a single classifier from the set of available classifiers.
getClassifier(int) - Method in class weka.classifiers.MultipleClassifiersCombiner: Gets a single classifier from the set of available classifiers.
getClassifier() - Method in class weka.classifiers.SingleClassifierEnhancer: Get the classifier used as the base learner.
getClassifier() - Method in class weka.experiment.ClassifierSplitEvaluator: Get the value of Classifier.
getClassifier() - Method in class weka.experiment.RegressionSplitEvaluator: Get the value of Classifier.
getClassifier() - Method in class weka.filters.supervised.attribute.AddClassification: Gets the classifier used by the filter.
getClassifier() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the classifier used by the filter.
getClassifier() - Method in class weka.gui.beans.BatchClassifierEvent: Get the classifier
getClassifier() - Method in class weka.gui.beans.Classifier: Get the currently trained classifier.
getClassifier() - Method in class weka.gui.beans.IncrementalClassifierEvent: Get the classifier
getClassifier() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Returns the currently set classifier.
getClassifier() - Method in class weka.gui.explorer.ClassifierPanel: Get the currently configured classifier from the GenericObjectEditor
getClassifier() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default classifier (fully configured) for the classify panel.
getClassifier() - Method in class weka.knowledgeflow.steps.Classifier: Get the classifier to train
getClassifierCollectPredictionsForEvaluation() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the predictions of the classifier are collected for calculating performance statistics such as AUROC.
getClassifierCostSensitiveEval() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the evaluation of the classifier is done cost-sensitively.
getClassifierCrossvalidationFolds() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default number of folds of the CV in the classify panel.
getClassifierErrorsMaximumPlotSizeNumeric() - Static method in class weka.gui.explorer.ExplorerDefaults: Returns the maximum size in pixels for plots of plotting classifier errors of numeric attributes.
getClassifierErrorsMinimumPlotSizeNumeric() - Static method in class weka.gui.explorer.ExplorerDefaults: Returns the minimum size in pixels for plots of plotting classifier errors of numeric attributes.
getClassifierErrorsPlotInstances() - Static method in class weka.gui.explorer.ExplorerDefaults: Returns an instance of the class used for generating plot instances for displaying the classifier errors.
getClassifierOutputAdditionalAttributes() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the string with the additional indices to output alongside the predictions.
getClassifierOutputConfusionMatrix() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the confusion matrix for the classifier is output.
getClassifierOutputEntropyEvalMeasures() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether entropy-based evaluation meastures of the classifier are output.
getClassifierOutputModel() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the built model is output.
getClassifierOutputModelsForTrainingSplits() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the models built for the training set are output
getClassifierOutputPerClassStats() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether additional per-class stats of the classifier are output.
getClassifierOutputPredictions() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the predictions of the classifier are output as well.
getClassifierOutputSourceCode() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the source of a sourcable Classifier is output in the classify tab.
getClassifierPercentageSplit() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default classifier test mode for the classify panel (0-99).
getClassifierPreserveOrder() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the order is preserved in case of the percentage split in the classify tab.
getClassifierRandomSeed() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default random seed value for the classifier for the classify panel.
getClassifiers() - Method in class weka.classifiers.meta.MultiScheme: Gets the list of possible classifers to choose from.
getClassifiers() - Method in class weka.classifiers.MultipleClassifiersCombiner: Gets the list of possible classifers to choose from.
getClassifierSourceCodeClass() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default classname for a sourcable Classifier in the classify tab.
getClassifierStoreTestDataAndPredictionsForVis() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the test data and the predictions of the classifier are stored for visualization.
getClassifierTemplate() - Method in class weka.gui.beans.Classifier: Return the classifier template currently in use.
getClassifierTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default classifier test mode for the classify panel.
getClassifyIterations() - Method in class weka.classifiers.BVDecomposeSegCVSub: Gets the number of times an instance is classified
getClassIndex() - Method in class weka.associations.Apriori: Gets the class index
getClassIndex() - Method in class weka.associations.FilteredAssociator: Gets the class index
getClassIndex() - Method in class weka.classifiers.BVDecompose: Get the index (starting from 1) of the attribute used as the class.
getClassIndex() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the index (starting from 1) of the attribute used as the class.
getClassIndex() - Method in class weka.classifiers.CheckSource: Gets the class index of the dataset.
getClassIndex() - Method in class weka.core.converters.JSONSaver: Get the index of the class attribute.
getClassIndex() - Method in class weka.core.converters.LibSVMSaver: Get the index of the class attribute.
getClassIndex() - Method in class weka.core.converters.SVMLightSaver: Get the index of the class attribute.
getClassIndex() - Method in class weka.core.converters.XRFFSaver: Get the index of the class attribute.
getClassIndex() - Method in class weka.core.FindWithCapabilities: returns the current current class index, -1 if no class attribute.
getClassIndex() - Method in class weka.core.TestInstances: returns the current class index (0-based), -1 is last attribute
getClassIndex() - Method in class weka.filters.CheckSource: Gets the class index of the dataset.
getClassIndex() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: returns the class index.
getClassIndex() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the attribute on which misclassifications are based.
getClassIndex() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Returns the 0-based class index.
getClassIndex() - Method in class weka.gui.SetInstancesPanel: Returns the currently selected class index.
getClassLabels() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix: Gets the value of the classLabels property.
getClassLoader() - Method in class weka.core.scripting.Groovy: returns the currently used Groovy classloader.
getClassMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns all the class/package matches with the partial search string.
getClassname() - Method in class weka.core.Javadoc: returns the current classname
getClassname() - Method in class weka.core.ListOptions: returns the current classname
getClassName() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Get the class containing the transformation method.
getClassname(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns the classname part of the partial classname.
getClassnames(String) - Method in class weka.core.ClassCache: Returns all the classes for the given package.
getClassOrder() - Method in class weka.filters.supervised.attribute.ClassOrder: Get the wanted class order
getClassPriors() - Method in class weka.classifiers.evaluation.Evaluation: Get the current weighted class counts.
getClassPriors() - Method in class weka.classifiers.Evaluation: Get the current weighted class counts.
getClassType() - Method in class weka.core.TestInstances: returns the current class type
getClassValue() - Method in class weka.gui.beans.ClassValuePicker: Gets the class value considered to be the "positive" class value.
getClassValue() - Method in class weka.knowledgeflow.steps.ClassValuePicker: Gets the class value considered to be the "positive" class value.
getClassValueIndex() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the class value index to use
getClassWeightedAverageStatistic(String) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric: Get the weighted (by class) average for this statistic.
getClearEachDataset() - Method in class weka.gui.streams.InstanceViewer
getClip() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
getClipBounds() - Method in class weka.gui.visualize.PostscriptGraphics: This returns the full current drawing area
getClipBounds(Rectangle) - Method in class weka.gui.visualize.PostscriptGraphics: This returns the full current drawing area
getClipRect() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
getClock() - Method in class weka.core.Debug: returns the instance of the Clock that is internally used
getClosestConnections(Point, int, Integer...) - Static method in class weka.gui.beans.BeanConnection: Return a list of connections within some delta of a point
getClosestConnectorPoint(Point) - Method in class weka.gui.beans.BeanVisual: Returns the coordinates of the closest "connector" point to the supplied point.
getClosestConnectorPoint(Point) - Method in class weka.gui.knowledgeflow.StepVisual: Returns the coordinates of the closest "connector" point to the supplied point.
getCloseTo() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the "close to" number.
getCloseToDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the "close to" default.
getCloseToTolerance() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the "close to" Tolerance.
getClosure() - Method in class weka.core.pmml.jaxbbindings.Interval: Gets the value of the closure property.
getClusterAssignments() - Method in class weka.clusterers.ClusterEvaluation: Return an array of cluster assignments corresponding to the most recent set of instances clustered.
getClusterCanopyAssignments() - Method in class weka.clusterers.Canopy: Get the canopies that each canopy (cluster center) is within T1 distance of
getClusterCentroids() - Method in class weka.clusterers.FarthestFirst: Get the centroids found by FarthestFirst
getClusterCentroids() - Method in class weka.clusterers.SimpleKMeans: Gets the the cluster centroids.
getClusterDefinitions() - Method in class weka.datagenerators.clusterers.SubspaceCluster: returns the currently set clusters
getClusterer() - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator: Get the clusterer
getClusterer() - Method in class weka.clusterers.CheckClusterer: Get the clusterer used as the clusterer
getClusterer() - Method in class weka.clusterers.MakeDensityBasedClusterer: Gets the clusterer being wrapped.
getClusterer() - Method in class weka.clusterers.SingleClustererEnhancer: Get the clusterer used as the base clusterer.
getClusterer() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Get the value of clusterer
getClusterer() - Method in class weka.filters.unsupervised.attribute.AddCluster: Gets the clusterer used by the filter.
getClusterer() - Method in class weka.gui.beans.BatchClustererEvent: Get the clusterer
getClusterer() - Method in class weka.gui.beans.Clusterer: Get the clusterer currently set for this wrapper
getClusterer() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: Returns the currently set clusterer.
getClusterer() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default clusterer (fully configured) for the clusterer panel.
getClusterer() - Method in class weka.knowledgeflow.steps.Clusterer: Get the clusterer to train
getClustererAssignmentsPlotInstances() - Static method in class weka.gui.explorer.ExplorerDefaults: Returns an instance of the class used for generating plot instances for displaying the cluster assignments.
getClustererStoreClustersForVis() - Static method in class weka.gui.explorer.ExplorerDefaults: returns whether the clusters are storeed for visualization purposes in the cluster panel.
getClustererTestMode() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default cluster test mode for the cluster panel.
getClusterEvaluation() - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: Returns the cluster evaluation object in use.
getClusteringModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the clusteringModel property.
getClusteringModelQuality() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation: Gets the value of the clusteringModelQuality property.
getClusterModelsNumericAtts() - Method in class weka.clusterers.EM: Return the normal distributions for the cluster models
getClusterNominalCounts() - Method in class weka.clusterers.SimpleKMeans: Returns for each cluster the weighted frequency counts for the values of each nominal attribute.
getClusterPriors() - Method in class weka.clusterers.EM: Return the priors for the clusters
getClusterSizes() - Method in class weka.clusterers.SimpleKMeans: Gets the sum of weights for all the instances in each cluster.
getClusterStandardDevs() - Method in class weka.clusterers.SimpleKMeans: Gets the standard deviations of the numeric attributes in each cluster.
getClusterSubType() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Gets the cluster sub type.
getClusterType() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Gets the cluster type.
getCoef0() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Gets the value of the coef0 property.
getCoef0() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Gets the value of the coef0 property.
getCoefficient() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Gets the value of the coefficient property.
getCoefficient() - Method in class weka.core.pmml.jaxbbindings.Coefficients: Gets the value of the coefficient property.
getCoefficient() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Gets the value of the coefficient property.
getCoefficient() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Gets the value of the coefficient property.
getCoefficients() - Method in class weka.core.matrix.LinearRegression: returns the calculated coefficients
getCoefficients() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the coefficients property.
getCol() - Method in class weka.core.pmml.jaxbbindings.MatCell: Gets the value of the col property.
getColCount() - Method in class weka.experiment.ResultMatrix: returns the number of columns.
getColHidden(int) - Method in class weka.experiment.ResultMatrix: returns the hidden status of the column, if the index is valid, otherwise false.
getCollapseTree() - Method in class weka.classifiers.trees.J48: Get the value of collapseTree.
getCollectPredictionsForVisAndAUC() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
getColName(int) - Method in class weka.experiment.ResultMatrix: returns the name of the row, if the index is valid, otherwise null.
getColNameWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the column names.
getColor() - Method in class weka.gui.ReaderToTextPane: Returns the color in use.
getColor() - Method in class weka.gui.treevisualizer.Node: Get the value of color.
getColor() - Method in class weka.gui.visualize.PostscriptGraphics: Get current pen color.
getColorBox() - Method in class weka.gui.AttributeVisualizationPanel: Returns the class selection combo box if the parent component wants to place it in itself or in some component other than this component.
getColOrder() - Method in class weka.experiment.ResultMatrix: returns the current order of the columns, null means the default order.
getColoringIndex() - Method in class weka.gui.AttributeVisualizationPanel: Get the coloring (class) index for the plot
getColoringIndex() - Method in class weka.gui.beans.AttributeSummarizer: Return the coloring index for the attribute summary plots
getColors() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Get the current vector of Color objects used for the classes
getColumn(int) - Method in class weka.core.Matrix: Deprecated.

Gets a column of the matrix and returns it as a double array.
getColumn() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair: Gets the value of the column property.
getColumn() - Method in class weka.core.pmml.jaxbbindings.InstanceField: Gets the value of the column property.
getColumn() - Method in class weka.core.pmml.jaxbbindings.VerificationField: Gets the value of the column property.
getColumn() - Static method in class weka.gui.experiment.ExperimenterDefaults: the comma-separated list of attribute names that identify a column.
getColumnClass(int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the most specific superclass for all the cell values in the column (always String)
getColumnClass(int) - Method in class weka.gui.InteractiveTableModel
getColumnClass(int) - Method in class weka.gui.SortedTableModel: Returns the most specific superclass for all the cell values in the column.
getColumnClass(int) - Method in class weka.gui.sql.ResultSetTableModel: returns the most specific superclass for all the cell values in the column (always String).
getColumnClasses() - Method in class weka.gui.sql.ResultSetHelper: returns the classes for the columns.
getColumnCount() - Method in class weka.gui.arffviewer.ArffTableModel: returns the number of columns in the model
getColumnCount() - Method in class weka.gui.InteractiveTableModel
getColumnCount() - Method in class weka.gui.SortedTableModel: Returns the number of columns in the model
getColumnCount() - Method in class weka.gui.sql.ResultSetHelper: returns the number of columns in the resultset.
getColumnCount() - Method in class weka.gui.sql.ResultSetTableModel: returns the number of columns in the model.
getColumnDimension() - Method in class weka.core.matrix.Matrix: Get column dimension.
getColumnName(int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the name of the column at columnIndex
getColumnName(int) - Method in class weka.gui.InteractiveTableModel
getColumnName(int) - Method in class weka.gui.SortedTableModel: Returns the name of the column at columnIndex
getColumnName(int) - Method in class weka.gui.sql.ResultSetTableModel: returns the name of the column at columnIndex.
getColumnNames() - Method in class weka.gui.sql.ResultSetHelper: returns an array with the names of the columns in the resultset.
getColumnPackedCopy() - Method in class weka.core.matrix.Matrix: Make a one-dimensional column packed copy of the internal array.
getCombinationRule() - Method in class weka.classifiers.meta.Vote: Gets the combination rule used
getCommand(String) - Static method in class weka.gui.simplecli.AbstractCommand: Locates the command for the given name.
getCommand() - Method in class weka.gui.treevisualizer.TreeDisplayEvent
getCommandDescription() - Method in class weka.gui.knowledgeflow.AbstractGraphicalCommand: Get a description of this command
getCommandDescription() - Method in class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand: Get the description of this command
getCommandDescription() - Method in class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand: Get the description of this command
getCommandHistory() - Method in class weka.gui.SimpleCLIPanel: Returns the command history.
getCommandName() - Method in class weka.gui.knowledgeflow.AbstractGraphicalCommand: Get the name of this command
getCommandName() - Method in class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand: Get the name of the command
getCommandName() - Method in class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand: Get the name of the command
getCommands() - Static method in class weka.gui.simplecli.AbstractCommand: Returns all available commands.
getComment() - Method in enum weka.core.TechnicalInformation.Field: returns the comment string
getComment() - Method in enum weka.core.TechnicalInformation.Type: returns the comment string
getCommonPrefix() - Method in class weka.core.Trie: returns the common prefix for all the nodes
getCommonPrefix() - Method in class weka.core.Trie.TrieNode: returns the common prefix for all the nodes starting with this node.
getCommonPrefix(String) - Method in class weka.core.Trie.TrieNode: returns the common prefix for all the nodes starting with the node for the specified prefix.
getCommonPrefix(Vector<String>) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns the common prefix for all the items in the list.
getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the compareFunction property.
getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the compareFunction property.
getCompareFunction() - Method in class weka.core.pmml.jaxbbindings.KNNInput: Gets the value of the compareFunction property.
getComparison() - Method in class weka.associations.NumericItem: Gets the comparison operator for this item.
getComparisonAsString() - Method in class weka.associations.Item: Get this item's comparison operator as a String.
getComparisonAsString() - Method in class weka.associations.NominalItem: Get this item's comparison operator as a String.
getComparisonAsString() - Method in class weka.associations.NumericItem: Get this item's comparison operator as a String.
getComparisonField() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the name of the field used for comparison.
getComparisons() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the comparisons property.
getCompatibilityState() - Method in class weka.experiment.AveragingResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.CrossValidationResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.DatabaseResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.LearningRateResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in class weka.experiment.RandomSplitResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getCompatibilityState() - Method in interface weka.experiment.ResultProducer: Gets a description of the internal settings of the result producer, sufficient for distinguishing a ResultProducer instance from another with different settings (ignoring those settings set through this interface).
getComponent() - Method in class weka.gui.visualize.JComponentWriter: returns the component that is stored in the output format
getComponent() - Method in class weka.gui.visualize.PrintableComponent: returns the GUI component this print dialog is part of.
getComposite() - Method in class weka.gui.visualize.PostscriptGraphics
getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the compoundPredicate property.
getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the compoundPredicate property.
getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the compoundPredicate property.
getCompoundPredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the compoundPredicate property.
getCompressOutput() - Method in class weka.core.converters.ArffSaver: Gets whether the output data is compressed.
getCompressOutput() - Method in class weka.core.converters.JSONSaver: Gets whether the output data is compressed.
getCompressOutput() - Method in class weka.core.converters.XRFFSaver: Gets whether the output data is compressed.
getComputeAttributeImportance() - Method in class weka.classifiers.trees.RandomForest: Get whether to compute and output attribute importance scores
getComputeImpurityDecreases() - Method in class weka.classifiers.trees.RandomTree: Get whether to compute/store impurity decreases for variable importance in RandomForest
getComputeMaxRowsInParallel() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the maximum number of threads to use when computing image rows
getCon() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the con property.
getConditionalEstimators() - Method in class weka.classifiers.bayes.NaiveBayes: Get all the conditional estimators.
getConfidence() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the confidence property.
getConfidence() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Gets the value of the confidence property.
getConfidence() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the confidence property.
getConfidence() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the confidence property.
getConfidenceFactor() - Method in class weka.classifiers.rules.PART: Get the value of CF.
getConfidenceFactor() - Method in class weka.classifiers.trees.J48: Get the value of CF.
getConfidenceLevel() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the confidenceLevel property.
getConfidenceLowerBound() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the confidenceLowerBound property.
getConfidenceUpperBound() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the confidenceUpperBound property.
getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewer: returns the setting of whether to display a confirm messagebox or not on exit
getConfirmExit() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the setting of whether to display a confirm messagebox or not on exit
getConfusionMatrix() - Method in class weka.classifiers.evaluation.TwoClassStats: Generates a ConfusionMatrix representing the current two-class statistics, using class names "negative" and "positive".
getConfusionMatrix() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the confusionMatrix property.
getConnectedFormat() - Method in class weka.gui.beans.ClassAssigner: Returns the structure of the incoming instances (if any)
getConnectedFormat() - Method in class weka.gui.beans.ClassValuePicker: Returns the structure of the incoming instances (if any)
getConnectedFormat() - Method in class weka.gui.beans.FlowByExpression: Returns the structure of the incoming instances (if any)
getConnectedFormat() - Method in class weka.gui.beans.Sorter: Returns the structure of the incoming instances (if any)
getConnectedInputNames() - Method in class weka.knowledgeflow.steps.Join: Get the names of the connected steps as a list
getConnection() - Method in class weka.gui.sql.DbUtils: returns the current database connection.
getConnectionName() - Method in class weka.knowledgeflow.Data: Get the connection name associated with this Data object
getConnections(Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns the list of connections
getConnectorPoint(int) - Method in class weka.gui.beans.BeanVisual: Returns the coordinates of the connector point given a compass point
getConsequence() - Method in class weka.associations.AssociationRule: Get the consequence of this rule.
getConsequence() - Method in class weka.associations.DefaultAssociationRule
getConsequenceSupport() - Method in class weka.associations.AssociationRule: Get the support for the consequence.
getConsequenceSupport() - Method in class weka.associations.DefaultAssociationRule
getConsequent() - Method in class weka.classifiers.rules.JRip.RipperRule: Gets the internal representation of the class label to be predicted
getConsequent() - Method in class weka.classifiers.rules.Rule: Get the consequent of this rule, i.e.
getConsequent() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the consequent property.
getConservativeForwardSelection() - Method in class weka.attributeSelection.GreedyStepwise: Gets whether conservative selection has been enabled
getConstant() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the constant property.
getConstant() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the constant property.
getConstant() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the constant property.
getConsumeNonMatching() - Method in class weka.gui.beans.SubstringLabeler: Get whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.
getConsumeNonMatching() - Method in class weka.gui.beans.SubstringLabelerRules: Get whether to consume non matching instances.
getConsumeNonMatching() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.
getContainChildBalls() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Gets whether if a parent ball should completely enclose its two child balls.
getContent(Element) - Method in class weka.classifiers.bayes.net.BIFReader: Returns all TEXT children of the given node in one string.
getContent(Element) - Method in class weka.classifiers.bayes.net.EditableBayesNet: XML helper function.
getContent() - Method in class weka.core.pmml.jaxbbindings.Annotation: Gets the value of the content property.
getContent() - Method in class weka.core.pmml.jaxbbindings.ArrayType: Gets the value of the content property.
getContent() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.Extension: Gets the value of the content property.
getContent() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.MiningModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.Node: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.Row: Gets the value of the content property.
getContent() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the rest of the content model.
getContent() - Method in class weka.core.pmml.jaxbbindings.Timestamp: Gets the value of the content property.
getContent() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the rest of the content model.
getContent(Element) - Static method in class weka.core.xml.XMLDocument: returns the text between the opening and closing tag of a node (performs a trim() on the result).
getContent() - Method in class weka.gui.scripting.Script: Returns the content.
getContinuousScoringMethod() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the continuousScoringMethod property.
getContrastMatrixType() - Method in class weka.core.pmml.jaxbbindings.Predictor: Gets the value of the contrastMatrixType property.
getControlPanel() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: This method returns a handle to the extra controls panel, so that the visualizing class can add it to some of it's own gui panel.
getControlPanel() - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method returns the extra controls panel for the LayoutEngine, if there is any.
getContStats() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the contStats property.
getConvertNominal() - Method in class weka.classifiers.trees.LMT: Get the value of convertNominal.
getCoord1() - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Gets the value of the coord1 property.
getCoord2() - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Gets the value of the coord2 property.
getCoord3() - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Gets the value of the coord3 property.
getCopyOfInputFormat() - Method in class weka.filters.Filter: Gets a copy of just the structure of the input format instances.
getCopyright() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the copyright property.
getCoreConvertersOnly() - Method in class weka.gui.ConverterFileChooser: Returns whether only the hardcoded core converters are displayed.
getCorrelationFields() - Method in class weka.core.pmml.jaxbbindings.Correlations: Gets the value of the correlationFields property.
getCorrelationMatrix() - Method in class weka.attributeSelection.PrincipalComponents: Return the correlation/covariance matrix
getCorrelationMethods() - Method in class weka.core.pmml.jaxbbindings.Correlations: Gets the value of the correlationMethods property.
getCorrelations() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation: Gets the value of the correlations property.
getCorrelationValues() - Method in class weka.core.pmml.jaxbbindings.Correlations: Gets the value of the correlationValues property.
getCostMatrix() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Gets the misclassification cost matrix.
getCostMatrix() - Method in class weka.gui.explorer.ClassifierPanel: Get the cost matrix (if any)
getCostMatrixSource() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Gets the source location method of the cost matrix.
getCostMatrixString() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get the cost matrix to use as a string
getCount(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Get a counts for a value
getCount() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Gets the value of the count property.
getCount() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount: Gets the value of the count property.
getCount() - Method in class weka.core.pmml.jaxbbindings.TimeException: Gets the value of the count property.
getCount(double) - Method in class weka.estimators.DiscreteEstimator: Get the count for a value
getCount(int) - Method in class weka.experiment.ResultMatrix: returns the count for the row.
getCount(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the number of visible nodes there are (this may accidentally count some of the invis nodes).
getCounts(int[], int[], int[], int, int, boolean) - Method in class weka.classifiers.bayes.net.ADNode: get counts for specific instantiation of a set of nodes
getCounts(int[], int[], int[], int, int, ADNode, boolean) - Method in class weka.classifiers.bayes.net.VaryNode: get counts for specific instantiation of a set of nodes
getCounts() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the counts property.
getCounts() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the counts property.
getCountTable() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the countTable property.
getCountWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the counts.
getCovariances() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the covariances property.
getCover() - Method in class weka.classifiers.rules.JRip.Antd
getCreatorApplication() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get the name of the application that created this model
getCreatorApplication() - Method in interface weka.core.pmml.PMMLModel: Get the name of the application that created this model.
getCriterion() - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod: Gets the value of the criterion property.
getCrossVal() - Method in class weka.classifiers.rules.DecisionTable: Gets the number of folds for cross validation
getCrossValidate() - Method in class weka.classifiers.lazy.IBk: Gets whether hold-one-out cross-validation will be used to select the best k value.
getCumHazard() - Method in class weka.core.pmml.jaxbbindings.BaselineCell: Gets the value of the cumHazard property.
getCumulativeLink() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the cumulativeLink property.
getCurrent() - Method in class weka.core.Memory: returns the currently used size of the JVM heap, obtains a fresh MemoryUsage object to do so.
getCurrentBeanLayout() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getCurrentDatasetNumber() - Method in class weka.experiment.Experiment: When an experiment is running, this returns the current dataset number.
getCurrentDir() - Static method in class weka.core.Debug: returns the current working directory of the user
getCurrentFilename() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the filename of the current tab
getCurrentImage() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the currently rendering image
getCurrentIndex() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the currently selected tab index
getCurrentInstance() - Method in class weka.gui.beans.IncrementalClassifierEvent: Get the current instance
getCurrentLayout() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the flow layout for the current (visible) tab
getCurrentLogPanel() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getCurrentModel() - Method in class weka.classifiers.misc.SerializedClassifier: Gets the currently loaded model (can be null).
getCurrentPanel() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the currently selected panel
getCurrentPropertyNumber() - Method in class weka.experiment.Experiment: When an experiment is running, this returns the index of the current custom property value.
getCurrentRunNumber() - Method in class weka.experiment.Experiment: When an experiment is running, this returns the current run number.
getCurrentTabIndex() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getCurrentTabIndex() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the index of the current (visible) tab
getCurrentZoomSetting() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.CostCurve: Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(ArrayList<Prediction>, int) - Method in class weka.classifiers.evaluation.CostCurve: Calculates the performance stats for the desired class and return results as a set of Instances.
getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.MarginCurve: Calculates the cumulative margin distribution for the set of predictions, returning the result as a set of Instances.
getCurve(ArrayList<Prediction>) - Method in class weka.classifiers.evaluation.ThresholdCurve: Calculates the performance stats for the default class and return results as a set of Instances.
getCurve(ArrayList<Prediction>, int) - Method in class weka.classifiers.evaluation.ThresholdCurve: Calculates the performance stats for the desired class and return results as a set of Instances.
getCustomEditor() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getCustomEditor() - Method in class weka.gui.ColorEditor: Returns our JColorChooser object
getCustomEditor() - Method in class weka.gui.CostMatrixEditor: Gets a GUI component with which the user can edit the cost matrix.
getCustomEditor() - Method in class weka.gui.EnvironmentField
getCustomEditor() - Method in class weka.gui.FileEditor: Gets the custom editor component.
getCustomEditor() - Method in class weka.gui.GenericArrayEditor: Returns the array editing component.
getCustomEditor() - Method in class weka.gui.GenericObjectEditor: Returns the array editing component.
getCustomEditor() - Method in class weka.gui.PasswordField
getCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor: Gets a GUI component with which the user can edit the date format.
getCustomEditorForStep() - Method in class weka.gui.knowledgeflow.StepVisual: Get the fully qualified name of the custom editor (if any) for the step wrapped in this visual
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get the class name of the custom editor for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the fully qualified class name of the custom editor for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.BaseStep: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Block: Get the fully qualified class name of the custom editor for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ClassAssigner: Get the custom editor for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ClassValuePicker: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.DataGrid: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.DataVisualizer
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the name of the editor dialog for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.FlowByExpression: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Job: Get the custom editor for this step
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Join: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Loader: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Note: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Saver: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.SetVariables: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.Sorter: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in interface weka.knowledgeflow.steps.Step: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.SubstringReplacer: Return the fully qualified name of a custom editor component (JComponent) to use for editing the properties of the step.
getCustomHeight() - Method in class weka.gui.visualize.JComponentWriter: gets the custom height currently used
getCustomName() - Method in class weka.gui.beans.Appender: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Associator: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in interface weka.gui.beans.BeanCommon: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.ClassAssigner: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Classifier: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.ClassValuePicker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Clusterer: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.CostBenefitAnalysis: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.CrossValidationFoldMaker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.DataVisualizer: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Filter: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.FlowByExpression
getCustomName() - Method in class weka.gui.beans.ImageSaver
getCustomName() - Method in class weka.gui.beans.ImageViewer
getCustomName() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Join: Get the custom name of this step
getCustomName() - Method in class weka.gui.beans.Loader: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.MetaBean: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.ModelPerformanceChart: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.PredictionAppender: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Saver: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.SerializedModelSaver: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.Sorter: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.StripChart: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.SubstringLabeler: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.SubstringReplacer: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.TestSetMaker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.TextSaver
getCustomName() - Method in class weka.gui.beans.TextViewer: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.TrainingSetMaker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomName() - Method in class weka.gui.beans.TrainTestSplitMaker: Get the custom (descriptive) name for this bean (if one has been set)
getCustomPanel() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getCustomPanel() - Method in interface weka.gui.CustomPanelSupplier: Gets the custom panel for the object.
getCustomPanel() - Method in class weka.gui.EnvironmentField
getCustomPanel() - Method in class weka.gui.GenericObjectEditor: Gets the custom panel used for editing the object.
getCustomPanel() - Method in class weka.gui.PasswordField
getCustomPropsFile() - Method in class weka.core.converters.DatabaseLoader: Returns the custom properties file in use, if any.
getCustomPropsFile() - Method in class weka.core.converters.DatabaseSaver: Returns the custom properties file in use, if any.
getCustomPropsFile() - Method in class weka.experiment.InstanceQuery: Returns the custom properties file in use, if any.
getCustomWidth() - Method in class weka.gui.visualize.JComponentWriter: gets the custom width currently used
getCutoff() - Method in class weka.clusterers.Cobweb: get the cutoff
getCutPoints(int) - Method in class weka.filters.supervised.attribute.Discretize: Gets the cut points for an attribute
getCutPoints(int) - Method in class weka.filters.unsupervised.attribute.Discretize: Gets the cut points for an attribute
getCVisible() - Method in class weka.gui.treevisualizer.Node: Get If this node's childs are visible.
getCVParameter(int) - Method in class weka.classifiers.meta.CVParameterSelection: Gets the scheme paramter with the given index.
getCVParameters() - Method in class weka.classifiers.meta.CVParameterSelection: Get method for CVParameters.
getCVPredictions(Classifier, Instances, int) - Method in class weka.classifiers.evaluation.EvaluationUtils: Generate a bunch of predictions ready for processing, by performing a cross-validation on the supplied dataset.
getCVType() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: get cross validation strategy to be used in searching for networks.
getD() - Method in class weka.core.matrix.EigenvalueDecomposition: Return the block diagonal eigenvalue matrix
getD00Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the d00Parameter property.
getD01Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the d01Parameter property.
getD10Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the d10Parameter property.
getD11Parameter() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the d11Parameter property.
getData() - Method in class weka.attributeSelection.BestFirst.Link2: Get a group
getData() - Method in class weka.classifiers.rules.RuleStats: Get the data of the stats
getData() - Method in class weka.core.AttributeLocator: returns the underlying data
getData() - Method in class weka.core.converters.ArffLoader.ArffReader: Returns the data that was read
getData() - Method in class weka.core.TestInstances: returns the current dataset, can be null
getData() - Method in class weka.knowledgeflow.steps.DataGrid: Get the data to be output by this DataGrid in textual ARFF format
getDatabaseURL() - Method in class weka.experiment.DatabaseUtils: Get the value of DatabaseURL.
getDataDictionary() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get the data dictionary.
getDataDictionary() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the dataDictionary property.
getDataFields() - Method in class weka.core.pmml.jaxbbindings.DataDictionary: Gets the value of the dataField property.
getDataFileName() - Method in class weka.classifiers.BVDecompose: Get the name of the data file used for the decomposition
getDataFileName() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the name of the data file used for the decomposition
GetDataFromResult - Class in weka.knowledgeflow.steps: Step that outputs data stored in the job environment
GetDataFromResult() - Constructor for class weka.knowledgeflow.steps.GetDataFromResult
getDataGenerator() - Method in class weka.knowledgeflow.steps.DataGenerator: get the data generator
getDataName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Gets the value of the dataName property.
getDataName() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the dataName property.
getDataPoint() - Method in class weka.gui.beans.ChartEvent: Get the data point
getDataset() - Method in class weka.classifiers.CheckSource: Gets the dataset to use for testing, can be null.
getDataSet() - Method in class weka.core.converters.AbstractLoader
getDataSet() - Method in class weka.core.converters.ArffLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.C45Loader: Return the full data set.
getDataSet() - Method in class weka.core.converters.ConverterUtils.DataSource: returns the full dataset, can be null in case of an error.
getDataSet(int) - Method in class weka.core.converters.ConverterUtils.DataSource: returns the full dataset with the specified class index set, can be null in case of an error.
getDataSet() - Method in class weka.core.converters.CSVLoader
getDataSet() - Method in class weka.core.converters.DatabaseLoader: Return the full data set in batch mode (header and all intances at once).
getDataSet() - Method in class weka.core.converters.JSONLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.LibSVMLoader: Return the full data set.
getDataSet() - Method in interface weka.core.converters.Loader: Return the full data set.
getDataSet() - Method in class weka.core.converters.MatlabLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.SerializedInstancesLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.SVMLightLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.TextDirectoryLoader: Return the full data set.
getDataSet() - Method in class weka.core.converters.XRFFLoader: Return the full data set.
getDataset() - Method in class weka.filters.CheckSource: Gets the dataset to use for testing, can be null.
getDataSet() - Method in class weka.gui.beans.DataSetEvent: Return the instances of the data set
getDataSet() - Method in class weka.gui.beans.ThresholdDataEvent: Return the instances of the data set
getDataSet() - Method in class weka.gui.beans.VisualizableErrorEvent: Return the instances of the data set
getDatasetFormat() - Method in class weka.datagenerators.DataGenerator: Gets the format of the dataset that is to be generated.
getDatasetKeyColumns() - Method in class weka.experiment.PairedTTester: Get the value of DatasetKeyColumns.
getDatasetKeyColumns() - Method in interface weka.experiment.Tester: Get the value of DatasetKeyColumns.
getDatasets() - Method in class weka.experiment.Experiment: Gets the datasets in the experiment.
getDatasets() - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer: Get the datasets seen so far
getDatasetsFirst() - Static method in class weka.gui.experiment.ExperimenterDefaults: whether datasets or algorithms are iterated first.
getDataType() - Method in class weka.core.pmml.jaxbbindings.Constant: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.ParameterField: Gets the value of the dataType property.
getDataType() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the dataType property.
getDataType() - Method in class weka.gui.beans.xml.XMLBeans: returns the type of data that is to be read/written
getDataUsage() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the dataUsage property.
getDateAttributes() - Method in class weka.core.converters.CSVLoader: Returns the current attribute range to be forced to type date.
getDateFormat() - Method in class weka.core.Attribute: Returns the Date format pattern in case this attribute is of type DATE, otherwise an empty string.
getDateFormat() - Method in class weka.core.converters.CSVLoader: Get the format to use for parsing date values.
getDateFormat() - Method in class weka.filters.unsupervised.attribute.Add: Get the date format, complying to ISO-8601.
getDateFormat() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the date formatting string (if any)
getDateFormat() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Get the date format used in output.
getDateFormat() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Get the date format used in output.
getDateFormat() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Get the date format to use for parsing the date replacement constant
getDateReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Get the date replacement value
getDateValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the value of the attribute as a date or null if the attribute isn't of type date.
getDbUtils() - Method in class weka.gui.sql.event.ConnectionEvent: returns the DbUtils instance that is responsible for the connect/disconnect.
getDbUtils() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the DbUtils instance that was executed the query
getDebug() - Method in class weka.attributeSelection.CfsSubsetEval: Set whether to output debugging info
getDebug() - Method in class weka.classifiers.AbstractClassifier: Get whether debugging is turned on.
getDebug() - Method in class weka.classifiers.BVDecompose: Gets whether debugging is turned on
getDebug() - Method in class weka.classifiers.BVDecomposeSegCVSub: Gets whether debugging is turned on
getDebug() - Method in class weka.classifiers.functions.Logistic: Gets whether debugging output will be printed.
getDebug() - Method in class weka.classifiers.functions.supportVector.Kernel: Gets whether debugging output is turned on or not.
getDebug() - Method in class weka.classifiers.meta.MultiScheme: Get whether debugging is turned on
getDebug() - Method in class weka.classifiers.rules.JRip: Gets whether debug information is output to the console
getDebug() - Method in class weka.clusterers.AbstractClusterer: Get whether debugging is turned on.
getDebug() - Method in class weka.clusterers.EM: Get debug mode
getDebug() - Method in class weka.core.Check: Get whether debugging is turned on
getDebug() - Method in class weka.core.converters.TextDirectoryLoader: Gets whether additional debug information is printed.
getDebug() - Method in class weka.core.Debug.Random: returns whether to print the generated random values or not
getDebug() - Method in class weka.core.stopwords.AbstractStopwords: Get whether debugging is turned on.
getDebug() - Method in class weka.datagenerators.DataGenerator: Gets the debug flag.
getDebug() - Method in class weka.estimators.CheckEstimator: Get whether debugging is turned on
getDebug() - Method in class weka.estimators.Estimator: Get whether debugging is turned on.
getDebug() - Method in class weka.experiment.DatabaseUtils: Gets whether there should be printed some debugging output to stderr or not.
getDebug() - Method in interface weka.experiment.InstanceQueryAdapter: Gets whether there should be printed some debugging output to stderr or not.
getDebug() - Method in class weka.filters.Filter: Get whether debugging is turned on.
getDebug() - Method in class weka.filters.unsupervised.attribute.AddExpression: Gets whether debug is set
getDebug() - Method in class weka.gui.DatabaseConnectionDialog: Returns the debug flag
getDebug() - Method in class weka.gui.knowledgeflow.MainKFPerspective
getDebug() - Method in class weka.gui.scripting.ScriptingPanel: Returns whether debugging mode is on.
getDebug() - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns whether debug mode is on.
getDebug() - Method in class weka.gui.streams.InstanceCounter
getDebug() - Method in class weka.gui.streams.InstanceJoiner
getDebug() - Method in class weka.gui.streams.InstanceLoader
getDebug() - Method in class weka.gui.streams.InstanceSavePanel
getDebug() - Method in class weka.gui.streams.InstanceTable
getDebug() - Method in class weka.gui.streams.InstanceViewer
getDebuggingOutput() - Method in class weka.attributeSelection.GreedyStepwise: Get whether to output debugging info to the console
getDecay() - Method in class weka.classifiers.functions.MultilayerPerceptron
getDecimals() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the number of decimals to round to.
getDecision() - Method in class weka.core.pmml.jaxbbindings.Decisions: Gets the value of the decision property.
getDecisions() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the decisions property.
getDefault() - Method in class weka.core.Tee: returns the default printstrean, can be NULL.
getDefaultChild() - Method in class weka.core.pmml.jaxbbindings.Node: Gets the value of the defaultChild property.
getDefaultColNameWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the column names.
getDefaultColNameWidth() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the default width for the column names.
getDefaultConfidence() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the defaultConfidence property.
getDefaultCountWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the counts.
getDefaultCountWidth() - Method in class weka.experiment.ResultMatrixPlainText: returns the default width for the counts.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrix: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixCSV: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixHTML: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateColNames() - Method in class weka.experiment.ResultMatrixLatex: returns the default of whether column names are prefixed with the index.
getDefaultEnumerateRowNames() - Method in class weka.experiment.ResultMatrix: returns theh default of whether row names are prefixed with the index.
getDefaultEnumerateRowNames() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the default of whether row names are prefixed with the index.
getDefaultExtension() - Method in class weka.gui.scripting.GroovyScript: Returns the default extension.
getDefaultExtension() - Method in class weka.gui.scripting.JythonScript: Returns the default extension.
getDefaultExtension() - Method in class weka.gui.scripting.Script: Returns the default extension.
getDefaultFlowExecutor() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Gets a new instance of the default flow executor suitable for use with this execution environment
getDefaultIconPath() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get the default icon for this type of wrapped algorithm (i.e.
getDefaultMeanPrec() - Method in class weka.experiment.ResultMatrix: returns the default precision for the means.
getDefaultMeanWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the mean.
getDefaultNumDecimals() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the default number of digits to output after the decimal point.
getDefaultPackageLevelIconPath() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get the default icon at the package level for this type of wrapped algorithm - e.g.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrix: returns the default of whether column names or numbers instead are printed.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixCSV: returns the default of whether column names or numbers instead are printed.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixHTML: returns the default of whether column names or numbers instead are printed.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixLatex: returns the default of whether column names or numbers instead are printed.
getDefaultPrintColNames() - Method in class weka.experiment.ResultMatrixSignificance: returns the default of whether column names or numbers instead are printed.
getDefaultPrintRowNames() - Method in class weka.experiment.ResultMatrix: returns the default of whether row names or numbers instead are printed.
getDefaultRemoveFilterName() - Method in class weka.experiment.ResultMatrix: returns the default of whether the filter classname is removed from the dataset name.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixCSV: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixHTML: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixPlainText: returns the default width for the row names.
getDefaultRowNameWidth() - Method in class weka.experiment.ResultMatrixSignificance: returns the default width for the row names.
getDefaults() - Method in class weka.core.Defaults: Get the map of default settings
getDefaultScore() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the defaultScore property.
getDefaultSettings() - Method in class weka.core.packageManagement.DefaultPackageManager: Get the default settings for the default package manager
getDefaultSettings() - Method in class weka.core.packageManagement.PackageManager: Get the default settings of this package manager.
getDefaultSettings() - Method in class weka.gui.AbstractPerspective: Get the default settings for this perspective (or null if there are none)
getDefaultSettings() - Method in class weka.gui.explorer.AssociationsPanel
getDefaultSettings() - Method in class weka.gui.explorer.AttributeSelectionPanel
getDefaultSettings() - Method in class weka.gui.explorer.ClassifierPanel
getDefaultSettings() - Method in class weka.gui.explorer.ClustererPanel
getDefaultSettings() - Method in class weka.gui.explorer.PreprocessPanel
getDefaultSettings() - Method in class weka.gui.explorer.VisualizePanel: Default settings for the scatter plot
getDefaultSettings() - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Get the default settings for this perspective
getDefaultSettings() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Get default settings for the viewer.
getDefaultSettings() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the default settings for this perspective (or null if there are none)
getDefaultSettings() - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Get default settings
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView: Get the default settings for this viewer
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView: Get default settings for this viewer
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView: Get default settings for this viewer
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView: Get the default settings of this viewer
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Get the default settings for this viewer
getDefaultSettings() - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Get the default settings of this viewer
getDefaultSettings() - Method in interface weka.gui.Perspective: Get the default settings for this perspective (or null if there are none)
getDefaultSettings() - Method in class weka.gui.SimpleCLIPanel
getDefaultSettings() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get default settings for the base execution environment
getDefaultSettings() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get default settings for this ExecutionEnvironment.
getDefaultSettings() - Method in class weka.knowledgeflow.steps.BaseStep: Get default settings for the step (if any).
getDefaultSettings() - Method in class weka.knowledgeflow.steps.ImageSaver: Get default settings for the step.
getDefaultSettings() - Method in interface weka.knowledgeflow.steps.Step: Get default settings for the step (if any).
getDefaultSettings() - Method in class weka.knowledgeflow.steps.TextSaver: Get default settings for the step (if any).
getDefaultShowAverage() - Method in class weka.experiment.ResultMatrix: returns the default of whether average per column is displayed or not.
getDefaultShowStdDev() - Method in class weka.experiment.ResultMatrix: returns the default of whether std deviations are displayed or not.
getDefaultShowStdDev() - Method in class weka.experiment.ResultMatrixSignificance: returns the default of whether std deviations are displayed or not.
getDefaultSignificanceWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the significance.
getDefaultStdDevPrec() - Method in class weka.experiment.ResultMatrix: returns the default standard deviation precision.
getDefaultStdDevWidth() - Method in class weka.experiment.ResultMatrix: returns the default width for the std dev.
getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the defaultValue property.
getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Gets the value of the defaultValue property.
getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the defaultValue property.
getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Gets the value of the defaultValue property.
getDefaultValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the defaultValue property.
getDefaultValue() - Method in class weka.core.pmml.TargetMetaInfo: Get the default value (numeric target)
getDefineFunction() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary: Gets the value of the defineFunction property.
getDegree() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Gets the value of the degree property.
getDegreesOfFreedom() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the degreesOfFreedom property.
getDegreesOfFreedom() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the degreesOfFreedom property.
getDegreesOfFreedom() - Method in class weka.experiment.PairedStats: Gets the degrees of freedom.
getDeleteEmptyBins() - Method in class weka.classifiers.meta.RegressionByDiscretization: Gets whether empty bins are deleted.
getDelimiter() - Method in class weka.core.pmml.jaxbbindings.Delimiter: Gets the value of the delimiter property.
getDelimiters() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Get the value of delimiters (not backquoted).
getDelimiters() - Method in class weka.gui.scripting.SyntaxDocument: Returns the delimiter characters to use.
getDelta() - Method in class weka.associations.Apriori: Get the value of delta.
getDelta() - Method in class weka.associations.FPGrowth: Get the value of delta.
getDelta() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getDelta() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getDelta() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the delta property.
getDensityBasedClusterer() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Get the clusterer used by this filter
getDependencies() - Method in class weka.core.packageManagement.DefaultPackage: Get the list of packages that this package depends on.
getDependencies() - Method in class weka.core.packageManagement.Package: Get the list of packages that this package depends on.
getDerivedField() - Method in class weka.core.pmml.jaxbbindings.BayesInput: Gets the value of the derivedField property.
getDerivedField() - Method in class weka.core.pmml.jaxbbindings.LocalTransformations: Gets the value of the derivedField property.
getDerivedField() - Method in class weka.core.pmml.jaxbbindings.NeuralInput: Gets the value of the derivedField property.
getDerivedField() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput: Gets the value of the derivedField property.
getDerivedField() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary: Gets the value of the derivedField property.
getDerivedFields() - Method in class weka.core.pmml.MiningSchema
getDerivedValue(double[]) - Method in class weka.core.pmml.DerivedFieldMetaInfo: Get the derived field value for the given incoming vector of values.
getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getDescendantPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getDescending() - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Return true if the sort is descending
getDescription() - Method in class weka.core.pmml.jaxbbindings.Decision: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.Decisions: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.LinearKernelType: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType: Gets the value of the description property.
getDescription() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Gets the value of the description property.
getDescription() - Method in class weka.core.Settings.SettingKey: Get the description (display name) of this setting
getDescription() - Method in class weka.gui.ExtensionFileFilter: Gets the description of accepted files.
getDescription() - Method in class weka.gui.visualize.BMPWriter: returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.JComponentWriter: returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.JPEGWriter: returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.PNGWriter: returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.gui.visualize.PostscriptWriter: returns the name of the writer, to display in the FileChooser.
getDescription() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get a description of this execution environment
getDescription() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get a description of this execution environment
getDesignVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin: Get the specific version of Weka the class is designed for.
getDesignVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin: Get the specific version of Weka the class is designed for.
getDesiredWeightOfInstancesPerInterval() - Method in class weka.filters.unsupervised.attribute.Discretize: Get the DesiredWeightOfInstancesPerInterval value.
getDestination() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default destination.
getDetectionPerAttribute() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").
getDeviceConfiguration() - Method in class weka.gui.visualize.PostscriptGraphics
getDF() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the df property.
getDf() - Method in class weka.core.pmml.jaxbbindings.PCell: Gets the value of the df property.
getDiagDefault() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the diagDefault property.
getDictionaries(boolean) - Method in class weka.core.DictionaryBuilder: Get the current dictionary(s) (one per class for nominal class, if set).
getDictionary() - Method in class weka.classifiers.functions.SGDText: Get this model's dictionary (including term weights).
getDictionaryFile() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Get the dictionary file to read from
getDictionaryFileToSaveTo() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the dictionary file to save the dictionary to.
getDictionaryHandler() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Get the dictionary builder used to manage the dictionary and perform the actual vectorization
getDictionaryIsBinary() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector
getDictionarySize() - Method in class weka.classifiers.functions.SGDText: Return the size of the dictionary (minus any low frequency terms that are below the threshold but haven't been pruned yet).
getDir() - Method in class weka.core.Javadoc: returns the current dir containing the class to update.
getDir() - Method in class weka.gui.Loader: returns the dir prefix
getDirection() - Method in class weka.attributeSelection.BestFirst: Get the search direction
getDirectory() - Method in class weka.core.converters.TextDirectoryLoader: get the Dir specified as the source
getDirectory() - Method in class weka.gui.beans.SerializedModelSaver: Get the directory that the model(s) will be saved into
getDiscardPredictions() - Method in class weka.classifiers.evaluation.Evaluation: Returns whether predictions are not recorded at all, in order to conserve memory.
getDiscardPredictions() - Method in class weka.classifiers.Evaluation: Returns whether predictions are not recorded at all, in order to conserve memory.
getDiscretize() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the discretize property.
getDiscretize() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the discretize property.
getDiscretize() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the discretize property.
getDiscretizeBin() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the discretizeBin property.
getDiscretizer() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return the discretizer used at this node
getDiscrStats() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the discrStats property.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.HTML: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.InMemory: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.Null: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.PlainText: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in class weka.classifiers.evaluation.output.prediction.XML: Returns a short display text, to be used in comboboxes.
getDisplay() - Method in enum weka.core.TechnicalInformation.Field: returns the display string
getDisplay() - Method in enum weka.core.TechnicalInformation.Type: returns the display string
getDisplayCol(int) - Method in class weka.experiment.ResultMatrix: returns the displayed index of the given col, depending on the order of columns, returns -1 if index out of bounds.
getDisplayedResultsets() - Method in class weka.experiment.PairedTTester: Gets the indices of the the datasets that are displayed (if null then all are displayed).
getDisplayedResultsets() - Method in interface weka.experiment.Tester: Gets the indices of the the datasets that are displayed (if null then all are displayed).
getDisplayModelInOldFormat() - Method in class weka.classifiers.bayes.NaiveBayes: Get whether to display model output in the old, original format.
getDisplayModelInOldFormat() - Method in class weka.clusterers.EM: Get whether to display model output in the old, original format.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the displayName property.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the displayName property.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the displayName property.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the displayName property.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the displayName property.
getDisplayName() - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Gets the value of the displayName property.
getDisplayName() - Method in class weka.experiment.PairedCorrectedTTester: returns the name of the tester
getDisplayName() - Method in class weka.experiment.PairedTTester: returns the name of the tester
getDisplayName() - Method in class weka.experiment.ResultMatrix: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixCSV: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixHTML: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixLatex: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixPlainText: returns the name of the output format.
getDisplayName() - Method in class weka.experiment.ResultMatrixSignificance: returns the name of the output format.
getDisplayName() - Method in interface weka.experiment.Tester: returns the name of the testing algorithm
getDisplayRow(int) - Method in class weka.experiment.ResultMatrix: returns the displayed index of the given row, depending on the order of rows, returns -1 if index out of bounds.
getDisplayRules() - Method in class weka.classifiers.rules.DecisionTable: Gets whether rules are being printed
getDisplayStdDevs() - Method in class weka.clusterers.SimpleKMeans: Gets whether standard deviations and nominal count.
getDisplayStepLabel() - Method in class weka.gui.knowledgeflow.NoteVisual
getDisplayStepLabel() - Method in class weka.gui.knowledgeflow.StepVisual: Returns true if the step label is to be displayed.
getDisplayValue() - Method in class weka.core.pmml.FieldMetaInfo.Value
getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.Decision: Gets the value of the displayValue property.
getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the displayValue property.
getDisplayValue() - Method in class weka.core.pmml.jaxbbindings.Value: Gets the value of the displayValue property.
getDistance() - Method in class weka.core.FilteredDistance: Gets the distance used.
getDistanceFunction() - Method in class weka.clusterers.HierarchicalClusterer
getDistanceFunction() - Method in class weka.clusterers.SimpleKMeans: returns the distance function currently in use.
getDistanceFunction() - Method in class weka.core.neighboursearch.KDTree: returns the distance function currently in use.
getDistanceFunction() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: returns the distance function currently in use.
getDistanceIsBranchLength() - Method in class weka.clusterers.HierarchicalClusterer
getDistances() - Method in class weka.core.neighboursearch.BallTree: Returns the distances of the k nearest neighbours.
getDistances() - Method in class weka.core.neighboursearch.CoverTree: Returns the distances of the (k)-NN(s) found earlier by kNearestNeighbours()/nearestNeighbour().
getDistances() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the distances for the nearest neighbours in the FILTERED space
getDistances() - Method in class weka.core.neighboursearch.KDTree: Returns the distances to the kNearest or 1 nearest neighbour currently found with either the kNearestNeighbours or the nearestNeighbour method.
getDistances() - Method in class weka.core.neighboursearch.LinearNNSearch: Returns the distances of the k nearest neighbours.
getDistances() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the distances of the k nearest neighbours.
getDistanceWeighting() - Method in class weka.classifiers.lazy.IBk: Gets the distance weighting method used.
getDistMult() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the distance multiplier.
getDistParameter() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the distParameter property.
getDistribution(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
getDistribution(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns distribution of a node in matrix form with matrix representing distribution with P[i][j] = P(node = j | parent configuration = i)
getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.HNode: Return a class probability distribution computed from the frequency counts at this node
getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.NBNode
getDistribution(Instance, Attribute) - Method in class weka.classifiers.trees.ht.NBNodeAdaptive
getDistribution() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the distribution property.
getDistribution() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the current distribution that'll be used for calculating the random matrix
getDistributions() - Method in class weka.classifiers.bayes.BayesNet: Get full set of estimators.
getDistributions(int) - Method in class weka.classifiers.rules.RuleStats: Get the class distribution predicted by the rule in given position
getDistributionSpread() - Method in class weka.filters.supervised.instance.SpreadSubsample: Gets the value for the distribution spread
getDocType() - Method in class weka.core.xml.XMLDocument: returns the current DOCTYPE, can be null.
getDocument() - Method in class weka.core.xml.XMLDocument: returns the parsed DOM document.
getDocument() - Method in class weka.core.xml.XMLOptions: returns the parsed DOM document.
getDocument() - Method in class weka.gui.DocumentPrinting: Returns the document to print.
getDocumentNormalization() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Gets the value of the documentNormalization property.
getDoNotCheckCapabilities() - Method in class weka.associations.AbstractAssociator: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.attributeSelection.ASEvaluation: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.classifiers.AbstractClassifier: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.classifiers.functions.supportVector.Kernel
getDoNotCheckCapabilities() - Method in class weka.clusterers.AbstractClusterer: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in interface weka.core.CapabilitiesIgnorer: Returns true if we do not actually want to check capabilities to conserver runtime.
getDoNotCheckCapabilities() - Method in class weka.core.converters.AbstractSaver: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.core.FindWithCapabilities: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.estimators.Estimator: Get whether capabilities checking is turned off.
getDoNotCheckCapabilities() - Method in class weka.filters.Filter: Get whether capabilities checking is turned off.
getDoNotCheckForModifiedClassAttribute() - Method in class weka.classifiers.meta.FilteredClassifier: Returns true if classifier checks whether class attribute has been modified by filter.
getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.rules.PART: Gets the value of doNotMakeSplitPointActualValue.
getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.trees.J48: Gets the value of doNotMakeSplitPointActualValue.
getDoNotMakeSplitPointActualValue() - Method in class weka.classifiers.trees.LMT: Gets the value of doNotMakeSplitPointActualValue.
getDoNotOperateOnPerClassBasis() - Method in class weka.core.converters.DictionarySaver: Get the DoNotOperateOnPerClassBasis value.
getDoNotOperateOnPerClassBasis() - Method in class weka.core.DictionaryBuilder: Get the DoNotOperateOnPerClassBasis value.
getDoNotOperateOnPerClassBasis() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Get the DoNotOperateOnPerClassBasis value.
getDoNotPrintModels() - Method in class weka.classifiers.meta.Vote: Get whether to print the individual ensemble models in the output
getDoNotStandardizeAttributes() - Method in class weka.classifiers.functions.Logistic: Gets whether not to standardize attributes.
getDontFilterAfterFirstBatch() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.
getDontNormalize() - Method in class weka.classifiers.functions.SGD: Get whether normalization has been turned off.
getDontNormalize() - Method in class weka.core.NormalizableDistance: Gets whether if the attribute values are to be normazlied in distance calculation.
getDontReplaceMissing() - Method in class weka.classifiers.functions.SGD: Get whether global replacement of missing values has been disabled.
getDontReplaceMissingValues() - Method in class weka.clusterers.Canopy: Gets whether missing values are to be replaced.
getDontReplaceMissingValues() - Method in class weka.clusterers.SimpleKMeans: Gets whether missing values are to be replaced.
getDontShowDialog(String) - Static method in class weka.core.Utils: For a named dialog, returns true if the user has opted not to view it again in the future.
getDontShowDialogResponse(String) - Static method in class weka.core.Utils: For a named dialog, if the user has opted not to view it again, returns the answer the answer the user supplied when they closed the dialog.
getDoublePivot() - Method in class weka.core.matrix.LUDecomposition: Return pivot permutation vector as a one-dimensional double array
getDownstreamStepNames() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get a list of the names of connected downstream steps
getDynamicArgsField() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the name of the attribute in the incoming instance structure that contains the arguments to the command to execute
getDynamicCmdField() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the name of the attribute in the incoming instance structure that contains the command to execute
getDynamicVarsInternalRep() - Method in class weka.knowledgeflow.steps.SetVariables
getDynamicWorkingDirField() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the name of the attribute in the incoming instance structure that containst the working directory for the command to execute
getEdited() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get whether this flow has been altered since the last save operation
getEditedStatus() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective: Get the edited status of the currently selected tab.
getEditedStatus(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective: Get the edited status of the tab at the supplied index.
getEditor() - Method in class weka.gui.PropertyDialog: Gets the current property editor.
getEditorActive() - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Returns true if the editor is currently in an active status---that is the array is active and able to be edited.
getEigenValues() - Method in class weka.attributeSelection.PrincipalComponents: Return the eigenvalues corresponding to the eigenvectors
getElement(int, int) - Method in class weka.classifiers.CostMatrix: Return the value of a cell as a double (for legacy code)
getElement(int, int, Instance) - Method in class weka.classifiers.CostMatrix: Return the value of a cell as a double.
getElement(int) - Method in class weka.core.AlgVector: Returns the value of a cell in the matrix.
getElement(int, int) - Method in class weka.core.Matrix: Deprecated.

Returns the value of a cell in the matrix.
getElementAt(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the component at the specified index.
getElements() - Method in class weka.core.AlgVector: Gets the elements of the vector and returns them as double array.
getEliminateColinearAttributes() - Method in class weka.classifiers.functions.LinearRegression: Get the value of EliminateColinearAttributes.
getEmpty() - Method in class weka.core.TestOptions
getEnabled() - Method in class weka.core.Debug: returns whether the logging is enabled
getEnclosureCharacters() - Method in class weka.core.converters.CSVLoader: Get the character(s) to use/recognize as string enclosures
getEndTime() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the endTime property.
getEndTimeVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the endTimeVariable property.
getEntropicAutoBlend() - Method in class weka.classifiers.lazy.KStar: Get whether entropic blending being used
getEntry(double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Returns the table entry to which the specified key is mapped in this hashtable.
getEntry(String, String, Class<?>) - Method in interface weka.core.metastore.MetaStore: Get a named entry from the store
getEntry(String, String, Class<?>) - Method in class weka.core.metastore.XMLFileBasedMetaStore
getEnumClass() - Method in class weka.core.EnumHelper: Get the fully qualified enum class name
getEnumerateColNames() - Method in class weka.experiment.ResultMatrix: returns whether column names are prefixed with the index.
getEnumerateRowNames() - Method in class weka.experiment.ResultMatrix: returns whether row names or prefixed with the index.
getEnvironment() - Method in class weka.gui.beans.FlowRunner: Get the environment variables that are in use.
getEnvironment() - Method in class weka.gui.knowledgeflow.StepEditorDialog: Get environment variables
getEnvironment() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the environment variables being used by this layout
getEnvironmentSettings() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getEnvironmentSettings(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getEnvironmentVariables() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get environment variables for this execution environment
getEnvironmentVariables() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get environment variables for this execution environment
getEpilogue() - Method in class weka.datagenerators.DataGenerator: Gets the epilogue string.
getEpochs() - Method in class weka.classifiers.functions.SGD: Get current number of epochs
getEpochs() - Method in class weka.classifiers.functions.SGDText: Get current number of epochs
getEpsilon() - Method in class weka.classifiers.functions.SGD: Get the epsilon threshold on the error for epsilon insensitive and Huber loss functions
getEpsilon() - Method in class weka.classifiers.functions.SMO: Get the value of epsilon.
getEpsilon() - Method in class weka.classifiers.functions.supportVector.RegSMO: Get the value of epsilon.
getEpsilonParameter() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Get the value of epsilon parameter of the epsilon insensitive loss function.
getError() - Method in class weka.classifiers.BVDecompose: Get the calculated error rate
getError() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated error rate
getError() - Method in class weka.knowledgeflow.ExecutionResult: Get the Exception generated during processing of a StepTask, or null if the task completed successfully.
getErrorOnProbabilities() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of errorOnProbabilities.
getErrorOnProbabilities() - Method in class weka.classifiers.trees.LMT: Get the value of errorOnProbabilities.
getErrorPlotPointSizeProportionalToMargin() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get whether the point size on classification error plots should be proportional to the prediction margin.
getErrorPlotPointSizeProportionalToMargin() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get whether the size of plot data points will be proportional to the prediction margin
getErrors() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return the errors made by the naive bayes model at this node
getErrors() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Return the errors made by the naive bayes models arising from this split.
getEstimatedErrorsForLeaf() - Method in class weka.classifiers.rules.part.C45PruneableDecList: Computes estimated errors for leaf.
getEstimator() - Method in class weka.classifiers.bayes.BayesNet: Get the BayesNetEstimator used for calculating the CPTs
getEstimator() - Method in class weka.classifiers.meta.RegressionByDiscretization: Get the estimator
getEstimator() - Method in class weka.estimators.CheckEstimator: Get the estimator used as the estimator
getEstimator(double) - Method in interface weka.estimators.ConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DDConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DKConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.DNConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.KDConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.KKConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.NDConditionalEstimator: Get a probability estimator for a value
getEstimator(double) - Method in class weka.estimators.NNConditionalEstimator: Get a probability estimator for a value
getEstimator() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Get the naive Bayes estimator in use
getEuclidean() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the euclidean property.
getEvaluateWithRespectToCosts() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get whether to evaluate with respoect to costs
getEvaluation() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Returns the Evaluation object in use.
getEvaluationMeasure() - Method in class weka.attributeSelection.ClassifierAttributeEval: Gets the currently set performance evaluation measure used for selecting attributes for the decision table
getEvaluationMeasure() - Method in class weka.attributeSelection.ClassifierSubsetEval: Gets the currently set performance evaluation measure used for selecting attributes for the decision table
getEvaluationMeasure() - Method in class weka.attributeSelection.WrapperSubsetEval: Gets the currently set performance evaluation measure used for selecting attributes for the decision table
getEvaluationMeasure() - Method in class weka.classifiers.rules.DecisionTable: Gets the currently set performance evaluation measure used for selecting attributes for the decision table
getEvaluationMetric() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the evaluation metric to use
getEvaluationMetricsToOutput() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the evaluation metrics to output (as a comma-separated list).
getEvaluationMetricsToOutput() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get the evaluation metrics to output (as a comma-separated list).
getEvaluator() - Method in class weka.attributeSelection.CheckAttributeSelection: Get the current evaluator
getEvaluator() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Gets the attribute evaluator used
getEvaluator() - Method in class weka.filters.supervised.attribute.AttributeSelection: Get the name of the attribute/subset evaluator
getEvaluator() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get the evaluator wrapped by this step
getEvalUsingTrainingData() - Method in class weka.attributeSelection.OneRAttributeEval: Returns true if the training data is to be used for evaluation
getEventName() - Method in class weka.gui.beans.BeanConnection: Returns the name of the event for this conncetion
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSinkBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractDataSourceBeanInfo: Get the event set descriptors pertinent to data sources
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTestSetProducerBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducerBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.AbstractTrainingSetProducerBeanInfo: Returns event set descriptors for this type of bean
getEventSetDescriptors() - Method in class weka.gui.beans.AppenderBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.AssociatorBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.AttributeSummarizerBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.ClustererBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.ClustererPerformanceEvaluatorBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.CostBenefitAnalysisBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.DataVisualizerBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.FilterBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.FlowByExpressionBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.GraphViewerBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.ImageSaverBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.ImageViewerBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.InstanceStreamToBatchMakerBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.JoinBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.ModelPerformanceChartBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.NoteBeanInfo
getEventSetDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo: Get the event set descriptors pertinent to data sources
getEventSetDescriptors() - Method in class weka.gui.beans.ScatterPlotMatrixBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.SerializedModelSaverBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.SorterBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.SubstringLabelerBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.SubstringReplacerBeanInfo: Returns the event set descriptors
getEventSetDescriptors() - Method in class weka.gui.beans.TextSaverBeanInfo: Get the event set descriptors for this bean
getEventSetDescriptors() - Method in class weka.gui.beans.TextViewerBeanInfo: Get the event set descriptors for this bean
getEvidence(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: get evidence state of a node.
getException() - Method in class weka.gui.sql.event.ConnectionEvent: returns the stored exception, if any (can be NULL)
getException() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the exception, if one happened, otherwise NULL
getExcludeNominalAttributes() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Get whether nominal attributes are to be excluded from the transformation
getExcludeNumericAttributes() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Get whether numeric attributes are being excluded from the transformation
getExecuting() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getExecuting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getExecutionEnvironment() - Method in interface weka.knowledgeflow.FlowExecutor: Return the execution environment object for this flow executor
getExecutionEnvironment() - Method in class weka.knowledgeflow.FlowRunner
getExecutionEnvironment() - Method in interface weka.knowledgeflow.StepManager: Get the executing environment.
getExecutionEnvironment() - Method in class weka.knowledgeflow.StepManagerImpl: Get the execution environment the managed step is running in
getExecutionSlots() - Method in class weka.gui.beans.Classifier: Get the number of execution slots (threads) used to train models.
getExecutionSlots() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Get the number of execution slots to use.
getExecutionStatus() - Method in class weka.experiment.TaskStatusInfo: Get the execution status of this Task.
getExecutionThread() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getExecutionThread(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getExitIfNoWindowsOpen() - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Gets whether System.exit gets called after the last window gets closed
getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewer: returns TRUE if a System.exit(0) is done on a close
getExitOnClose() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns TRUE if a System.exit(0) is done on a close
getExpectedResultsPerAverage() - Method in class weka.experiment.AveragingResultProducer: Get the value of ExpectedResultsPerAverage.
getExperiment() - Method in class weka.experiment.RemoteExperimentSubTask: Get the experiment for this sub task
getExperiment() - Method in class weka.gui.experiment.AbstractSetupPanel: Gets the currently configured experiment.
getExperiment() - Method in class weka.gui.experiment.SetupModePanel: Gets the currently configured experiment.
getExperiment() - Method in class weka.gui.experiment.SetupPanel: Gets the currently configured experiment.
getExperiment() - Method in class weka.gui.experiment.SimpleSetupPanel: Gets the currently configured experiment.
getExperimentType() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default experiment type.
getExplicitPropsFile() - Method in class weka.gui.GenericPropertiesCreator: returns TRUE, if a file is loaded and not the Utils class used for locating the props file.
getExplorer() - Method in class weka.gui.explorer.AssociationsPanel: returns the parent Explorer frame
getExplorer() - Method in class weka.gui.explorer.AttributeSelectionPanel: returns the parent Explorer frame
getExplorer() - Method in class weka.gui.explorer.ClassifierPanel: returns the parent Explorer frame.
getExplorer() - Method in class weka.gui.explorer.ClustererPanel: returns the parent Explorer frame
getExplorer() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel: returns the parent Explorer frame
getExplorer() - Method in class weka.gui.explorer.PreprocessPanel: returns the parent Explorer frame
getExplorer() - Method in class weka.gui.explorer.VisualizePanel: returns the parent Explorer frame
getExponent() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Gets the exponent value.
getExponent() - Method in class weka.classifiers.functions.VotedPerceptron: Get the value of exponent.
getExponent() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the exponent property.
getExponent() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Gets the value of the exponent property.
getExpression(Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - Static method in class weka.core.pmml.Expression: Static factory method that returns a subclass of Expression that encapsulates the type of expression contained in the Element supplied.
getExpression(String, Node, FieldMetaInfo.Optype, ArrayList<Attribute>, TransformationDictionary) - Static method in class weka.core.pmml.Expression: Static factory method that returns a subclass of Expression that encapsulates the type of expression supplied as an argument.
getEXPRESSION() - Method in class weka.core.pmml.jaxbbindings.Apply: Gets the value of the expression property.
getExpression() - Method in class weka.datagenerators.classifiers.regression.Expression: Gets the mathematical expression for generating y out of x
getExpression() - Method in class weka.filters.unsupervised.attribute.AddExpression: Get the expression
getExpression() - Method in class weka.filters.unsupervised.attribute.MathExpression: Get the expression
getExpression() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the regular expression in use.
getExpression() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the expression used for filtering.
getExpressionString() - Method in class weka.gui.beans.FlowByExpression: Get the current expression (in internal format)
getExpressionString() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get the current expression (in internal format)
getExtender() - Method in class weka.core.pmml.jaxbbindings.Extension: Gets the value of the extender property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Aggregate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Alternate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Anova: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Application: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Apply: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BaselineCell: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesInput: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesInputs: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BayesOutput: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.BoundaryValues: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Categories: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Category: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Characteristic: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Characteristics: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Chebychev: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CityBlock: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ClassLabels: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Coefficient: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Coefficients: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Comparisons: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Con1: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ContStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationFields: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Correlations: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CorrelationValues: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Counts: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Covariances: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.CovariateList: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DataDictionary: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Decision: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Decisions: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Delimiter: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DiscrStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Euclidean: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.EventValues: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.FactorList: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.False: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldRef: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldValue: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.InlineTable: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.InstanceField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.InstanceFields: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Interval: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Item: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ItemRef: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Itemset: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Jaccard: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.KNNInput: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.KNNInputs: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.LinearKernelType: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.LinearNorm: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.LocalTransformations: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningBuildTask: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MiningSchema: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Minkowski: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralInput: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Output: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PairCounts: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Parameter: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ParameterList: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ParamMatrix: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Partition: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PCell: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PPCell: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PPMatrix: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Predictor: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Quantile: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Segmentation: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SequenceReference: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SetReference: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleMatching: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SquaredEuclidean: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVector: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TableLocator: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Tanimoto: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Targets: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TargetValueCounts: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Taxonomy: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TextCorpus: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TextDictionary: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TextDocument: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Time: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.TransformationDictionary: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.True: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.Value: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorFields: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.VerificationField: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.VerificationFields: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.XCoordinates: Gets the value of the extension property.
getExtension() - Method in class weka.core.pmml.jaxbbindings.YCoordinates: Gets the value of the extension property.
getExtension() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default experiment extension.
getExtension() - Method in class weka.gui.visualize.BMPWriter: returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.JComponentWriter: returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.JPEGWriter: returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.PNGWriter: returns the extension (incl.
getExtension() - Method in class weka.gui.visualize.PostscriptWriter: returns the extension (incl.
getExtensionAndDelimiterAndTime() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the extensionAndDelimiterAndTime property.
getExtensions() - Method in class weka.gui.ExtensionFileFilter: Returns a copy of the acceptable extensions.
getExtremeValuesAsOutliers() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Get whether extreme values are also tagged as outliers.
getExtremeValuesFactor() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets the factor for determining the thresholds for extreme values.
getFactory() - Method in class weka.core.xml.XMLDocument: returns the DocumentBuilderFactory.
getFailReason() - Method in class weka.core.Capabilities: returns the reason why the tests failed, is null if tests succeeded
getFallout() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the fallout.
getFalse() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the false property.
getFalse() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the false property.
getFalse() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the false property.
getFalse() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the false property.
getFalseNegative() - Method in class weka.classifiers.evaluation.TwoClassStats: Gets the number of positive instances predicted as negative
getFalsePositive() - Method in class weka.classifiers.evaluation.TwoClassStats: Gets the number of negative instances predicted as positive
getFalsePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the false positive rate.
getFalseStepName() - Method in class weka.gui.beans.FlowByExpression: Get the name of the connected step to send "false" instances to
getFalseStepName() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get the name of the connected step to send "false" instances to
getFastDistanceCalc() - Method in class weka.clusterers.SimpleKMeans: Gets whether to use faster distance calculation.
getFastRegression() - Method in class weka.classifiers.trees.LMT: Get the value of fastRegression.
getFeature() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the feature property.
getFeature() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the feature property.
getField() - Method in class weka.core.pmml.jaxbbindings.Aggregate: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.FieldRef: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.FieldValue: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.InstanceField: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.KNNInput: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the field property.
getField() - Method in class weka.core.pmml.jaxbbindings.VerificationField: Gets the value of the field property.
getFieldAsAttribute() - Method in class weka.core.pmml.DerivedFieldMetaInfo: Get this derived field as an Attribute.
getFieldAsAttribute() - Method in class weka.core.pmml.FieldMetaInfo: Return this field as an Attribute.
getFieldAsAttribute() - Method in class weka.core.pmml.MiningFieldMetaInfo: Return this mining field as an Attribute.
getFieldAsAttribute() - Method in class weka.core.pmml.TargetMetaInfo: Return this field as an Attribute.
getFieldColumnPair() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the fieldColumnPair property.
getFieldCount() - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Gets the value of the fieldCount property.
getFieldCount() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the fieldCount property.
getFieldDef(String) - Method in class weka.core.pmml.Expression: Return the named attribute from the list of reference fields.
getFieldDefIndex(String) - Method in class weka.core.pmml.Expression
getFieldName() - Method in class weka.core.pmml.FieldMetaInfo: Get the name of this field.
getFieldName() - Method in class weka.core.pmml.jaxbbindings.BayesInput: Gets the value of the fieldName property.
getFieldName() - Method in class weka.core.pmml.jaxbbindings.BayesOutput: Gets the value of the fieldName property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the fieldRef property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the fieldRef property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the fieldRef property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the fieldRef property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Gets the value of the fieldRef property.
getFieldRef() - Method in class weka.core.pmml.jaxbbindings.VectorFields: Gets the value of the fieldRef property.
getFieldsAsInstances() - Method in class weka.core.pmml.MiningSchema: Get the all the fields (both mining schema and derived) as Instances.
getFieldSeparator() - Method in class weka.core.converters.CSVLoader: Returns the character used as column separator.
getFieldSeparator() - Method in class weka.core.converters.CSVSaver: Returns the character used as column separator.
getFieldsMappingString() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get a textual description of the mapping between mining schema fields and incoming data fields.
getFieldsMappingString() - Method in class weka.core.pmml.MappingInfo: Get a textual description of them mapping between mining schema fields and incoming data fields.
getFieldValue() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE: Gets the value of the fieldValue property.
getFieldValue() - Method in class weka.core.pmml.jaxbbindings.FieldValue: Gets the value of the fieldValue property.
getFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE: Gets the value of the fieldValueCount property.
getFieldValueCount() - Method in class weka.core.pmml.jaxbbindings.FieldValue: Gets the value of the fieldValueCount property.
getFieldWeight() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the fieldWeight property.
getFieldWeight() - Method in class weka.core.pmml.jaxbbindings.KNNInput: Gets the value of the fieldWeight property.
getFile() - Method in class weka.core.FileHelper: Get the file wrapped in this instance
getFile() - Method in class weka.core.pmml.jaxbbindings.TextDocument: Gets the value of the file property.
getFile() - Method in class weka.gui.visualize.JComponentWriter: returns the file being used for storing the output
getFile() - Method in class weka.knowledgeflow.steps.ImageSaver: Get the file to save to
getFile() - Method in class weka.knowledgeflow.steps.TextSaver: Get the file to save to
getFileDescription() - Method in class weka.core.converters.AbstractFileSaver: to be pverridden
getFileDescription() - Method in class weka.core.converters.ArffLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.ArffSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.C45Loader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.C45Saver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.CSVLoader
getFileDescription() - Method in class weka.core.converters.CSVSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.DictionarySaver
getFileDescription() - Method in interface weka.core.converters.FileSourcedConverter: Get a one line description of the type of file
getFileDescription() - Method in class weka.core.converters.JSONLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.JSONSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.LibSVMLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.LibSVMSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.MatlabLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.MatlabSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SerializedInstancesLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SerializedInstancesSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SVMLightLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.SVMLightSaver: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.TextDirectoryLoader: Returns a description of the file type, actually it's directories.
getFileDescription() - Method in class weka.core.converters.XRFFLoader: Returns a description of the file type.
getFileDescription() - Method in class weka.core.converters.XRFFSaver: Returns a description of the file type.
getFileExtension() - Method in class weka.core.converters.AbstractFileSaver: Gets ihe file extension.
getFileExtension() - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
getFileExtension() - Method in class weka.core.converters.ArffLoader: Get the file extension used for arff files
getFileExtension() - Method in class weka.core.converters.C45Loader: Get the file extension used for arff files
getFileExtension() - Method in class weka.core.converters.CSVLoader
getFileExtension() - Method in interface weka.core.converters.FileSourcedConverter: Get the file extension used for this type of file
getFileExtension() - Method in class weka.core.converters.JSONLoader: Get the file extension used for JSON files.
getFileExtension() - Method in class weka.core.converters.LibSVMLoader: Get the file extension used for libsvm files.
getFileExtension() - Method in class weka.core.converters.MatlabLoader: Get the file extension used for libsvm files.
getFileExtension() - Method in interface weka.core.converters.Saver: Gets the file extension
getFileExtension() - Method in class weka.core.converters.SerializedInstancesLoader: Get the file extension used for arff files
getFileExtension() - Method in class weka.core.converters.SVMLightLoader: Get the file extension used for svm light files.
getFileExtension() - Method in class weka.core.converters.XRFFLoader: Get the file extension used for libsvm files
getFileExtensions() - Method in class weka.core.converters.AbstractFileSaver: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.ArffLoader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.ArffSaver: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.C45Loader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.CSVLoader
getFileExtensions() - Method in interface weka.core.converters.FileSourcedConverter: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.JSONLoader: Gets all the file extensions used for this type of file.
getFileExtensions() - Method in class weka.core.converters.JSONSaver: Gets all the file extensions used for this type of file.
getFileExtensions() - Method in class weka.core.converters.LibSVMLoader: Gets all the file extensions used for this type of file.
getFileExtensions() - Method in class weka.core.converters.MatlabLoader: Gets all the file extensions used for this type of file.
getFileExtensions() - Method in class weka.core.converters.SerializedInstancesLoader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.SVMLightLoader: Gets all the file extensions used for this type of file.
getFileExtensions() - Method in class weka.core.converters.XRFFLoader: Gets all the file extensions used for this type of file
getFileExtensions() - Method in class weka.core.converters.XRFFSaver: Gets all the file extensions used for this type of file
getFileFormat() - Method in class weka.gui.beans.SerializedModelSaver: Get the file format to use for saving.
getFileLoaders() - Static method in class weka.core.converters.ConverterResources: Returns the file loaders.
getFileLoaders() - Static method in class weka.core.converters.ConverterUtils: returns a vector with the classnames of all the file loaders.
getFileMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns all the file/dir matches with the partial search string.
getFileMustExist() - Method in class weka.gui.ConverterFileChooser: Returns whether the selected file must exist (only open dialog).
getFileName() - Method in class weka.classifiers.bayes.net.BIFReader: returns the current filename
getFilename() - Method in class weka.core.Debug.Log: returns the filename of the log, can be null
getFilename() - Method in class weka.core.Debug.SimpleLog: returns the filename of the log, can be null
getFilename() - Method in class weka.core.FindWithCapabilities: returns the current filename for the dataset to base the capabilities on.
getFilename() - Method in class weka.gui.arffviewer.ArffPanel: returns the filename
getFilename(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the filename of the specified panel
getFilename() - Method in class weka.gui.beans.ImageSaver: Get the filename to save to
getFilename() - Method in class weka.gui.beans.TextSaver: Get the filename to save to
getFilename() - Method in class weka.gui.scripting.Script: Returns the current filename.
getFilenamePrefix() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get the text to prepend to the filename
getFilePath() - Method in class weka.core.FileHelper: Get the file path
getFilePath() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the current path (if any) of the flow being edited in this layout
getFileSavers() - Static method in class weka.core.converters.ConverterResources: Returns the file savers.
getFileSavers() - Static method in class weka.core.converters.ConverterUtils: returns a vector with the classnames of all the file savers.
getFillWithMissing() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
getFilter() - Method in class weka.associations.FilteredAssociator: Gets the filter used.
getFilter() - Method in class weka.classifiers.meta.FilteredClassifier: Gets the filter used.
getFilter() - Method in class weka.clusterers.FilteredClusterer: Gets the filter used.
getFilter() - Method in class weka.core.FilteredDistance: Gets the filter used.
getFilter() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Gets the filter used.
getFilter() - Method in class weka.filters.CheckSource: Gets the filter being used for the tests, can be null.
getFilter(int) - Method in class weka.filters.MultiFilter: Gets a single filter from the set of available filters.
getFilter(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets a single filter from the set of available filters.
getFilter() - Method in class weka.gui.beans.Filter
getFilter() - Method in class weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent: returns the associated Capabilities filter
getFilter() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the default filter (fully configured) for the preprocess panel.
getFilter() - Method in class weka.knowledgeflow.steps.Filter: Get the filter.
getFilterAfterFirstBatch() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Get whether to apply the filter to instances that arrive once the first (training) batch has been seen.
getFilterClass() - Method in class weka.gui.ExtensionFileFilterWithClass: Returns the underlying class.
getFiltered(int) - Method in class weka.classifiers.rules.RuleStats: Get the data after filtering the given rule
getFilteredInputFormat() - Method in class weka.attributeSelection.PrincipalComponents: Return the header of the training data after all filtering - i.e missing values and nominal to binary.
getFilters() - Method in class weka.filters.MultiFilter: Gets the list of possible filters to choose from.
getFilters() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets the list of possible filters to choose from.
getFilters() - Method in class weka.gui.scripting.GroovyScript: Returns the extension filters for this type of script.
getFilters() - Method in class weka.gui.scripting.JythonScript: Returns the extension filters for this type of script.
getFilters() - Method in class weka.gui.scripting.Script: Returns the extension filters for this type of script.
getFilterType() - Method in class weka.classifiers.functions.GaussianProcesses: Gets how the training data will be transformed.
getFilterType() - Method in class weka.classifiers.functions.SMO: Gets how the training data will be transformed.
getFilterType() - Method in class weka.classifiers.functions.SMOreg: Gets how the training data will be transformed.
getFind() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the current regular expression for .
getFindAllRulesForSupportLevel() - Method in class weka.associations.FPGrowth: Get whether all rules meeting the lower bound on min support and the minimum metric threshold are to be found.
getFindNumBins() - Method in class weka.filters.unsupervised.attribute.Discretize: Get the value of FindNumBins.
getFindNumBins() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Get the value of FindNumBins.
getFirstInputStructure() - Method in class weka.knowledgeflow.steps.Join: Get the Instances structure being produced by the first input
getFirstToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils: Gets token, skipping empty lines.
getFirstToken(StreamTokenizer) - Static method in class weka.core.converters.StreamTokenizerUtils: Gets token, skipping empty lines.
getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Get the index of the first value used.
getFirstValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues: Get the index of the first value used.
getFlag(char, String[]) - Static method in class weka.core.Utils: Checks if the given array contains the flag "-Char".
getFlag(String, String[]) - Static method in class weka.core.Utils: Checks if the given array contains the flag "-String".
getFlow() - Method in class weka.gui.beans.KnowledgeFlowApp: Gets the current flow being edited.
getFlow() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the flow being edited by this layout
getFlow() - Method in interface weka.knowledgeflow.FlowExecutor: Get the flow to be executed
getFlow() - Method in class weka.knowledgeflow.FlowRunner: Get the flow to execute
getFlowExecutor() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the FlowExecutor being used for execution of this flow
getFlowExecutor() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get the executor that will actually be responsible for running the flow.
getFlowFile() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getFlowFile(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getFlowFile() - Method in class weka.knowledgeflow.steps.Job
getFlowFileExtension() - Method in interface weka.knowledgeflow.FlowLoader: Get the extension of the Knowledge Flow file format handled by this loader
getFlowFileExtension() - Method in class weka.knowledgeflow.JSONFlowLoader: Get the file extension handled by this loader
getFlowFileExtension() - Method in class weka.knowledgeflow.LegacyFlowLoader: Get the flow file extension of the file format handled by this flow loader
getFlowFileExtensionDescription() - Method in interface weka.knowledgeflow.FlowLoader: Get a description of the flow file format handled by this loader
getFlowFileExtensionDescription() - Method in class weka.knowledgeflow.JSONFlowLoader: Get the description of the file format handled by this loader
getFlowFileExtensionDescription() - Method in class weka.knowledgeflow.LegacyFlowLoader: Get the description of the file format handled by this flow loader
getFlowID() - Method in class weka.knowledgeflow.Flow: Get an ID string for this flow.
getFlowLoader(String, Logger) - Static method in class weka.knowledgeflow.Flow: Utility method to get a FlowLoader implementation suitable for loading a flow with the supplied file extension.
getFlowName() - Method in class weka.knowledgeflow.Flow: Get the name of this Flow
getFlows() - Method in class weka.gui.beans.FlowRunner: Get the vector holding the flow(s)
getFlowXML() - Method in class weka.gui.beans.KnowledgeFlowApp: Returns the current flow being edited in XML format.
getFMeasure() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the F-Measure.
getFold() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets the fold which is selected.
getFold() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets the fold which is selected.
getFoldColumn() - Method in class weka.experiment.PairedTTester: Get the value of FoldColumn.
getFoldColumn() - Method in interface weka.experiment.Tester: Get the value of FoldColumn.
getFolds() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the number of folds used for accuracy estimation
getFolds() - Method in class weka.attributeSelection.OneRAttributeEval: Get the number of folds used for cross validation
getFolds() - Method in class weka.attributeSelection.WrapperSubsetEval: Get the number of folds used for accuracy estimation
getFolds() - Method in class weka.classifiers.rules.JRip: Gets the number of folds
getFolds() - Method in class weka.gui.beans.CrossValidationFoldMaker: Get the currently set number of folds
getFolds() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the number of folds used for cross-validation.
getFont() - Method in class weka.core.FontHelper: Get the Font wrapped by this instance
getFont() - Method in class weka.gui.visualize.PostscriptGraphics: Get current font.
getFontMetrics(Font) - Method in class weka.gui.visualize.PostscriptGraphics: Get Font metrics
getFontName() - Method in class weka.core.FontHelper: Get the font name
getFontName() - Method in class weka.gui.scripting.SyntaxDocument: gets the current font family.
getFontRenderContext() - Method in class weka.gui.visualize.PostscriptGraphics: START overridden Graphics2D methods
getFontSize() - Method in class weka.core.FontHelper: Get the font size
getFontSize() - Method in class weka.gui.scripting.SyntaxDocument: gets the current font size.
getFontSizeAdjust() - Method in class weka.gui.beans.Note: Get the font size adjustment
getFontSizeAdjust() - Method in class weka.gui.knowledgeflow.NoteVisual: Get the font size adjustment
getFontStyle() - Method in class weka.core.FontHelper: Get the font style (see constants in Font class)
getForceResampleWithWeights() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Gets the size of each subSpace, as a percentage of the training set size.
getFormat() - Method in class weka.core.Debug.Timestamp: returns the current timestamp format
getFormat() - Method in class weka.knowledgeflow.steps.ImageSaver: Get the format of the image to save
getFrameLocation() - Method in class weka.gui.MemoryUsagePanel: Returns the default position for the dialog.
getFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the title (incl.
getFrequency() - Method in class weka.associations.Item: Get the frequency of this item.
getFreshCardinalityOfParents(Instances) - Method in class weka.classifiers.bayes.net.ParentSet: returns cardinality of parents after recalculation
getFrom() - Method in class weka.core.pmml.jaxbbindings.Con1: Gets the value of the from property.
getFromYear() - Static method in class weka.core.Copyright: returns the start year of the copyright
getFStatistic() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the fStatistic property.
getFStatistic() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the fStatistic property.
getFunction(String) - Static method in class weka.core.pmml.Function: Get a built-in PMML Function.
getFunction(String, TransformationDictionary) - Static method in class weka.core.pmml.Function: Get either a function.
getFunction() - Method in class weka.core.pmml.jaxbbindings.Aggregate: Gets the value of the function property.
getFunction() - Method in class weka.core.pmml.jaxbbindings.Apply: Gets the value of the function property.
getFunction() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Gets the function for generating the data.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.MiningModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the value of the functionName property.
getFunctionName() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the functionName property.
getFValue() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the fValue property.
getGamma() - Method in class weka.classifiers.functions.supportVector.RBFKernel: Gets the gamma value.
getGamma() - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Gets the value of the gamma property.
getGamma() - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType: Gets the value of the gamma property.
getGamma() - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Gets the value of the gamma property.
getGamma() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Gets the value of the gamma property.
getGap() - Method in class weka.core.pmml.jaxbbindings.Delimiter: Gets the value of the gap property.
getGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate: Gets the value of the gaussianDistribution property.
getGaussianDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the gaussianDistribution property.
getGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the number of visible groups of siblings there are.
getGeneralRegressionModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the generalRegressionModel property.
getGenerateRanking() - Method in class weka.attributeSelection.GreedyStepwise: Gets whether ranking has been requested.
getGenerateRanking() - Method in interface weka.attributeSelection.RankedOutputSearch: Gets whether the user has opted to see a ranked list of attributes rather than the normal result of the search
getGenerateRanking() - Method in class weka.attributeSelection.Ranker: This is a dummy method.
getGenerateSparseData() - Method in class weka.gui.sql.SqlViewerDialog: Returns whether sparse data is generated.
getGenerator() - Method in class weka.gui.explorer.DataGeneratorPanel: returns the currently selected DataGenerator
getGeneratorSamplesBase() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Get the base used for computing the number of samples to obtain from each generator
getGlobalBlend() - Method in class weka.classifiers.lazy.KStar: Get the value of the global blend parameter
getGlobalInfo(Object, boolean) - Static method in class weka.core.Utils: Utility method for grabbing the global info help (if it exists) from an arbitrary object.
getGlobalInfo(Object) - Static method in class weka.gui.beans.KnowledgeFlowApp: Utility method for grabbing the global info help (if it exists) from an arbitrary object
getGlobalInputProperties() - Static method in class weka.gui.GenericPropertiesCreator: Get the global input properties
getGlobalModel() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Return the global naive bayes model for this node
getGlobalOutputProperties() - Static method in class weka.gui.GenericPropertiesCreator: Get the global output properties
getGlobalTermWeights() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Gets the value of the globalTermWeights property.
getGracePeriod() - Method in class weka.classifiers.trees.HoeffdingTree: Get the number of instances (or total weight of instances) a leaf should observe between split attempts
getGraphicalEnvironmentCommandHandler() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get the environment for performing commands at the application-level in a graphical environment.
getGraphicalEnvironmentCommandHandler() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get the environment for performing commands at the application-level in a graphical environment.
getGraphString() - Method in class weka.gui.beans.GraphEvent: Return the dot string for the graph
getGraphTitle() - Method in class weka.gui.beans.GraphEvent: Return the graph title
getGraphType() - Method in class weka.gui.beans.GraphEvent: Return the graph type
getGridWidth() - Method in class weka.gui.beans.AttributeSummarizer: Get the width of the grid of plots
getGroupField() - Method in class weka.core.pmml.jaxbbindings.Aggregate: Gets the value of the groupField property.
getGroupIdentifier() - Method in class weka.gui.beans.BatchClassifierEvent
getGUI() - Method in class weka.classifiers.functions.MultilayerPerceptron
getGUIType() - Method in class weka.gui.Main: Gets the currently set type of GUI to display.
getH() - Method in class weka.core.matrix.QRDecomposition: Return the Householder vectors
getHandler() - Method in class weka.core.FindWithCapabilities: returns the current set CapabilitiesHandler to generate the dataset for, can be null.
getHandler() - Method in class weka.core.TestInstances: returns the current set CapabilitiesHandler to generate the dataset for, can be null
getHashtable(ArrayList<Object>, int) - Static method in class weka.associations.ItemSet: Return a hashtable filled with the given item sets.
getHashtable(ArrayList<Object>, int) - Static method in class weka.associations.LabeledItemSet: Return a hashtable filled with the given item sets.
getHeader() - Method in class weka.classifiers.bayes.NaiveBayes: Return the header that this classifier was trained with
getHeader() - Method in class weka.classifiers.evaluation.Evaluation: Returns the header of the underlying dataset.
getHeader() - Method in class weka.classifiers.Evaluation: Returns the header of the underlying dataset.
getHeader() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the header of the dataset.
getHeader() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the header property.
getHeader(String) - Method in class weka.experiment.ResultMatrix: returns the value associated with the given key, null if if cannot be found.
getHeight() - Method in class weka.gui.beans.BeanInstance: Gets the height of this bean
getHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the number of visible levels there are.
getHelp() - Method in class weka.gui.simplecli.AbstractCommand: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Capabilities: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Cls: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Echo: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Exit: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Help: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.History: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Java: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Kill: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Script: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Set: Returns the help string (no indentation).
getHelp() - Method in class weka.gui.simplecli.Unset: Returns the help string (no indentation).
getHeuristicStop() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of heuristicStop.
getHiddenLayers() - Method in class weka.classifiers.functions.MultilayerPerceptron
getHighValue() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the highValue property.
getHistory() - Method in class weka.gui.GenericObjectEditor: Returns the history of the used setups.
getHistory() - Method in class weka.gui.GenericObjectEditorHistory: Returns the current history.
getHistory() - Method in class weka.gui.sql.ConnectionPanel: returns the history.
getHistory() - Method in class weka.gui.sql.event.HistoryChangedEvent: returns the history model
getHistory() - Method in class weka.gui.sql.QueryPanel: returns the history.
getHistoryItem() - Method in class weka.gui.GenericObjectEditorHistory.HistorySelectionEvent: Returns the selected history item.
getHistoryName() - Method in class weka.gui.sql.event.HistoryChangedEvent: returns the name of the history
getHoeffdingTieThreshold() - Method in class weka.classifiers.trees.HoeffdingTree: Get the threshold below which a split will be forced to break ties
getHoldOutFile() - Method in class weka.attributeSelection.ClassifierSubsetEval: Gets the file that holds hold out/test instances.
getHomeDir() - Static method in class weka.core.Debug: returns the home directory of the user
getIcon(double) - Method in class weka.gui.knowledgeflow.StepVisual: Get the icon for this visual at the given scale factor
getIcon() - Method in class weka.gui.scripting.GroovyPanel: Returns an icon to be used in a frame.
getIcon() - Method in class weka.gui.scripting.JythonPanel: Returns an icon to be used in a frame.
getIcon() - Method in class weka.gui.scripting.ScriptingPanel: Returns an icon to be used in a frame.
getIcon() - Method in class weka.gui.SimpleCLIPanel: Returns an icon to be used in a frame.
getIconPath() - Method in class weka.gui.beans.BeanVisual: returns the path for the icon
getIconPath() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get the path to the icon for this wrapped algorithm
getId() - Method in class weka.classifiers.functions.neural.NeuralConnection
getID() - Method in class weka.core.Debug.Random: returns the unique ID of this number generator
getID() - Method in class weka.core.Defaults: Get the ID of this set of defaults
getId() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Item: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Itemset: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.NeuralInput: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Node: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.TextDocument: Gets the value of the id property.
getId() - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Gets the value of the id property.
getID() - Method in class weka.core.pmml.VectorInstance: Get the ID of this vector instance
getID() - Method in class weka.core.Settings: Get the ID used for these settings
getID() - Method in class weka.core.Tag: Gets the numeric ID of the Tag.
getID() - Method in class weka.core.TechnicalInformation: returns the unique ID (either the one used in creating this instance or the automatically generated one)
getID() - Method in class weka.gui.streams.InstanceEvent: Get the event type
getID() - Method in class weka.gui.treevisualizer.TreeDisplayEvent
getIDFTransform() - Method in class weka.core.DictionaryBuilder: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
getIDFTransform() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
getIDFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
getIDIndex() - Method in class weka.filters.unsupervised.attribute.AddID: Get the index of the attribute used.
getIDStr() - Method in class weka.core.Tag: Gets the string ID of the Tag.
getIgnoreCase() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
getIgnoreCase() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get whether to ignore case when matching
getIgnoreCase() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Get whether to ignore case when matching
getIgnoreCaseForNames() - Method in class weka.classifiers.misc.InputMappedClassifier: Get whether to ignore case when matching attribute names and nominal values.
getIgnoreClass() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Gets the IgnoreClass value.
getIgnoreClass() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Gets the IgnoreClass value.
getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.AddCluster: Gets ranges of attributes to be ignored.
getIgnoredAttributeIndices() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Gets ranges of attributes to be ignored.
getIgnoredProperties() - Method in class weka.core.CheckGOE: Get the ignored properties used in checkToolTips() as comma-separated list (sorted).
getIgnoreRange() - Method in class weka.filters.unsupervised.attribute.MathExpression: Get the current range selection.
getImage() - Method in class weka.gui.beans.ImageEvent: Get the encapsulated image
getImage(String, String) - Static method in class weka.gui.ComponentHelper: returns the Image for a given directory and filename, NULL if not successful
getImage(String) - Static method in class weka.gui.ComponentHelper: returns the Image for a given filename, NULL if not successful
getImageHeight() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the image height (in pixels)
getImageIcon(String, String) - Static method in class weka.gui.ComponentHelper: returns the ImageIcon for a given filename and directory, NULL if not successful
getImageIcon(String) - Static method in class weka.gui.ComponentHelper: returns the ImageIcon for a given filename, NULL if not successful
getImagEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition: Return the imaginary parts of the eigenvalues
getImageName() - Method in class weka.gui.beans.ImageEvent: Get the name of the image
getImages() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the completed images
getImages() - Method in class weka.knowledgeflow.steps.ImageViewer: Get a map of named images that this step has collected
getImageWidth() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the image width (in pixels)
getImportance() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the importance property.
getImportance() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the importance property.
getImpurityDecreases() - Method in class weka.classifiers.trees.RandomTree: Get the array of impurity decrease/gain sums
getIncludeClass() - Method in class weka.core.InstanceComparator: Returns whether the class is included in the comparison.
getIncludeClass() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Gets whether the class is included in the cleaning process or always skipped.
getIncludeRelationName() - Method in class weka.gui.beans.SerializedModelSaver: Get whether the relation name of the training data used to create the model is to be included in the filename of the serialized model.
getIncludeRelationNameInFilename() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get whether to include the relation name as part of the filename
getIncomingConnectedStepsOfConnectionType(String) - Method in interface weka.knowledgeflow.StepManager: Get a list of steps that are the source of incoming connections of the given type
getIncomingConnectedStepsOfConnectionType(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get a list of steps providing incoming connections of the specified type
getIncomingConnectedStepWithName(String) - Method in interface weka.knowledgeflow.StepManager: Get the named step that is connected with an incoming connection.
getIncomingConnectedStepWithName(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get a named step connected to this step with an incoming connection
getIncomingConnections() - Method in interface weka.knowledgeflow.StepManager: Get a Map of all incoming connections.
getIncomingConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Get the man of upstream (incoming connections) connected steps
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get the list of acceptable incoming connection types
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Appender: Get the incoming connection types accepted by this step at this time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get incoming connections accepted given the current state of the step
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Get a list of incoming connections that this step accepts.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Associator: Get a list of incoming connection types that this step can accept at this time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer: Get a list of incoming connection types that this step can accept at this time
getIncomingConnectionTypes() - Method in interface weka.knowledgeflow.steps.BaseStepExtender: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Block: Get a list of incoming connection types that this step can accept at this time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassAssigner: Get the incoming connections that this step can accept at this time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Classifier
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassValuePicker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Clusterer: Get a list of connection types that could be made to this Step at this point in time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClustererPerformanceEvaluator: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.CostBenefitAnalysis
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataGenerator: Get acceptable incoming connection types.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataGrid
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataVisualizer
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Dummy: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the acceptable incoming connection types at this point in time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Filter: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.GetDataFromResult
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.GraphViewer: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ImageSaver: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ImageViewer: Get a list of acceptable incoming connections - only StepManager.CON_IMAGE in this case
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.InstanceStreamToBatchMaker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Job
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Join: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Loader: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Note: Get incoming connections accepted - none in the case of a note :-)
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.PredictionAppender: Get the incoming connection types that this step accepts
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Saver: Get a list of incoming connection types that this step can receive at this time
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SendToPerspective
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SetPropertiesFromEnvironment: Get a list of acceptable incoming connection types
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SetVariables: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.Sorter: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in interface weka.knowledgeflow.steps.Step: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.StripChart: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.SubstringReplacer: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TestSetMaker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TextSaver: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TextViewer: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TrainingSetMaker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Get a list of incoming connection types that this step can accept.
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.WriteDataToResult
getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.WriteWekaLog: Get a list of acceptable incoming connection types (at this point in time)
getIncomingStructureForConnectionType(String) - Method in interface weka.knowledgeflow.StepManager: Attempt to retrieve the structure (as a header-only set of instances) for the named incoming connection type.
getIncomingStructureForConnectionType(String, Environment) - Method in interface weka.knowledgeflow.StepManager: Attempt to retrieve the structure (as a header-only set of instances) for the named incoming connection type.
getIncomingStructureForConnectionType(String) - Method in class weka.knowledgeflow.StepManagerImpl: Attempt to get the incoming structure (as a header-only set of instances) for the named incoming connection type.
getIncomingStructureForConnectionType(String, Environment) - Method in class weka.knowledgeflow.StepManagerImpl: Attempt to retrieve the structure (as a header-only set of instances) for the named incoming connection type.
getIncomingStructureFromStep(StepManager, String) - Method in interface weka.knowledgeflow.StepManager: Attempt to get the incoming structure (as a header-only set of instances) from the given managed step for the given connection type.
getIncomingStructureFromStep(StepManager, String) - Method in class weka.knowledgeflow.StepManagerImpl: Attempt to get the incoming structure (as a header-only set of instances) from the given managed step for the given connection type.
getIncompatibleDependencies(List<Package>) - Method in class weka.core.packageManagement.DefaultPackage: Gets those packages from the supplied list that this package depends on and are currently incompatible with this package.
getIncompatibleDependencies() - Method in class weka.core.packageManagement.DefaultPackage: Gets a list of installed packages that this package depends on that are currently incompatible with this package.
getIncompatibleDependencies() - Method in class weka.core.packageManagement.Package: Gets a list of installed packages that this package depends on that are currently incompatible with this package.
getIncompatibleDependencies(List<Package>) - Method in class weka.core.packageManagement.Package: Gets those packages from the supplied list that this package depends on and are currently incompatible with this package.
getIncrementalLoggingFrequency() - Method in class weka.knowledgeflow.steps.WriteWekaLog: Get how frequently to write an incremental data point to the log
getIncrementalSaveSchedule() - Method in class weka.gui.beans.SerializedModelSaver: Get how often to save incremental models.
getIncrementalSaveSchedule() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get how frequently to save an incremental model
getIndentationSize() - Method in class weka.gui.scripting.SyntaxDocument: Returns the number of blanks used for indentation.
getIndex() - Method in class weka.core.pmml.jaxbbindings.TimeValue: Gets the value of the index property.
getIndex() - Method in class weka.core.PropertyPath.PathElement: returns the index of the property, -1 if the property is not an index-based one
getIndex() - Method in class weka.core.SingleIndex: Gets the selected index.
getIndex() - Method in class weka.gui.SortedTableModel.SortContainer: Returns the original index of the item.
getIndexedPrimaryResult(int) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Retrieve the primary result corresponding to a given set number
getIndexedValueFromNamedStore(String, Integer) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Gets an indexed value from a named store
getIndices() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Gets the value of the indices property.
getIndices() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Gets the value of the indices property.
getInfoData() - Method in interface weka.gui.visualize.InstanceInfo: Returns the underlying data.
getInfoData() - Method in class weka.gui.visualize.InstanceInfoFrame: Returns the underlying data.
getInfoStep(Class) - Method in interface weka.knowledgeflow.StepManager: Returns a reference to the step being managed if it has one or more outgoing CON_INFO connections and the managed step is of the supplied class
getInfoStep() - Method in interface weka.knowledgeflow.StepManager: Returns a reference to the step being managed if it has one or more outgoing CON_INFO connections.
getInfoStep(Class) - Method in class weka.knowledgeflow.StepManagerImpl: Returns a reference to the step being managed if it has one or more outgoing CON_INFO connections and the managed step is of the supplied class
getInfoStep() - Method in class weka.knowledgeflow.StepManagerImpl: Returns a reference to the step being managed if it has one or more outgoing CON_INFO connections.
getInfoText() - Method in interface weka.gui.visualize.InstanceInfo: Returns the currently displayed info text.
getInfoText() - Method in class weka.gui.visualize.InstanceInfoFrame: Returns the currently displayed info text.
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Gets whether to init as naive bayes
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.global.K2: Gets whether to init as naive bayes
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Gets whether to init as naive bayes
getInitAsNaiveBayes() - Method in class weka.classifiers.bayes.net.search.local.K2: Gets whether to init as naive bayes
getInitFile() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the file to initialize the filter with, can be null.
getInitFileClassIndex() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the class index of the file to initialize the filter with.
getInitGenericObjectEditorFilter() - Static method in class weka.gui.explorer.ExplorerDefaults: returns if the GOEs in the Explorer will be initialized based on the data that is loaded into the Explorer.
getInitial() - Method in class weka.core.Memory: returns the initial size of the JVM heap, obtains a fresh MemoryUsage object to do so.
getInitialCount() - Method in class weka.classifiers.trees.REPTree: Get the value of InitialCount.
getInitialDatasetsDirectory() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the initial directory for the datasets (if empty, it returns the user's home directory).
getInitialDirectory() - Static method in class weka.gui.explorer.ExplorerDefaults: Returns the initial directory for the file chooser used for opening datasets.
getInitializationMethod() - Method in class weka.clusterers.SimpleKMeans: Get the initialization method to use
getInitializer() - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Returns an object to initialize the declared variables
getInitialScore() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the initialScore property.
getInlineTable() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the inlineTable property.
getInlineTable() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the inlineTable property.
getInlineTable() - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Gets the value of the inlineTable property.
getInlineTable() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the inlineTable property.
getInputFilename() - Method in class weka.gui.GenericPropertiesCreator: returns the name of the input file
getInputFormat() - Method in class weka.core.DictionaryBuilder: Gets the currently set input format
getInputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection: Use this to get easy access to the input numbers.
getInputOrder() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the input order.
getInputProperties() - Method in class weka.gui.GenericPropertiesCreator: returns the input properties object (template containing the packages)
getInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection: Use this to get easy access to the inputs.
getInputs() - Method in class weka.gui.beans.MetaBean
getInputStream(String, String) - Static method in class weka.gui.Loader: returns an InputStream for the given dir and filename, can be NULL if it fails
getInputStream(String) - Method in class weka.gui.Loader: returns an InputStream for the given filename, can be NULL if it fails
getInputStructure() - Method in class weka.gui.beans.SubstringLabelerRules: Get the input structure
getInstalledLookAndFeels() - Static method in class weka.gui.LookAndFeel: returns an array with the classnames of all the installed LnFs
getInstalledPackageInfo(String) - Method in class weka.core.packageManagement.DefaultPackageManager: Get package information on the named installed package.
getInstalledPackageInfo(String) - Method in class weka.core.packageManagement.PackageManager: Get package information on the named installed package.
getInstalledPackageInfo(String) - Static method in class weka.core.WekaPackageManager: Get meta data for an installed package
getInstalledPackages() - Method in class weka.core.packageManagement.DefaultPackageManager: Get a list of installed packages.
getInstalledPackages() - Method in class weka.core.packageManagement.PackageManager: Get a list of installed packages.
getInstalledPackages() - Static method in class weka.core.WekaPackageManager: Get a list of installed packages
getInstance() - Method in class weka.gui.beans.InstanceEvent: Get the instance
getInstanceField() - Method in class weka.core.pmml.jaxbbindings.InstanceFields: Gets the value of the instanceField property.
getInstanceFields() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the instanceFields property.
getInstanceIdVariable() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the instanceIdVariable property.
getInstanceRange() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Gets the number of instances forward to translate values between.
getInstances() - Method in class weka.core.converters.AbstractSaver: Gets instances that should be stored.
getInstances() - Method in interface weka.core.DistanceFunction: returns the instances currently set.
getInstances() - Method in class weka.core.FilteredDistance: returns the instances currently set.
getInstances() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: returns the instances currently set.
getInstances() - Method in class weka.core.NormalizableDistance: returns the instances currently set.
getInstances() - Method in class weka.core.xml.XMLInstances: returns the current instances, either the ones that were set or the ones that were generated from the XML structure.
getInstances() - Method in class weka.experiment.PairedTTester: Get the value of Instances.
getInstances() - Method in interface weka.experiment.Tester: Get the value of Instances.
getInstances() - Method in class weka.gui.arffviewer.ArffPanel: returns the instances of the panel, if none then NULL
getInstances() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the data
getInstances() - Method in class weka.gui.arffviewer.ArffTableModel: returns the data
getInstances() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Get the training instances
getInstances() - Method in class weka.gui.explorer.AbstractPlotInstances: Returns the training data.
getInstances() - Method in class weka.gui.explorer.ClassifierPanel: Get the current set of instances
getInstances() - Method in class weka.gui.explorer.DataGeneratorPanel: returns the generated instances, null if the process was cancelled.
getInstances() - Method in class weka.gui.explorer.PreprocessPanel: Gets the working set of instances.
getInstances() - Method in class weka.gui.SetInstancesPanel: Gets the set of instances currently held by the panel.
getInstances() - Method in class weka.gui.treevisualizer.Node: This will return the Instances object related to this node.
getInstances() - Method in class weka.gui.ViewerDialog: returns the currently displayed instances
getInstances() - Method in class weka.gui.visualize.VisualizePanel: Get the master plot's instances
getInstances() - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Get the data to output from this step
getInstances1() - Method in class weka.gui.visualize.VisualizePanelEvent
getInstances2() - Method in class weka.gui.visualize.VisualizePanelEvent
getInstancesFromClass(Instances, int, int, double, Instances) - Static method in class weka.estimators.EstimatorUtils: Returns a dataset that contains all instances of a certain class value.
getInstancesFromClass(Instances, int, double) - Static method in class weka.estimators.EstimatorUtils: Returns a dataset that contains of all instances of a certain class value.
getInstancesFromValue(Instances, int, double) - Static method in class weka.estimators.EstimatorUtils: Returns a dataset that contains of all instances of a certain value for the given attribute.
getInstancesIndices() - Method in class weka.filters.unsupervised.instance.RemoveRange: Gets ranges of instances selected.
getInstancesNoClass() - Method in class weka.associations.Apriori: Gets the instances without the class atrribute.
getInstancesNoClass() - Method in interface weka.associations.CARuleMiner: Gets the instances without the class attribute
getInstancesOnlyClass() - Method in class weka.associations.Apriori: Gets only the class attribute of the instances.
getInstancesOnlyClass() - Method in interface weka.associations.CARuleMiner: Gets the class attribute and its values for all instances
getInstancesValueAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the double value of the underlying Instances object at the given position, -1 if out of bounds
getInstancesValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the double value of the underlying Instances object at the given position, -1 if out of bounds
getINTEntries() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Gets the value of the intEntries property.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get a map of popup viewers that can be used with this step
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.BaseStep: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.CostBenefitAnalysis: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.DataVisualizer
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.GraphViewer: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.ImageViewer: Gets a list of classes of viewers that can be popped up in the GUI Knowledge Flow from this step, given that we have received and stored some image data.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.ScatterPlotMatrix: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in interface weka.knowledgeflow.steps.Step: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.StripChart: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewers() - Method in class weka.knowledgeflow.steps.TextViewer: When running in a graphical execution environment a step can make one or more popup Viewer components available.
getInteractiveViewersImpls() - Method in class weka.knowledgeflow.steps.BaseStep: An alternative to getStepInteractiveViewers that returns a Map of instantiated StepInteractiveViewer objects.
getInteractiveViewersImpls() - Method in interface weka.knowledgeflow.steps.Step: An alternative to getStepInteractiveViewers that returns a Map of instantiated StepInteractiveViewer objects.
getIntercept() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns the intercept of the function.
getIntercept() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Returns the intercept of the function.
getIntercept() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the intercept property.
getInternalCacheSize() - Method in class weka.classifiers.functions.supportVector.StringKernel: Gets the size of the internal cache
getInterpolationMethod() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the interpolationMethod property.
getInterpreter() - Method in class weka.core.scripting.Jython: returns the currently used Python Interpreter
getInterQuartileRange() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the interQuartileRange property.
getInterval() - Method in class weka.core.pmml.jaxbbindings.ContStats: Gets the value of the interval property.
getInterval() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the interval property.
getInterval() - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin: Gets the value of the interval property.
getInterval() - Method in class weka.core.pmml.jaxbbindings.EventValues: Gets the value of the interval property.
getInvalidFreq() - Method in class weka.core.pmml.jaxbbindings.Counts: Gets the value of the invalidFreq property.
getInvalidValueTreatment() - Method in class weka.core.pmml.jaxbbindings.Apply: Gets the value of the invalidValueTreatment property.
getInvalidValueTreatment() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the invalidValueTreatment property.
getInvert() - Method in class weka.core.InstanceComparator: Returns whether the matching sense of the attribute range is inverted.
getInvert() - Method in class weka.core.Range: Gets whether the range sense is inverted, i.e.
getInvert() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Get whether selection is inverted.
getInvertSelection() - Method in class weka.core.converters.DictionarySaver: Gets whether the supplied columns are to be processed or skipped.
getInvertSelection() - Method in class weka.core.DictionaryBuilder: Gets whether the supplied columns are to be processed or skipped.
getInvertSelection() - Method in interface weka.core.DistanceFunction: Gets whether the matching sense of attribute indices is inverted or not.
getInvertSelection() - Method in class weka.core.FilteredDistance: Gets whether the matching sense of attribute indices is inverted or not.
getInvertSelection() - Method in class weka.core.NormalizableDistance: Gets whether the matching sense of attribute indices is inverted or not.
getInvertSelection() - Method in class weka.filters.supervised.attribute.Discretize: Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Get whether the supplied attributes are to be acted on or all other attributes.
getInvertSelection() - Method in class weka.filters.supervised.instance.Resample: Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).
getInvertSelection() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Copy: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Gets whether the supplied columns are to be worked on or the others.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets whether the supplied columns are to be processed or skipped.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.MathExpression: Get whether the supplied columns are to be select or unselect
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Get whether the supplied attributes are to be acted on or all other attributes.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Gets whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Gets whether the selection of the columns is inverted
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Gets whether the supplied columns are to be worked on or the others.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Gets whether the supplied columns are to be worked on or the others.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Gets whether the supplied columns are to be worked on or the others.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Get whether the supplied columns are to be transformed or not
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Get whether to invert the selection - i.e.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.Remove: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Get whether the supplied columns are to be removed or kept.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RemoveType: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Gets whether to invert the selection of the attributes.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Gets whether the supplied columns are to be worked on or the others.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.SortLabels: Gets whether the supplied columns are to be processed or skipped.
getInvertSelection() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets whether the supplied columns are to be processed or skipped.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveRange: Gets if selection is to be inverted.
getInvertSelection() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Get whether the supplied columns are to be removed or kept
getInvertSelection() - Method in class weka.filters.unsupervised.instance.Resample: Gets whether selection is inverted (only if instances are drawn WIHTOUT replacement).
getIRClassValue() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the class value (label or index) to use with IR metric evaluation of subsets.
getIRClassValue() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get the class value (label or index) to use with IR metric evaluation of subsets.
getIRClassValue() - Method in class weka.attributeSelection.WrapperSubsetEval: Get the class value (label or index) to use with IR metric evaluation of subsets.
getIsCenterField() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the isCenterField property.
getIsCyclic() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the isCyclic property.
getIsMultiValued() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the isMultiValued property.
getIsRecursive() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the isRecursive property.
getItemRef() - Method in class weka.core.pmml.jaxbbindings.ItemRef: Gets the value of the itemRef property.
getItemRef() - Method in class weka.core.pmml.jaxbbindings.Itemset: Gets the value of the itemRef property.
getItems() - Method in class weka.associations.ItemSet: Get the item array
getItemValueAsString() - Method in class weka.associations.Item: Get this item's value as a String.
getItemValueAsString() - Method in class weka.associations.NominalItem: Get this item's value as a String.
getItemValueAsString() - Method in class weka.associations.NumericItem: Get this item's value as a String.
getIterativeClassifier() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the classifier used as the base learner.
getJaccard() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the jaccard property.
getJavaInitializationString() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getJavaInitializationString() - Method in class weka.gui.ColorEditor: Don't really need this
getJavaInitializationString() - Method in class weka.gui.CostMatrixEditor: Returns the Java code that generates an object the same as the one being edited.
getJavaInitializationString() - Method in class weka.gui.EnvironmentField
getJavaInitializationString() - Method in class weka.gui.FileEditor: Returns a representation of the current property value as java source.
getJavaInitializationString() - Method in class weka.gui.GenericArrayEditor: Supposedly returns an initialization string to create a classifier identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString() - Method in class weka.gui.GenericObjectEditor: Supposedly returns an initialization string to create a Object identical to the current one, including it's state, but this doesn't appear possible given that the initialization string isn't supposed to contain multiple statements.
getJavaInitializationString() - Method in class weka.gui.PasswordField
getJavaInitializationString() - Method in class weka.gui.RangeEditor: Returns a description of the property value as java source.
getJavaInitializationString() - Method in class weka.gui.SelectedTagEditor: Returns a description of the property value as java source.
getJavaInitializationString() - Method in class weka.gui.SimpleDateFormatEditor: Returns the Java code that generates an object the same as the one being edited.
getJTable() - Method in class weka.gui.JTableHelper: returns the JTable
getKeepDictionarySorted() - Method in class weka.core.converters.DictionarySaver: Get whether to keep the dictionary sorted alphabetically or not
getKernel() - Method in class weka.classifiers.functions.GaussianProcesses: Gets the kernel to use.
getKernel() - Method in class weka.classifiers.functions.SMO.BinarySMO: Returns the kernel to use
getKernel() - Method in class weka.classifiers.functions.SMO: Returns the kernel to use
getKernel() - Method in class weka.classifiers.functions.SMOreg: Returns the kernel to use
getKernel() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Get the kernel being tested
getKernel() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the kernel to use.
getKernelBandwidth() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Get the kernel bandwidth
getKernelBandwidth() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the kernel bandwidth
getKernelEvaluations() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: returns the number of kernel evaluations
getKernelFactorExpression() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the expression for the kernel.
getKernelMatrixFile() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Gets the file containing the kernel matrix.
getKey() - Method in class weka.core.Settings.SettingKey: Get the key of this setting
getKey() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the key describing the current SplitEvaluator.
getKey() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the key describing the current SplitEvaluator.
getKey() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the key describing the current SplitEvaluator.
getKey() - Method in interface weka.experiment.SplitEvaluator: Gets the key describing the current SplitEvaluator.
getKeyFieldName() - Method in class weka.experiment.AveragingResultProducer: Get the value of KeyFieldName.
getKeyNames() - Method in class weka.experiment.AveragingResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in class weka.experiment.CrossValidationResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.DatabaseResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.LearningRateResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.RandomSplitResultProducer: Gets the names of each of the columns produced for a single run.
getKeyNames() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in interface weka.experiment.ResultProducer: Gets the names of each of the key columns produced for a single run.
getKeyNames() - Method in interface weka.experiment.SplitEvaluator: Gets the names of each of the key columns produced for a single run.
getKeys() - Method in class weka.core.converters.DatabaseLoader: Gets the key columns' name
getKeySpec() - Method in class weka.gui.beans.Join: Get the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)
getKeySpec() - Method in class weka.knowledgeflow.steps.Join: Get the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)
getKeyTypes() - Method in class weka.experiment.AveragingResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.CrossValidationResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.DatabaseResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.LearningRateResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.RandomSplitResultProducer: Gets the data types of each of the columns produced for a single run.
getKeyTypes() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in interface weka.experiment.ResultProducer: Gets the data types of each of the key columns produced for a single run.
getKeyTypes() - Method in interface weka.experiment.SplitEvaluator: Gets the data types of each of the key columns produced for a single run.
getKeywordFormatting(String) - Method in class weka.gui.scripting.SyntaxDocument: Gets the formatting for a keyword.
getKeywords() - Method in class weka.experiment.DatabaseUtils: Returns the currently stored keywords (as comma-separated list).
getKeywordsMaskChar() - Method in class weka.experiment.DatabaseUtils: Returns the currently set mask character.
getKind() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the kind property.
getKind() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the kind property.
getKNN() - Method in class weka.classifiers.lazy.IBk: Gets the number of neighbours the learner will use.
getKNN() - Method in class weka.classifiers.lazy.LWL: Gets the number of neighbours used for kernel bandwidth setting.
getKNNInput() - Method in class weka.core.pmml.jaxbbindings.KNNInputs: Gets the value of the knnInput property.
getKohonenMap() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the kohonenMap property.
getKValue() - Method in class weka.classifiers.trees.RandomTree: Get the value of K.
getKWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated bias squared according to the Kohavi and Wolpert definition
getKWSigma() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated sigma according to the Kohavi and Wolpert definition
getKWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated variance according to the Kohavi and Wolpert definition
getL() - Method in class weka.core.matrix.CholeskyDecomposition: Return triangular factor.
getL() - Method in class weka.core.Matrix: Deprecated.

Returns the L part of the matrix.
getL() - Method in class weka.core.matrix.LUDecomposition: Return lower triangular factor
getLabel() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Gets the value of the label property.
getLabel() - Method in class weka.core.pmml.jaxbbindings.Parameter: Gets the value of the label property.
getLabel() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Get the label for the new merged class.
getLabel() - Method in class weka.gui.beans.BatchClassifierEvent: Get the label for this event
getLabel() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get the label to assign if this rule matches, or empty string if binary flag attribute is being created.
getLabel() - Method in class weka.gui.treevisualizer.Edge: Get the value of label.
getLabel() - Method in class weka.gui.treevisualizer.Node: Get the value of label.
getLabels() - Method in class weka.filters.unsupervised.attribute.AddValues: Get the comma-separated list of labels that are added.
getLambda() - Method in class weka.classifiers.functions.SGD: Get the current value of lambda
getLambda() - Method in class weka.classifiers.functions.SGDText: Get the current value of lambda
getLambda() - Method in class weka.classifiers.functions.supportVector.StringKernel: Gets the lambda constant used in the string kernel
getLatestCompatibleVersion(String) - Static method in class weka.core.WekaPackageManager: Get the latest version of the named package that is compatible with the base version of Weka being used.
getLaunchCommand() - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin: Get the name of the launch command (to appear as the button text or in the popup menu)
getLaunchCommand() - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin: Get the name of the launch command (to appear as the button text or in the popup menu)
getLaunchStartPointsSequentially() - Method in class weka.knowledgeflow.FlowRunner: Get whether to launch start points sequentially
getLayoutAt(int) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the flow layout at the supplied index
getLeafPredictionStrategy() - Method in class weka.classifiers.trees.HoeffdingTree: Get the leaf prediction strategy to use (majority class, naive Bayes or naive Bayes adaptive)
getLearningRate() - Method in class weka.classifiers.functions.MultilayerPerceptron
getLearningRate() - Method in class weka.classifiers.functions.SGD: Get the learning rate.
getLearningRate() - Method in class weka.classifiers.functions.SGDText: Get the learning rate.
getLeaveOneAttributeOut() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get whether to evaluate the merit of an attribute based on the impact of leaving it out from the full set instead of considering its worth in isolation
getLeftMargin() - Method in class weka.core.pmml.jaxbbindings.Interval: Gets the value of the leftMargin property.
getLegendText() - Method in class weka.gui.beans.ChartEvent: Get the legend text vector
getLength() - Method in class weka.core.pmml.jaxbbindings.TextDocument: Gets the value of the length property.
getLength() - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Gets the value of the length property.
getLengthLimit() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the lengthLimit property.
getLevel() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the level property.
getLevel() - Method in class weka.gui.HierarchyPropertyParser: Get the level of current node.
getLeverage() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the leverage property.
getLHSAttName() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Get the lhs attribute name
getLift() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the lift property.
getLift() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the lift property.
getLiftData() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the liftData property.
getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph: Gets the value of the liftGraph property.
getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph: Gets the value of the liftGraph property.
getLiftGraph() - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph: Gets the value of the liftGraph property.
getLikelihoodThreshold() - Method in class weka.classifiers.meta.LogitBoost: Get the value of Precision.
getLine(int) - Method in class weka.gui.treevisualizer.Edge: Returns line number n
getLine(int) - Method in class weka.gui.treevisualizer.Node: Returns the text String for the specfied line.
getLinearNorm() - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Gets the value of the linearNorm property.
getLineNo() - Method in class weka.core.converters.ArffLoader.ArffReader: returns the current line number
getLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2: returns the element (Link) at a specific index from the list.
getLinkFunction() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the linkFunction property.
getLinkParameter() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the linkParameter property.
getLinkType() - Method in class weka.clusterers.HierarchicalClusterer
getList() - Method in class weka.gui.ResultHistoryPanel: Gets the JList used by the results list
getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.CheckBoxList.CheckBoxListRenderer: Return a component that has been configured to display the specified value.
getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer: Return a component that has been configured to display the specified value.
getListCellRendererComponent(JList, Object, int, boolean, boolean) - Method in class weka.gui.sql.InfoPanelCellRenderer: Return a component that has been configured to display the specified value.
getLNorm() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get the L Norm used.
getLNorm() - Method in class weka.classifiers.functions.SGDText: Get the L Norm used.
getLoadClassifierFileName() - Method in class weka.gui.beans.Classifier: Get the name of the classifier to load at execution time.
getLoadClassifierFileName() - Method in class weka.knowledgeflow.steps.Classifier: Get the name of the classifier to load at execution time.
getLoadClustererFileName() - Method in class weka.knowledgeflow.steps.Clusterer: Get the name of the clusterer to load at execution time.
getLoadedPerspectives() - Method in class weka.gui.PerspectiveManager: Get a list of all loaded perspectives.
getLoader() - Method in class weka.core.converters.ConverterUtils.DataSource: returns the determined loader, null if the DataSource was initialized with data alone and not a file/URL.
getLoader() - Method in class weka.gui.beans.Loader: Get the loader
getLoader() - Method in class weka.gui.ConverterFileChooser: returns the loader that was chosen by the user, can be null in case the user aborted the dialog or the save dialog was shown.
getLoader() - Method in class weka.gui.SetInstancesPanel: Gets the currently used Loader.
getLoader() - Method in class weka.knowledgeflow.steps.Loader: Convenience method - calls getWrappedAlgorithm()
getLoaderForClass(String) - Method in class weka.core.WekaPackageClassLoaderManager: Attempts to locate a classloader for the named class.
getLoaderForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loader to use for this kind of extension, returns null if none can be found.
getLoaderForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loader to use for this kind of file, returns null if none can be found.
getLoaderForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loader to use for this kind of file, returns null if none can be found.
getLoadersForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loader to use for this kind of extension, returns null if none can be found.
getLoadersForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loaders to use for this kind of file.
getLoadersForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the loaders to use for this kind of file.
getLocallyPredictive() - Method in class weka.attributeSelection.CfsSubsetEval: Return true if including locally predictive attributes
getLocalModel() - Method in class weka.classifiers.trees.j48.ClassifierTree
getLocalTermWeights() - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Gets the value of the localTermWeights property.
getLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the localTransformations property.
getLocalTransformations() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the localTransformations property.
getLocator(int) - Method in class weka.core.AttributeLocator: Returns the AttributeLocator at the given index.
getLocatorIndices() - Method in class weka.core.AttributeLocator: Returns the indices of the AttributeLocator objects.
getLog() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get the logger.
getLog() - Method in class weka.core.Debug.Random: the currently used log, if null then stdout is used for outputting the debugging information
getLog() - Method in interface weka.core.LogHandler: Get the log in use
getLog() - Method in interface weka.core.pmml.PMMLModel: Get the logger.
getLog() - Method in class weka.gui.explorer.ClassifierPanel: Get the log
getLog() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get the log in use
getLog() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get the log in use
getLog() - Method in class weka.knowledgeflow.LogManager: Get the wrapped log
getLog() - Method in interface weka.knowledgeflow.StepManager: Get the log
getLog() - Method in class weka.knowledgeflow.StepManagerImpl: Get the log to use
getLogger() - Method in interface weka.knowledgeflow.FlowExecutor: Get the log in use
getLogger() - Method in class weka.knowledgeflow.FlowRunner: Get the log to use
getLoggingLevel() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get the logging level in use
getLoggingLevel() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get the logging level in use
getLoggingLevel() - Method in interface weka.knowledgeflow.FlowExecutor: Get the logging level to log at
getLoggingLevel() - Method in class weka.knowledgeflow.FlowRunner: Get the logging level to use
getLoggingLevel() - Method in class weka.knowledgeflow.LogManager: Get the logging level in use
getLoggingLevel() - Method in interface weka.knowledgeflow.StepManager: Get the currently set logging level
getLoggingLevel() - Method in class weka.knowledgeflow.StepManagerImpl: Get the logging level in use
getLoggingLevel() - Method in class weka.knowledgeflow.steps.WriteWekaLog: Get the logging level to use
getLogLikelihood() - Method in class weka.clusterers.ClusterEvaluation: Return the log likelihood corresponding to the most recent set of instances clustered.
getLogLossDecoding() - Method in class weka.classifiers.meta.MultiClassClassifier: Whether log loss decoding is used for random or exhaustive codes.
getLogPanel(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getLogPanel() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the log panel in use by this layout
getLookAheadIterations() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of LookAheadIterations.
getLookupCacheSize() - Method in class weka.attributeSelection.BestFirst: Return the maximum size of the evaluated subset cache (expressed as a multiplier for the number of attributes in a data set.
getLossFunction() - Method in class weka.classifiers.functions.SGD: Get the current loss function.
getLossFunction() - Method in class weka.classifiers.functions.SGDText: Get the current loss function.
getLower() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution: Gets the value of the lower property.
getLower() - Method in class weka.gui.experiment.RunNumberPanel: Gets the current lower run number.
getLowerBound() - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Get the lower bound of this range
getLowerBoundMinSupport() - Method in class weka.associations.Apriori: Get the value of lowerBoundMinSupport.
getLowerBoundMinSupport() - Method in class weka.associations.FPGrowth: Get the value of lowerBoundMinSupport.
getLowercaseTokens() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get whether to convert all tokens to lowercase
getLowercaseTokens() - Method in class weka.classifiers.functions.SGDText: Get whether to convert all tokens to lowercase
getLowerCaseTokens() - Method in class weka.core.converters.DictionarySaver: Gets whether if the tokens are to be downcased or not.
getLowerCaseTokens() - Method in class weka.core.DictionaryBuilder: Gets whether if the tokens are to be downcased or not.
getLowerCaseTokens() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets whether if the tokens are to be downcased or not.
getLowerCaseTokens() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets whether if the tokens are to be downcased or not.
getLowerComparison() - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Get the lower comparison
getLowerNumericBound() - Method in class weka.core.Attribute: Returns the lower bound of a numeric attribute.
getLowerSize() - Method in class weka.experiment.LearningRateResultProducer: Get the value of LowerSize.
getLowValue() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the lowValue property.
getM5RootNode() - Method in class weka.classifiers.trees.m5.M5Base
getM5RootNode() - Method in class weka.classifiers.trees.m5.Rule
getMacro(String) - Method in class weka.core.expressionlanguage.common.IfElseMacro: Tries to fetch the macro
getMacro(String) - Method in class weka.core.expressionlanguage.common.JavaMacro
getMacro(String) - Method in class weka.core.expressionlanguage.common.MacroDeclarationsCompositor: Tries to fetch a macro from one of the combined declarations.
getMacro(String) - Method in class weka.core.expressionlanguage.common.MathFunctions: Tries to fetch the macro
getMacro(String) - Method in class weka.core.expressionlanguage.common.NoMacros: Tries to fetch a macro.
getMacro(String) - Method in interface weka.core.expressionlanguage.core.MacroDeclarations: Tries to fetch the macro
getMacro(String) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Tries to fetch a macro
getMainApplication() - Method in class weka.gui.AbstractPerspective: Get the main application that this perspective belongs to
getMainApplication() - Method in interface weka.gui.Perspective: Get the main application that this perspective belongs to
getMainApplication() - Method in class weka.gui.SimpleCLIPanel
getMainKFPerspective() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Get the main knowledge flow perspective.
getMainKFPerspective() - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Get the main knowledge flow perspective.
getMainPanel() - Method in class weka.gui.arffviewer.ArffViewer: returns the main panel
getMainPerspective() - Method in class weka.gui.beans.KnowledgeFlowApp: Gets the main knowledge flow perspective
getMainPerspective() - Method in interface weka.gui.GUIApplication: Get the main Perspective of this application - i.e.
getMainPerspective() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the main perspective of this application
getMainPerspective() - Method in class weka.gui.PerspectiveManager: Get the main application perspective.
getMainPerspective() - Method in class weka.gui.WorkbenchApp: Get the main perspective of this application.
getMainToolBar() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the main toolbar
getMakeBinary() - Method in class weka.filters.supervised.attribute.Discretize: Gets whether binary attributes should be made for discretized ones.
getMakeBinary() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets whether binary attributes should be made for discretized ones.
getMakeResourceIntensive() - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Get whether downstream steps are to be made resource intensive
getManagedStep() - Method in interface weka.knowledgeflow.StepManager: Get the actual step managed by this step manager
getManagedStep() - Method in class weka.knowledgeflow.StepManagerImpl: Get the step managed by this manager
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.Apply: Gets the value of the mapMissingTo property.
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.Discretize: Gets the value of the mapMissingTo property.
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.FieldRef: Gets the value of the mapMissingTo property.
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the mapMissingTo property.
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Gets the value of the mapMissingTo property.
getMapMissingTo() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Gets the value of the mapMissingTo property.
getMappedClassIndex() - Method in class weka.classifiers.misc.InputMappedClassifier
getMappedValue() - Method in class weka.core.pmml.jaxbbindings.Item: Gets the value of the mappedValue property.
getMapValues() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the mapValues property.
getMapValues() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the mapValues property.
getMapValues() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the mapValues property.
getMargin(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: return marginal distibution for a node
getMargin(int) - Method in class weka.classifiers.bayes.net.MarginCalculator
getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
getMarkovBlanketClassifier() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
getMasterPlot() - Method in class weka.gui.CostBenefitAnalysisPanel: Get the master threshold plot data
getMasterPlot() - Method in class weka.gui.visualize.Plot2D: Get the master plot
getMatCell() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the matCell property.
getMatch() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get the string/regex to use for matching
getMatch() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Get the string/regex to use for matching
getMatchAttributeName() - Method in class weka.gui.beans.SubstringLabeler
getMatchAttributeName() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get the name of the new attribute that is created to indicate the match
getMatchDetails() - Method in class weka.gui.beans.SubstringLabeler: Get the internally encoded list of match rules
getMatchDetails() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get the internally encoded list of match rules
getMatches() - Method in class weka.core.FindWithCapabilities: returns the matches from the last find call.
getMatches(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns all the matches with the partial search string, files or classes.
getMatchMissingValues() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Gets whether missing values are counted as a match.
getMatchReplaceDetails() - Method in class weka.gui.beans.SubstringReplacer: Get the internally encoded list of match-replace rules
getMatchReplaceDetails() - Method in class weka.knowledgeflow.steps.SubstringReplacer: Get the internally encoded list of match-replace rules
getMatrix(int, int, int, int) - Method in class weka.core.matrix.Matrix: Get a submatrix.
getMatrix(int[], int[]) - Method in class weka.core.matrix.Matrix: Get a submatrix.
getMatrix(int, int, int[]) - Method in class weka.core.matrix.Matrix: Get a submatrix.
getMatrix(int[], int, int) - Method in class weka.core.matrix.Matrix: Get a submatrix.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.Comparisons: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.CorrelationValues: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.Covariances: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix: Gets the value of the matrix property.
getMatrix() - Method in class weka.core.pmml.jaxbbindings.Predictor: Gets the value of the matrix property.
getMax() - Method in class weka.core.Memory: returns the maximum size of the JVM heap, obtains a fresh MemoryUsage object to do so.
getMax() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the max property.
getMax() - Method in class weka.core.pmml.jaxbbindings.Time: Gets the value of the max property.
getMax() - Method in class weka.gui.beans.ChartEvent: Get the max y value
getMaxArray() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the calculated maximum values for the attributes in the data.
getMaxBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of maxBoostingIterations.
getMaxC() - Method in class weka.gui.visualize.Plot2D: Return the current max value of the colouring attribute
getMaxCardinality() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: returns the max cardinality
getMaxCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the maximum of coords per point.
getMaxCost(int) - Method in class weka.classifiers.CostMatrix: Gets the maximum cost for a particular class value.
getMaxCost(int, Instance) - Method in class weka.classifiers.CostMatrix: Gets the maximum cost for a particular class value.
getMaxCount() - Method in class weka.filters.supervised.instance.SpreadSubsample: Gets the value for the max count
getMaxDecimalPlaces() - Method in class weka.core.converters.ArffSaver: Get the maximum number of decimal places to print
getMaxDecimalPlaces() - Method in class weka.core.converters.CSVSaver: Get the maximum number of decimal places to print
getMaxDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the maximum default.
getMaxDepth() - Method in class weka.classifiers.trees.RandomForest: Get the maximum depth of trh tree, 0 for unlimited.
getMaxDepth() - Method in class weka.classifiers.trees.RandomTree: Get the maximum depth of trh tree, 0 for unlimited.
getMaxDepth() - Method in class weka.classifiers.trees.REPTree: Get the value of MaxDepth.
getMaxDepth() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the depth of the built tree.
getMaximum() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the maximum property.
getMaximum() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the maximum property.
getMaximumAntConsSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumAntConsSeparationTime property.
getMaximumAttributeNames() - Method in class weka.attributeSelection.PrincipalComponents: Gets maximum number of attributes to include in transformed attribute names.
getMaximumAttributeNames() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Gets maximum number of attributes to include in transformed attribute names.
getMaximumAttributes() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Gets maximum number of PC attributes to retain.
getMaximumItemsetSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumItemsetSeparationTime property.
getMaximumNumberOfAntecedentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumNumberOfAntecedentItems property.
getMaximumNumberOfClusters() - Method in class weka.clusterers.EM: Get the maximum number of clusters to consider when cross-validating
getMaximumNumberOfConsequentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumNumberOfConsequentItems property.
getMaximumNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumNumberOfItems property.
getMaximumTotalSequenceTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the maximumTotalSequenceTime property.
getMaximumVariancePercentageAllowed() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Gets the maximum variance attributes are allowed to have before they are deleted by the filter.
getMaxInfoGain() - Method in class weka.classifiers.rules.JRip.Antd
getMaxInstancesInLeaf() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the maximum number of instances allowed in a leaf.
getMaxInstInLeaf() - Method in class weka.core.neighboursearch.KDTree: Get the maximum number of instances in a leaf.
getMaxInstNum() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the upper boundary for instances per cluster.
getMaxInstNum() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Gets the upper boundary for instances per cluster.
getMaxIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: returns the maximum of internal nodes visited.
getMaxIterations() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns the maxIterations parameter.
getMaxIterations() - Method in class weka.clusterers.EM: Get the maximum number of iterations
getMaxIterations() - Method in class weka.clusterers.SimpleKMeans: gets the number of maximum iterations to be executed.
getMaxIterations() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the maximum number of cleansing iterations performed
getMaxIts() - Method in class weka.classifiers.functions.Logistic: Get the value of MaxIts.
getMaxK() - Method in class weka.classifiers.functions.VotedPerceptron: Get the value of maxK.
getMaxLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the maximum number of leaves visited.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Gets the max number of parents.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.global.K2: Gets the max number of parents.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Gets the max number of parents.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.K2: Gets the max number of parents.
getMaxNrOfParents() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Gets the max number of parents.
getMaxNumberOfItems() - Method in class weka.associations.FPGrowth: Gets the maximum number of items to be included in large item sets.
getMaxNumberOfItemsPerTA() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the maxNumberOfItemsPerTA property.
getMaxNumberOfItemsPerTransaction() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the maxNumberOfItemsPerTransaction property.
getMaxNumberOfTAsPerTAGroup() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the maxNumberOfTAsPerTAGroup property.
getMaxNumCandidateCanopiesToHoldInMemory() - Method in class weka.clusterers.Canopy: Get the maximum number of candidate canopies to retain in memory during training.
getMaxNumComponents() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the number of components to use.
getMaxPlots() - Method in class weka.gui.beans.AttributeSummarizer: Get the number of plots to display
getMaxPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the maximum of points visited.
getMaxRadius() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the upper boundary for the radiuses of the clusters.
getMaxRange() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the upper boundary for the range of x
getMaxRelativeLeafRadius() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the maximum relative radius of a leaf node.
getMaxRows() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the maximum number of rows to retrieve.
getMaxRows() - Method in class weka.gui.sql.QueryPanel: returns the current value for the maximum number of rows.
getMaxRows() - Method in class weka.gui.sql.ResultSetHelper: the maximum number of rows to retrieve, less than 1 means unlimited.
getMaxRuleSize() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the maximum number of tests in rules.
getMaxRunNumber() - Method in class weka.gui.beans.BatchClassifierEvent: Get the maximum run number
getMaxRunNumber() - Method in class weka.gui.beans.TestSetEvent: Get the maximum number of runs.
getMaxRunNumber() - Method in class weka.gui.beans.TrainingSetEvent: Get the maximum number of runs.
getMaxSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent: Get the maximum set number (ie the total number of training and testing sets in the series).
getMaxSetNumber() - Method in class weka.gui.beans.BatchClustererEvent: Get the maximum set number (ie the total number of training and testing sets in the series).
getMaxSetNumber() - Method in class weka.gui.beans.TestSetEvent: Get the maximum set number
getMaxSetNumber() - Method in class weka.gui.beans.TrainingSetEvent: Get the maximum set number
getMaxSubsequenceLength() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the maximum length of the subsequence
getMaxThreshold() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the maximum threshold.
getMaxTime() - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables: Gets the value of the maxTime property.
getMaxTime() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Gets the value of the maxTime property.
getMaxValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getMaxVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin: Get the maximum version of Weka, exclusive, the class is designed to work with.
getMaxX() - Method in class weka.gui.visualize.Plot2D: Return the current max value of the attribute plotted on the x axis
getMaxXBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).
getMaxY() - Method in class weka.gui.visualize.Plot2D: Return the current max value of the attribute plotted on the y axis
getMaxYBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Gets the maximum x-coordinate bound, in training-instance units (not mouse coordinates).
getMean() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution: Gets the value of the mean property.
getMean() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution: Gets the value of the mean property.
getMean() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the mean property.
getMean() - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution: Gets the value of the mean property.
getMean() - Method in class weka.core.pmml.jaxbbindings.Time: Gets the value of the mean property.
getMean() - Method in class weka.estimators.MultivariateGaussianEstimator: Returns the mean vector.
getMean() - Method in class weka.estimators.NormalEstimator: Return the value of the mean of this normal estimator.
getMean(int, int) - Method in class weka.experiment.ResultMatrix: returns the mean at the given position, if the position is valid, otherwise 0.
getMeanAbsoluteError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the meanAbsoluteError property.
getMeanCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the mean of coords per point.
getMeanError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the meanError property.
getMeanIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the mean of internal nodes visited.
getMeanLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the mean of number of leaves visited.
getMeanOfSquares() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the meanOfSquares property.
getMeanPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the mean of points visited.
getMeanPrec() - Method in class weka.experiment.ResultMatrix: returns the current precision for the means.
getMeanPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default precision for the mean.
getMeans() - Method in class weka.estimators.KernelEstimator: Return the means of the kernels.
getMeanSquared() - Method in class weka.classifiers.lazy.IBk: Gets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
getMeanSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the meanSquaredError property.
getMeanValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getMeanWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the mean.
getMeasure(String) - Method in class weka.classifiers.bayes.BayesNet: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.functions.SimpleLogistic: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.functions.SMOreg: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.lazy.IBk: Returns the value of the named measure from the neighbour search algorithm, plus the chosen K in case cross-validation is enabled.
getMeasure(String) - Method in class weka.classifiers.lazy.LWL: Returns the value of the named measure from the neighbour search algorithm.
getMeasure(String) - Method in class weka.classifiers.meta.AdditiveRegression: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.meta.Bagging: Returns the value of the named measure.
getMeasure(String) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.DecisionTable: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.JRip: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.rules.PART: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.J48: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.LMT: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.m5.M5Base: Returns the value of the named measure
getMeasure(String) - Method in class weka.classifiers.trees.REPTree: Returns the value of the named measure.
getMeasure(String) - Method in interface weka.core.AdditionalMeasureProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.core.neighboursearch.BallTree: Returns the value of the named measure.
getMeasure(String) - Method in class weka.core.neighboursearch.CoverTree: Returns the value of the named measure.
getMeasure(String) - Method in class weka.core.neighboursearch.KDTree: Returns the value of the named measure.
getMeasure(String) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the value of the named measure.
getMeasure(String) - Method in class weka.core.neighboursearch.PerformanceStats: Returns the value of the named measure.
getMeasure(String) - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the value of the named measure.
getMeasure(String) - Method in class weka.experiment.AveragingResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.CrossValidationResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.DatabaseResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the value of the named measure.
getMeasure(String) - Method in class weka.experiment.LearningRateResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.RandomSplitResultProducer: Returns the value of the named measure
getMeasure(String) - Method in class weka.experiment.RegressionSplitEvaluator: Returns the value of the named measure
getMeasurePerformance() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Gets whether performance statistics are being calculated or not.
getMedian() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the median property.
getMembershipValues(Instance) - Method in class weka.classifiers.meta.Bagging: Computes an array that indicates leaf membership
getMembershipValues(Instance) - Method in class weka.classifiers.meta.FilteredClassifier: Computes an array that has a value for each element in the partition.
getMembershipValues(Instance) - Method in class weka.classifiers.meta.RandomCommittee: Computes an array that indicates leaf membership
getMembershipValues(Instance) - Method in class weka.classifiers.trees.j48.ClassifierTree: Computes a list that indicates node membership
getMembershipValues(Instance) - Method in class weka.classifiers.trees.J48: Computes an array that indicates node membership.
getMembershipValues(Instance) - Method in class weka.classifiers.trees.RandomTree: Computes array that indicates node membership.
getMembershipValues(Instance) - Method in class weka.classifiers.trees.REPTree: Computes array that indicates node membership.
getMembershipValues(Instance) - Method in interface weka.core.PartitionGenerator: Computes an array that has a value for each element in the partition.
getMenu() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the menu bar to be added in a frame
getMenuBar() - Method in class weka.classifiers.bayes.net.GUI: Get the menu bar for this application.
getMenuBar() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin: Return the menu bar for this plugin
getMenuBar() - Method in class weka.gui.scripting.FileScriptingPanel: Returns the menu bar to to be displayed in the frame.
getMenuBar() - Method in class weka.gui.scripting.ScriptingPanel: Returns the menu bar to to be displayed in the frame.
getMenuBar() - Method in class weka.gui.SimpleCLIPanel: Not supported.
getMenuEntryText() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin: Get the text entry to appear in the menu
getMenuItem(String) - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar
getMenus() - Method in class weka.gui.AbstractPerspective: Get an ordered list of menus to appear in the main menu bar.
getMenus() - Method in class weka.gui.explorer.PreprocessPanel
getMenus() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get an ordered list of menus to appear in the main menu bar.
getMenus() - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar: Get the list of menus
getMenus() - Method in interface weka.gui.Perspective: Get an ordered list of menus to appear in the main menu bar.
getMenus() - Method in class weka.gui.SimpleCLIPanel
getMenuTitle() - Method in interface weka.gui.MainMenuExtension: Returns the name of the menu item.
getMenuToDisplayIn() - Method in interface weka.gui.GUIChooser.GUIChooserMenuPlugin: Get the menu that the plugin is to be listed in
getMergeValueRange() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Get the range of the merge values used.
getMetaClassifier() - Method in class weka.classifiers.meta.Stacking: Gets the meta classifier.
getMetadata() - Method in class weka.core.Attribute: Returns the properties supplied for this attribute.
getMetaData() - Method in class weka.core.converters.DatabaseConnection: Gets meta data for the database connection object.
getMetadata() - Method in class weka.core.Settings.SettingKey: Get the metadata for this setting
getMetadataElement(String) - Method in class weka.core.Settings.SettingKey: Get a piece of metadata for this setting
getMetadataElement(String, String) - Method in class weka.core.Settings.SettingKey: Get a peice of metadata for this setting
getMetaStore() - Static method in class weka.gui.beans.BeansProperties: Get the metastore
getMethod() - Method in class weka.classifiers.functions.neural.NeuralNode
getMethod() - Method in class weka.classifiers.meta.MultiClassClassifier: Gets the method used.
getMethod() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Gets the value of the method property.
getMethodName() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Get the transformation method.
getMetricDescription() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Get a short description of this metric (algorithm, forumulas etc.).
getMetricName() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Get the name of this metric
getMetricNamesForRule() - Method in class weka.associations.AssociationRule: Return the names of the metrics available for this rule.
getMetricNamesForRule() - Method in class weka.associations.DefaultAssociationRule
getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.GiniSplitMetric
getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.InfoGainSplitMetric
getMetricRange(Map<String, WeightMass>) - Method in class weka.classifiers.trees.ht.SplitMetric: Get the range of the splitting metric
getMetricsToDisplay() - Method in class weka.classifiers.evaluation.Evaluation: Get a list of the names of metrics to have appear in the output The default is to display all built in metrics and plugin metrics that haven't been globally disabled.
getMetricsToDisplay() - Method in class weka.classifiers.Evaluation: Get a list of the names of metrics to have appear in the output The default is to display all built in metrics and plugin metrics that haven't been globally disabled.
getMetricType() - Method in class weka.associations.Apriori: Get the metric type
getMetricType() - Method in class weka.associations.FPGrowth: Get the metric type to use.
getMetricValuesForRule() - Method in class weka.associations.AssociationRule: Get all the available metric values for this rule.
getMetricValuesForRule() - Method in class weka.associations.DefaultAssociationRule
getMiddle(double[]) - Method in class weka.core.EuclideanDistance: Returns value in the middle of the two parameter values.
getMin() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the min property.
getMin() - Method in class weka.core.pmml.jaxbbindings.Time: Gets the value of the min property.
getMin() - Method in class weka.gui.beans.ChartEvent: Get the min y value
getMinAbsoluteCoefficientValue() - Method in class weka.classifiers.functions.SGDText: Get the minimum absolute magnitude for model coefficients.
getMinArray() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the calculated minimum values for the attributes in the data.
getMinBoxRelWidth() - Method in class weka.core.neighboursearch.KDTree: Gets the minimum relative box width.
getMinBucketSize() - Method in class weka.classifiers.rules.OneR: Get the value of minBucketSize.
getMinC() - Method in class weka.gui.visualize.Plot2D: Return the current min value of the colouring attribute
getMinCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the minimum of coords per point.
getMinDefault() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the minimum default.
getMinFunction() - Method in class weka.core.Optimization: Get the minimal function value
getMinimal() - Method in class weka.classifiers.functions.LinearRegression: Returns whether to be more memory conservative or being able to output the model as string.
getMinimizeAbsoluteError() - Method in class weka.classifiers.meta.AdditiveRegression: Gets whether absolute error is to be minimized.
getMinimizeAbsoluteError() - Method in class weka.classifiers.meta.RegressionByDiscretization: Gets whether to min.
getMinimizeExpectedCost() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Gets the value of MinimizeExpectedCost.
getMinimum() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the minimum property.
getMinimum() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the minimum property.
getMinimumAntConsSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumAntConsSeparationTime property.
getMinimumBucketSize() - Method in class weka.attributeSelection.OneRAttributeEval: Get the minimum bucket size used by oneR
getMinimumCanopyDensity() - Method in class weka.clusterers.Canopy: Get the minimum T2-based density below which a canopy will be pruned during periodic pruning.
getMinimumConfidence() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the minimumConfidence property.
getMinimumConfidence() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumConfidence property.
getMinimumFractionOfWeightInfoGain() - Method in class weka.classifiers.trees.HoeffdingTree: Get the minimum fraction of weight required down at least two branches for info gain splitting
getMinimumFrequency() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Gets the minimum frequency.
getMinimumItemsetSeparationTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumItemsetSeparationTime property.
getMinimumLift() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumLift property.
getMinimumNumberInstances() - Method in class weka.core.Capabilities: returns the minimum number of instances that have to be in the dataset
getMinimumNumberOfAntecedentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumNumberOfAntecedentItems property.
getMinimumNumberOfConsequentItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumNumberOfConsequentItems property.
getMinimumNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumNumberOfItems property.
getMinimumSupport() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the minimumSupport property.
getMinimumSupport() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumSupport property.
getMinimumTotalSequenceTime() - Method in class weka.core.pmml.jaxbbindings.Constraints: Gets the value of the minimumTotalSequenceTime property.
getMiningBuildTask() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the miningBuildTask property.
getMiningFields() - Method in class weka.core.pmml.jaxbbindings.MiningSchema: Gets the value of the miningField property.
getMiningFields() - Method in class weka.core.pmml.MiningSchema
getMiningModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the miningModel property.
getMiningSchema() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get the mining schema for this model.
getMiningSchema() - Method in interface weka.core.pmml.PMMLModel: Get the mining schema.
getMiningSchemaAsInstances() - Method in class weka.core.pmml.MiningSchema: Get the mining schema fields as an Instances object.
getMinInstNum() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the lower boundary for instances per cluster.
getMinInstNum() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Gets the lower boundary for instances per cluster.
getMinIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the minimum of internal nodes visited.
getMinkowski() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the minkowski property.
getMinLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the minimum number of leaves visited.
getMinLevel() - Method in class weka.core.logging.Logger: Returns the minimum level log messages must have in order to appear in the log.
getMinLogLikelihoodImprovementCV() - Method in class weka.clusterers.EM: Get the minimum improvement in cross-validated log likelihood required to consider increasing the number of clusters when cross-validating to find the best number of clusters
getMinLogLikelihoodImprovementIterating() - Method in class weka.clusterers.EM: Get the minimum improvement in log likelihood necessary to perform another iteration of the E and M steps.
getMinMax(Instances, int, double[]) - Static method in class weka.estimators.CheckEstimator: Find the minimum and the maximum of the attribute and return it in the last parameter..
getMinMax(Instances, int, double[]) - Static method in class weka.estimators.EstimatorUtils: Find the minimum and the maximum of the attribute and return it in the last parameter.
getMinMetric() - Method in class weka.associations.Apriori: Get the value of minConfidence.
getMinMetric() - Method in class weka.associations.FPGrowth: Get the value of minConfidence.
getMinNo() - Method in class weka.classifiers.rules.JRip: Gets the minimum total weight of the instances in a rule
getMinNum() - Method in class weka.classifiers.trees.RandomTree: Get the value of MinNum.
getMinNum() - Method in class weka.classifiers.trees.REPTree: Get the value of MinNum.
getMinNumInstances() - Method in class weka.classifiers.trees.LMT: Get the value of minNumInstances.
getMinNumInstances() - Method in class weka.classifiers.trees.m5.M5Base: Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.Rule: Get the minimum number of instances to allow at a leaf node
getMinNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode: Get the minimum number of instances to allow at a leaf node
getMinNumObj() - Method in class weka.classifiers.rules.PART: Get the value of minNumObj.
getMinNumObj() - Method in class weka.classifiers.trees.J48: Get the value of minNumObj.
getMinPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the minimum of points visited.
getMinRadius() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the lower boundary for the radiuses of the clusters.
getMinRange() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the lower boundary for the range of x
getMinRuleSize() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the minimum number of tests in rules.
getMinStdDev() - Method in class weka.clusterers.EM: Get the minimum allowable standard deviation.
getMinStdDev() - Method in class weka.clusterers.MakeDensityBasedClusterer: Get the minimum allowable standard deviation.
getMinTermFreq() - Method in class weka.core.converters.DictionarySaver: Get the MinTermFreq value.
getMinTermFreq() - Method in class weka.core.DictionaryBuilder: Get the MinTermFreq value.
getMinTermFreq() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Get the MinTermFreq value.
getMinThreshold() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Get the minimum threshold.
getMinValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getMinVarianceProp() - Method in class weka.classifiers.trees.RandomTree: Get the value of MinVarianceProp.
getMinVarianceProp() - Method in class weka.classifiers.trees.REPTree: Get the value of MinVarianceProp.
getMinVersion() - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinVersion() - Method in interface weka.gui.visualize.plugins.VisualizePlugin: Get the minimum version of Weka, inclusive, the class is designed to work with.
getMinWordFrequency() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get the minimum word frequency.
getMinWordFrequency() - Method in class weka.classifiers.functions.SGDText: Get the minimum word frequency.
getMinX() - Method in class weka.gui.visualize.Plot2D: Return the current min value of the attribute plotted on the x axis
getMinXBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Gets the minimum x-coordinate bound, in training-instance units (not mouse coordinates).
getMinY() - Method in class weka.gui.visualize.Plot2D: Return the current min value of the attribute plotted on the y axis
getMinYBound() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Gets the minimum y-coordinate bound, in training-instance units (not mouse coordinates).
getMisses() - Method in class weka.core.FindWithCapabilities: returns the misses from the last find call.
getMissingDependencies(List<Package>) - Method in class weka.core.packageManagement.DefaultPackage: Gets a list of packages that this package depends on that are not in the supplied list of packages.
getMissingDependencies() - Method in class weka.core.packageManagement.DefaultPackage: Gets a list of packages that this package depends on that are not currently installed.
getMissingDependencies() - Method in class weka.core.packageManagement.Package: Gets a list of packages that this package depends on that are not currently installed.
getMissingDependencies(List<Package>) - Method in class weka.core.packageManagement.Package: Gets a list of packages that this package depends on that are not in the supplied list of packages.
getMissingFreq() - Method in class weka.core.pmml.jaxbbindings.Counts: Gets the value of the missingFreq property.
getMissingMerge() - Method in class weka.attributeSelection.GainRatioAttributeEval: get whether missing values are being distributed or not
getMissingMerge() - Method in class weka.attributeSelection.InfoGainAttributeEval: get whether missing values are being distributed or not
getMissingMerge() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: get whether missing values are being distributed or not
getMissingMode() - Method in class weka.classifiers.lazy.KStar: Gets the method to use for handling missing values.
getMissingSeparate() - Method in class weka.attributeSelection.CfsSubsetEval: Return true is missing is treated as a separate value
getMissingValue() - Method in class weka.core.converters.CSVLoader: Returns the current placeholder for missing values.
getMissingValue() - Method in class weka.core.converters.CSVSaver: Returns the current placeholder for missing values.
getMissingValuePenalty() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the missingValuePenalty property.
getMissingValuePenalty() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the missingValuePenalty property.
getMissingValueReplacement() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the missingValueReplacement property.
getMissingValueStrategy() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the missingValueStrategy property.
getMissingValueStrategy() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the missingValueStrategy property.
getMissingValueTreatment() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the missingValueTreatment property.
getMissingValueTreatmentMethod() - Method in class weka.core.pmml.MiningFieldMetaInfo: Get the missing value treatment method for this field.
getModalValue() - Method in class weka.core.pmml.jaxbbindings.DiscrStats: Gets the value of the modalValue property.
getModel() - Method in class weka.classifiers.trees.m5.RuleNode: Get the linear model at this node
getModel() - Method in class weka.gui.SortedTableModel: returns the current model, can be null
getModelClass() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the modelClass property.
getModelDF() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the modelDF property.
getModelFile() - Method in class weka.classifiers.misc.SerializedClassifier: Gets the file containing the serialized model.
getModelHeader(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Return the instance structure that the encapsulated model was built with.
getModelLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the modelLiftGraph property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.MiningModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the value of the modelName property.
getModelName() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the modelName property.
getModelParameters() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns a string describing the number of LogitBoost iterations performed at this node, the total number of LogitBoost iterations performed (including iterations at higher levels in the tree), and the number of training examples at this node.
getModelPath() - Method in class weka.classifiers.misc.InputMappedClassifier: Get the path used for loading a model.
getModelStats() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the modelStats property.
getModelStats() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the modelStats property.
getModelType() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the modelType property.
getModelType() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the modelType property.
getModelValueAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the value at the given position
getModificationText() - Method in class weka.filters.RenameRelation: Get the modification text to apply
getModificationText() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get the modification text to apply
getModifyHeader() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Gets whether the header will be modified when selecting on nominal attributes.
getModifyHeader() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Gets whether the header will be modified when selecting on nominal attributes.
getModType() - Method in class weka.filters.RenameRelation: Get the modification type to apply
getModType() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get the modification type to apply
getMomentum() - Method in class weka.classifiers.functions.MultilayerPerceptron
getMultiInstance() - Method in class weka.core.TestInstances: Gets whether multi-instance data (with a fixed structure) is generated
getMultiInstanceCapabilities() - Method in interface weka.core.MultiInstanceCapabilitiesHandler: Returns the capabilities of this multi-instance classifier for the relational data (i.e., the bags).
getMultiLineComment() - Method in class weka.gui.scripting.SyntaxDocument: Returns whether multi-line comments are enabled.
getMultiLineCommentEnd() - Method in class weka.gui.scripting.SyntaxDocument: Returns the end of a multi-line comment.
getMultiLineCommentStart() - Method in class weka.gui.scripting.SyntaxDocument: Returns the string that is the start of a multi-line comment.
getMultipleModelMethod() - Method in class weka.core.pmml.jaxbbindings.Segmentation: Gets the value of the multipleModelMethod property.
getMultivariateStat() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats: Gets the value of the multivariateStat property.
getMultivariateStats() - Method in class weka.core.pmml.jaxbbindings.ModelStats: Gets the value of the multivariateStats property.
getMustRunSingleThreaded() - Method in class weka.knowledgeflow.StepTask: Get whether this StepTask must run single threaded - i.e.
getN() - Method in class weka.core.pmml.jaxbbindings.ArrayType: Gets the value of the n property.
getN() - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Gets the value of the n property.
getN() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Gets the value of the n property.
getNaiveBayesModel() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Get the naive bayes model at this node
getNaiveBayesModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the naiveBayesModel property.
getNaiveBayesPredictionThreshold() - Method in class weka.classifiers.trees.HoeffdingTree: Get the number of instances (weight) a leaf should observe before allowing naive Bayes to make predictions
getName() - Method in class weka.classifiers.bayes.BayesNet: get name of the Bayes network
getName() - Method in class weka.core.expressionlanguage.common.Primitives.BooleanVariable
getName() - Method in class weka.core.expressionlanguage.common.Primitives.DoubleVariable
getName() - Method in class weka.core.expressionlanguage.common.Primitives.StringVariable
getName() - Method in class weka.core.json.JSONNode: Returns the name of the node.
getName() - Method in class weka.core.packageManagement.DefaultPackage: Convenience method to return the name of this package.
getName() - Method in class weka.core.packageManagement.Package: Convenience method to return the name of this package.
getName() - Method in class weka.core.pmml.Function
getName() - Method in class weka.core.pmml.jaxbbindings.Application: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Characteristic: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Extension: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Parameter: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.ParameterField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Partition: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Predictor: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.Taxonomy: Gets the value of the name property.
getName() - Method in class weka.core.pmml.jaxbbindings.TextDocument: Gets the value of the name property.
getName() - Method in class weka.core.pmml.MiningFieldMetaInfo: Get the name of this field.
getName() - Method in class weka.core.PropertyPath.PathElement: returns the name of the property
getName() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the name of the new attribute
getName() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the name of the new attribute
getName() - Method in class weka.gui.experiment.AbstractSetupPanel: Returns the name of the panel.
getName() - Method in class weka.gui.experiment.SetupPanel: Returns the name of the panel.
getName() - Method in class weka.gui.experiment.SimpleSetupPanel: Returns the name of the panel.
getName() - Method in class weka.gui.simplecli.AbstractCommand: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Capabilities: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Cls: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Echo: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Exit: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Help: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.History: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Java: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Kill: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Script: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Set: Returns the name of the command.
getName() - Method in class weka.gui.simplecli.Unset: Returns the name of the command.
getName() - Method in class weka.gui.visualize.VisualizePanel: Returns the name associated with this plot.
getName() - Method in interface weka.knowledgeflow.StepManager: Get the name of the step managed by this StepManager
getName() - Method in class weka.knowledgeflow.StepManagerImpl: Get the name of the Step being managed
getName() - Method in class weka.knowledgeflow.steps.BaseStep: Get the name of this step
getName() - Method in interface weka.knowledgeflow.steps.Step: Get the name of this step
getNameAndValueFromUnsupervisedNominalToBinaryDerivedAttribute(Instances, Attribute) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Extracts the original attribute name and value from the name of a binary indicator attribute created by unsupervised NominalToBinary.
getNameAtIndex(int) - Method in class weka.gui.ResultHistoryPanel: Gets the name of theitem in the list at the specified index
getNamedBuffer(String) - Method in class weka.gui.ResultHistoryPanel: Gets the named buffer
getNamedMetric(String, int...) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper: Gets the value of a named metric.
getNamedMetricThresholds(String) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper: Gets the thresholds produced by the metric, if the metric implements ThresholdProducingMetric.
getNamedMetricValue(String) - Method in class weka.associations.AssociationRule: Get the value of the named metric for this rule
getNamedMetricValue(String) - Method in class weka.associations.DefaultAssociationRule
getNamedObject(String) - Method in class weka.gui.ResultHistoryPanel: Get the named object from the list
getNbCols() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the nbCols property.
getNbCorrect() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the nbCorrect property.
getNbCorrect() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the nbCorrect property.
getNbRows() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the nbRows property.
getNearestNeighborModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the nearestNeighborModel property.
getNearestNeighbourSearchAlgorithm() - Method in class weka.classifiers.lazy.IBk: Returns the current nearestNeighbourSearch algorithm in use.
getNearestNeighbourSearchAlgorithm() - Method in class weka.classifiers.lazy.LWL: Returns the current nearestNeighbourSearch algorithm in use.
getNegativeTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the negativeTargetFieldDisplayValue property.
getNegativeTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the negativeTargetFieldValue property.
getNeuralInput() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs: Gets the value of the neuralInput property.
getNeuralNetwork() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the neuralNetwork property.
getNeuralOutput() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs: Gets the value of the neuralOutput property.
getNeuron() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the neuron property.
getNewAttributeName() - Method in class weka.gui.beans.SubstringLabelerRules: Get the name to use for the new attribute that is added
getNewLine() - Method in class weka.gui.scripting.Script: Returns the new line string in use.
getNext(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Gets the next element in the set.
getNextInstance(Instances) - Method in class weka.core.converters.AbstractLoader
getNextInstance(Instances) - Method in class weka.core.converters.ArffLoader: Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.C45Loader: Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.CSVLoader
getNextInstance(Instances) - Method in class weka.core.converters.DatabaseLoader: Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.JSONLoader: JSONLoader is unable to process a data set incrementally.
getNextInstance(Instances) - Method in class weka.core.converters.LibSVMLoader: LibSVmLoader is unable to process a data set incrementally.
getNextInstance(Instances) - Method in interface weka.core.converters.Loader: Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.MatlabLoader: MatlabLoader is unable to process a data set incrementally.
getNextInstance(Instances) - Method in class weka.core.converters.SerializedInstancesLoader: Read the data set incrementally---get the next instance in the data set or returns null if there are no more instances to get.
getNextInstance(Instances) - Method in class weka.core.converters.SVMLightLoader: SVMLightLoader is unable to process a data set incrementally.
getNextInstance(Instances) - Method in class weka.core.converters.TextDirectoryLoader: Process input directories/files incrementally.
getNextInstance(Instances) - Method in class weka.core.converters.XRFFLoader: XRFFLoader is unable to process a data set incrementally.
getNGramMaxSize() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Gets the max N of the NGram.
getNGramMaxSize() - Method in class weka.core.tokenizers.NGramTokenizer: Gets the max N of the NGram.
getNGramMinSize() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Gets the min N of the NGram.
getNGramMinSize() - Method in class weka.core.tokenizers.NGramTokenizer: Gets the min N of the NGram.
getNoClass() - Method in class weka.core.TestInstances: whether no class attribute is generated
getNode(String) - Method in class weka.classifiers.bayes.net.BIFReader: getNode finds the index of the node with name sNodeName and throws an exception if no such node can be found.
getNode(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns index of node with given name.
getNode(String) - Method in class weka.classifiers.bayes.net.MarginCalculator
getNode() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the node property.
getNode(String) - Method in class weka.core.xml.XMLDocument: Returns the node represented by the XPath expression.
getNode2(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns index of node with given name, or -1 if no such node exists
getNodeName(int) - Method in class weka.classifiers.bayes.BayesNet: get name of a node in the Bayes network
getNodes() - Method in class weka.classifiers.trees.lmt.LMTNode: Return a list of all inner nodes in the tree
getNodes(Vector<LMTNode>) - Method in class weka.classifiers.trees.lmt.LMTNode: Fills a list with all inner nodes in the tree
getNodes() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: give access to set of graph nodes
getNodes() - Method in interface weka.gui.graphvisualizer.LayoutEngine: give access to set of graph nodes
getNodeSplitter() - Method in class weka.core.neighboursearch.KDTree: Returns the splitting method currently in use to split the nodes of the KDTree.
getNodeType() - Method in class weka.core.json.JSONNode: Returns the type of the container.
getNodeValue(int, int) - Method in class weka.classifiers.bayes.BayesNet: get name of a particular value of a node
getNoHeaderRow() - Method in class weka.core.converters.CSVSaver: Get whether to not write the header row
getNoHeaderRowPresent() - Method in class weka.core.converters.CSVLoader: Get whether there is no header row in the data.
getNoise() - Method in class weka.classifiers.functions.GaussianProcesses: Get the value of noise.
getNoisePercent() - Method in class weka.datagenerators.classifiers.classification.LED24: Gets the noise percentage.
getNoiseRate() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the gaussian noise rate.
getNoiseVariance() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the noise variance
getNominalAttributes() - Method in class weka.core.converters.CSVLoader: Returns the current attribute range to be forced to type nominal.
getNominalBinary() - Method in class weka.gui.beans.SubstringLabeler: Get whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.
getNominalBinary() - Method in class weka.gui.beans.SubstringLabelerRules: Get whether to create a nominal binary attribute in the case when the user has not supplied an explicit label to use for each rule.
getNominalBinary() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.
getNominalCols() - Method in class weka.datagenerators.clusterers.SubspaceCluster: returns the range of nominal attributes
getNominalConversionThreshold() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Get the minimum number of values a nominal attribute must have in order to be transformed.
getNominalIndices() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Get the set of nominal value indices that will be used for selection
getNominalLabels() - Method in class weka.filters.unsupervised.attribute.Add: Get the list of labels for nominal attribute creation.
getNominalLabelSpecs() - Method in class weka.core.converters.CSVLoader: Get label specifications for nominal attributes.
getNominalOrStringValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the value of the attribute as a string (nominal and string attribute) or null if the attribute is not nominal or string
getNominalStringReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Get the nominal/string replacement value
getNominalToBinaryFilter() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNonEmpty() - Method in class weka.core.TestOptions
getNoPruning() - Method in class weka.classifiers.trees.REPTree: Get the value of NoPruning.
getNoReplacement() - Method in class weka.filters.supervised.instance.Resample: Gets whether instances are drawn with or without replacement.
getNoReplacement() - Method in class weka.filters.unsupervised.instance.Resample: Gets whether instances are drawn with or without replacement.
getNorm() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get the instance's Norm.
getNorm() - Method in class weka.classifiers.functions.SGDText: Get the instance's Norm.
getNorm() - Method in class weka.core.pmml.jaxbbindings.LinearNorm: Gets the value of the norm property.
getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the normalizationMethod property.
getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the normalizationMethod property.
getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the normalizationMethod property.
getNormalizationMethod() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the normalizationMethod property.
getNormalizationScheme() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the normalizationScheme property.
getNormalize() - Method in class weka.core.DictionaryBuilder: Get whether word frequencies for a document should be normalized
getNormalizeAttributes() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNormalizedCountTable() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the normalizedCountTable property.
getNormalizeDimWidths() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Whether we are normalizing the widths(ranges) of the dimensions (attributes) or not.
getNormalizeDocLength() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get whether to normalize the length of each document
getNormalizeDocLength() - Method in class weka.classifiers.functions.SGDText: Get whether to normalize the length of each document
getNormalizeDocLength() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets whether if the word frequencies for a document (instance) should be normalized or not.
getNormalizeDocLength() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets whether if the word frequencies for a document (instance) should be normalized or not.
getNormalizeNodeWidth() - Method in class weka.core.neighboursearch.KDTree: Gets the normalize flag.
getNormalizeNumericClass() - Method in class weka.classifiers.functions.MultilayerPerceptron
getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the normContinuous property.
getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the normContinuous property.
getNormContinuous() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the normContinuous property.
getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the normDiscrete property.
getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the normDiscrete property.
getNormDiscrete() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the normDiscrete property.
getNoSizeDetermination() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns whether the size determination (train/test/classifer) is skipped.
getNoSizeDetermination() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns whether the size determination (train/test/clusterer) is skipped.
getNoSizeDetermination() - Method in class weka.experiment.RegressionSplitEvaluator: Returns whether the size determination (train/test/classifer) is skipped.
getNot() - Method in class weka.datagenerators.Test: Negates the test.
getNotCapabilities() - Method in class weka.core.FindWithCapabilities: The "not to have" capabilities to search for.
getNotes() - Method in class weka.experiment.Experiment: Get the user notes.
getNoteText() - Method in class weka.gui.beans.Note: Get the note text
getNoteText() - Method in class weka.knowledgeflow.steps.Note: Get the text of the note
getNoTrueChildStrategy() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the noTrueChildStrategy property.
getNoTrueChildStrategy() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the noTrueChildStrategy property.
getNPointPrecision(Instances, int) - Static method in class weka.classifiers.evaluation.ThresholdCurve: Calculates the n point precision result, which is the precision averaged over n evenly spaced (w.r.t recall) samples of the curve.
getNrOfGoodOperations() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Gets the number of "good operations"
getNrOfLookAheadSteps() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Gets the number of look-ahead steps
getNrOfNodes() - Method in class weka.classifiers.bayes.BayesNet: get number of nodes in the Bayes network
getNrOfParents(int) - Method in class weka.classifiers.bayes.BayesNet: get number of parents of a node in the network structure
getNrOfParents() - Method in class weka.classifiers.bayes.net.ParentSet: returns number of parents
getNumArcs() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the number of arcs for the bayesian net
getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.ContStats: Gets the value of the numarray property.
getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the numarray property.
getNUMARRAY() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the numarray property.
getNumAttributes() - Method in class weka.core.TestInstances: returns the overall number of attributes (incl.
getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the number of attributes that should be produced.
getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Gets the number of attributes that should be produced.
getNumAttributes() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the number of attributes that should be produced.
getNumAttributes() - Method in class weka.datagenerators.ClusterGenerator: Gets the number of attributes that should be produced.
getNumAttributes() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Get the number of attributes (< 1 percentage, >= 1 absolute number).
getNumberOfAttributes() - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Gets the value of the numberOfAttributes property.
getNumberOfAttributes() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Gets the current number of attributes (dimensionality) to which the data will be reduced to.
getNumberOfClusters() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the numberOfClusters property.
getNumberOfCoefficients() - Method in class weka.core.pmml.jaxbbindings.Coefficients: Gets the value of the numberOfCoefficients property.
getNumberOfDocuments() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the numberOfDocuments property.
getNumberOfFields() - Method in class weka.core.pmml.jaxbbindings.DataDictionary: Gets the value of the numberOfFields property.
getNumberOfFields() - Method in class weka.core.pmml.jaxbbindings.VectorFields: Gets the value of the numberOfFields property.
getNumberOfInputs() - Method in class weka.core.pmml.jaxbbindings.NeuralInputs: Gets the value of the numberOfInputs property.
getNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the numberOfItems property.
getNumberOfItems() - Method in class weka.core.pmml.jaxbbindings.Itemset: Gets the value of the numberOfItems property.
getNumberOfItemsets() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the numberOfItemsets property.
getNumberOfLayers() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the numberOfLayers property.
getNumberOfMetricsForRule() - Method in class weka.associations.AssociationRule: Gets the number of metrics available for this rule.
getNumberOfMetricsForRule() - Method in class weka.associations.DefaultAssociationRule
getNumberOfNeighbors() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the numberOfNeighbors property.
getNumberOfNeurons() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the numberOfNeurons property.
getNumberOfOutputs() - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs: Gets the value of the numberOfOutputs property.
getNumberOfRules() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the numberOfRules property.
getNumberOfSets() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the numberOfSets property.
getNumberOfSets() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the numberOfSets property.
getNumberOfSupportVectors() - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Gets the value of the numberOfSupportVectors property.
getNumberOfTerms() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the numberOfTerms property.
getNumberOfTransactionGroups() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the numberOfTransactionGroups property.
getNumberOfTransactions() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the numberOfTransactions property.
getNumberOfTransactions() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the numberOfTransactions property.
getNumberOfVectors() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Gets the value of the numberOfVectors property.
getNumBins() - Method in class weka.classifiers.meta.RegressionByDiscretization: Gets the number of bins numeric attributes will be divided into
getNumBins() - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
getNumBins() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Gets the number of bins
getNumBoostingIterations() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of numBoostingIterations.
getNumBoostingIterations() - Method in class weka.classifiers.trees.LMT: Get the value of numBoostingIterations.
getNumBootstrapRuns() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the number of Bootstrap runs.
getNumCentroids() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Gets the number of centroids.
getNumClasses() - Method in class weka.core.TestInstances: returns the current number of classes
getNumClasses() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Gets the number of classes the dataset should have.
getNumClasses() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the number of classes the dataset should have.
getNumClusters() - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator: Return the number of clusters used by the subset evaluator
getNumClusters() - Method in class weka.clusterers.Canopy: Get the number of clusters to generate
getNumClusters() - Method in class weka.clusterers.ClusterEvaluation: Return the number of clusters found for the most recent call to evaluateClusterer
getNumClusters() - Method in class weka.clusterers.EM: Get the number of clusters
getNumClusters() - Method in class weka.clusterers.FarthestFirst: gets the number of clusters to generate
getNumClusters() - Method in class weka.clusterers.HierarchicalClusterer
getNumClusters() - Method in class weka.clusterers.SimpleKMeans: gets the number of clusters to generate.
getNumClusters() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the number of clusters the dataset should have.
getNumComponents() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the number of components to use.
getNumCVFolds() - Method in class weka.gui.explorer.ClassifierPanel: Get the number of cross-validation folds to use
getNumCycles() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the number of cycles.
getNumDatasets() - Method in class weka.experiment.PairedTTester: Gets the number of datasets in the resultsets
getNumDatasets() - Method in interface weka.experiment.Tester: Gets the number of datasets in the resultsets
getNumDate() - Method in class weka.core.CheckScheme: returns the current number of date attributes
getNumDate() - Method in class weka.core.TestInstances: returns the current number of date attributes
getNumDecimalPlaces() - Method in class weka.classifiers.AbstractClassifier: Get the number of decimal places.
getNumDecimalPlaces() - Method in class weka.classifiers.trees.m5.Rule: Get the number of decimal places.
getNumDecimals() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the number of digits to output after the decimal point.
getNumeric() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Check if new attribute is to be numeric.
getNumericAttributes() - Method in class weka.core.converters.CSVLoader: Gets the attribute range to be forced to type numeric
getNumericColumns() - Method in class weka.gui.sql.ResultSetHelper: returns an array that indicates whether a column is numeric or nor.
getNumericInfo() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the numericInfo property.
getNumericInfo() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the numericInfo property.
getNumericPredictors() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the numericPredictor property.
getNumericReplacementValue() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Get the numeric replacement value
getNumericValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the value of the attribute as a number or Utils.missingValue() if the attribute is not numeric.
getNumExamples() - Method in class weka.datagenerators.ClassificationGenerator: Gets the number of examples, given by option.
getNumExamples() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the number of examples, given by option.
getNumExamples() - Method in class weka.datagenerators.RegressionGenerator: Gets the number of examples, given by option.
getNumExamplesAct() - Method in class weka.datagenerators.DataGenerator: Gets the number of examples the dataset should have.
getNumExecutionSlots() - Method in class weka.attributeSelection.GreedyStepwise: Gets the number of threads.
getNumExecutionSlots() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Get the number of execution slots (threads) to use for building the members of the ensemble.
getNumExecutionSlots() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Get the number of execution slots (threads) to use for building the members of the ensemble.
getNumExecutionSlots() - Method in class weka.clusterers.EM: Get the degree of parallelism to use.
getNumExecutionSlots() - Method in class weka.clusterers.SimpleKMeans: Get the degree of parallelism to use.
getNumFeatures() - Method in class weka.classifiers.trees.RandomForest: Get the number of features used in random selection.
getNumFiles() - Method in class weka.core.Debug.Log: returns the number of files being used
getNumFolds() - Method in class weka.classifiers.functions.SMO: Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.meta.CVParameterSelection: Gets the number of folds for the cross-validation.
getNumFolds() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of NumFolds.
getNumFolds() - Method in class weka.classifiers.meta.MultiScheme: Gets the number of folds for cross-validation.
getNumFolds() - Method in class weka.classifiers.meta.Stacking: Gets the number of folds for the cross-validation.
getNumFolds() - Method in class weka.classifiers.rules.PART: Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.trees.J48: Get the value of numFolds.
getNumFolds() - Method in class weka.classifiers.trees.RandomTree: Get the value of NumFolds.
getNumFolds() - Method in class weka.classifiers.trees.REPTree: Get the value of NumFolds.
getNumFolds() - Method in class weka.clusterers.EM: Get the number of folds to use when cross-validating to find the best number of clusters.
getNumFolds() - Method in class weka.experiment.CrossValidationResultProducer: Get the value of NumFolds.
getNumFolds() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets the number of folds in which dataset is to be split into.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets the number of folds in which dataset is to be split into.
getNumFolds() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the number of cross-validation folds used by the filter.
getNumFolds() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Get the number of folds to create
getNumGeneratingModels() - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Returns the number of generating models used by this DataGenerator
getNumGeneratingModels() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Return the number of kernels (there is one per training instance)
getNumInnerNodes() - Method in class weka.classifiers.trees.lmt.LMTNode: Method to count the number of inner nodes in the tree
getNumInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
getNumInstances() - Method in class weka.classifiers.bayes.BayesNet: Returns the number of instances the model was built from.
getNumInstances() - Method in class weka.classifiers.trees.m5.RuleNode: Return the number of instances that reach this node.
getNumInstances() - Method in class weka.core.CheckScheme: Gets the current number of instances to use for the datasets.
getNumInstances() - Method in class weka.core.TestInstances: returns the current number of instances to produce
getNumInstances() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getNumInstances() - Method in class weka.estimators.CheckEstimator: Gets the current number of instances to use for the datasets.
getNumInstancesRelational() - Method in class weka.core.CheckScheme: returns the current number of instances in relational/bag attributes to produce
getNumInstancesRelational() - Method in class weka.core.TestInstances: returns the current number of instances in relational/bag attributes to produce
getNumIntervals() - Method in class weka.filters.supervised.instance.ClassBalancer: Gets the number of discretization intervals to use when the class is numeric.
getNumIrrelevant() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the number of irrelevant attributes.
getNumIterations() - Method in class weka.classifiers.functions.VotedPerceptron: Get the value of NumIterations.
getNumIterations() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Gets the number of bagging iterations
getNumKernels() - Method in class weka.estimators.KernelEstimator: Return the number of kernels in this kernel estimator
getNumKMeansRuns() - Method in class weka.clusterers.EM: Returns the number of runs of k-means to perform.
getNumLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the number of leaves in the tree.
getNumLeaves() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the number of leaves in the built tree.
getNumLocationsPerPixel() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the number of locations/samples per pixel
getNumNeighbours() - Method in class weka.attributeSelection.ReliefFAttributeEval: Get the number of nearest neighbours
getNumNodes() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the number of nodes (internal + leaf) in the built tree.
getNumNominal() - Method in class weka.core.CheckScheme: returns the current number of nominal attributes
getNumNominal() - Method in class weka.core.TestInstances: returns the current number of nominal attributes
getNumNominalValues() - Method in class weka.core.TestInstances: returns the current number of values for nominal attributes
getNumNumeric() - Method in class weka.core.CheckScheme: returns the current number of numeric attributes
getNumNumeric() - Method in class weka.core.TestInstances: returns the current number of numeric attributes
getNumNumeric() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the number of numerical attributes.
getNumOfPredictors() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the numOfPredictors property.
getNumOfRecords() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the numOfRecords property.
getNumOfRecordsWeighted() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the numOfRecordsWeighted property.
getNumOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection
getNumQueries() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the number of queries.
getNumRegressions() - Method in class weka.classifiers.functions.SimpleLogistic: Get the number of LogitBoost iterations performed (= the number of regression functions fit by LogitBoost).
getNumRegressions() - Method in class weka.classifiers.trees.lmt.LogisticBase: The number of LogitBoost iterations performed (= the number of simple regression functions fit).
getNumRelational() - Method in class weka.core.CheckScheme: returns the current number of relational attributes
getNumRelational() - Method in class weka.core.TestInstances: returns the current number of relational attributes
getNumRelationalDate() - Method in class weka.core.TestInstances: returns the current number of date attributes in a relational attribute
getNumRelationalNominal() - Method in class weka.core.TestInstances: returns the current number of nominal attributes in a relational attribute
getNumRelationalNominalValues() - Method in class weka.core.TestInstances: returns the current number of values for nominal attributes in a relational attribute
getNumRelationalNumeric() - Method in class weka.core.TestInstances: returns the current number of numeric attributes in a relational attribute
getNumRelationalString() - Method in class weka.core.TestInstances: returns the current number of string attributes in a relational attribute
getNumResultsets() - Method in class weka.experiment.PairedTTester: Gets the number of resultsets in the data.
getNumResultsets() - Method in interface weka.experiment.Tester: Gets the number of resultsets in the data.
getNumRules() - Method in class weka.associations.Apriori: Get the value of numRules.
getNumRules() - Method in class weka.associations.AssociationRules: Get the number of rules.
getNumRules() - Method in class weka.associations.FilteredAssociationRules: Get the number of rules.
getNumRulesToFind() - Method in class weka.associations.FPGrowth: Get the number of rules to find.
getNumRuns() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of NumRuns.
getNumSamplesPerRegion() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Get the number of points to sample from a region (fixed dimensions).
getNumString() - Method in class weka.core.CheckScheme: returns the current number of string attributes
getNumString() - Method in class weka.core.TestInstances: returns the current number of string attributes
getNumSymbols() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Gets the number of symbols this estimator operates with
getNumSymbols() - Method in class weka.estimators.DiscreteEstimator: Gets the number of symbols this estimator operates with
getNumTabs() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getNumTabs() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the number of open tabs
getNumThreads() - Method in class weka.attributeSelection.CfsSubsetEval: Gets the number of threads.
getNumThreads() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Gets the number of threads.
getNumThreads() - Method in class weka.classifiers.meta.LogitBoost: Gets the number of threads.
getNumToEvaluateInParallel() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the number of attributes to evaluate in parallel
getNumToSelect() - Method in class weka.attributeSelection.GreedyStepwise: Gets the number of attributes to be retained.
getNumToSelect() - Method in interface weka.attributeSelection.RankedOutputSearch: Gets the user specified number of attributes to be retained.
getNumToSelect() - Method in class weka.attributeSelection.Ranker: Gets the number of attributes to be retained.
getNumTraining() - Method in class weka.classifiers.lazy.IBk: Get the number of training instances the classifier is currently using.
getNumValues() - Method in class weka.datagenerators.clusterers.SubspaceCluster: returns array that stores the number of values for a nominal attribute.
getNumValues() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Gets how many values are retained
getObject() - Method in class weka.core.CheckGOE: Get the object used in the tests.
getObject() - Method in class weka.core.SerializedObject: Returns a serialized object.
getObjectInputStream(InputStream) - Static method in class weka.core.SerializationHelper: Get a (Weka package classloader aware) ObjectInputStream instance for reading objects from the supplied input stream
getOccurrence() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the occurrence property.
getOccurrence() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the occurrence property.
getOffDiagDefault() - Method in class weka.core.pmml.jaxbbindings.Matrix: Gets the value of the offDiagDefault property.
getOffscreenAdditionalOpts() - Method in class weka.gui.beans.DataVisualizer: Get the additional options for the offscreen renderer
getOffscreenAdditionalOpts() - Method in class weka.gui.beans.ModelPerformanceChart: Get the additional options for the offscreen renderer
getOffscreenAdditionalOpts() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the additional options for the offscreen renderer
getOffscreenAdditionalOpts() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the additional options for the offscreen renderer
getOffscreenAdditionalOpts() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the additional options for the offscreen renderer
getOffscreenHeight() - Method in class weka.gui.beans.DataVisualizer: Get the height (in pixels) of the offscreen image to generate
getOffscreenHeight() - Method in class weka.gui.beans.ModelPerformanceChart: Get the height (in pixels) of the offscreen image to generate
getOffscreenHeight() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the height (in pixels) of the offscreen image to generate
getOffscreenHeight() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the height (in pixels) of the offscreen image to generate
getOffscreenHeight() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the height (in pixels) of the offscreen image to generate
getOffscreenRendererName() - Method in class weka.gui.beans.DataVisualizer: Get the name of the renderer to use for offscreen chart rendering operations
getOffscreenRendererName() - Method in class weka.gui.beans.ModelPerformanceChart: Get the name of the renderer to use for offscreen chart rendering operations
getOffscreenRendererName() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the name of the renderer to use for offscreen chart rendering operations
getOffscreenRendererName() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the name of the renderer to use for offscreen chart rendering operations
getOffscreenRendererName() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the name of the renderer to use for offscreen chart rendering operations
getOffscreenWidth() - Method in class weka.gui.beans.DataVisualizer: Get the width (in pixels) of the offscreen image to generate.
getOffscreenWidth() - Method in class weka.gui.beans.ModelPerformanceChart: Get the width (in pixels) of the offscreen image to generate.
getOffscreenWidth() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the width (in pixels) of the offscreen image to generate.
getOffscreenWidth() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the width (in pixels) of the offscreen image to generate.
getOffscreenWidth() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the width (in pixels) of the offscreen image to generate.
getOffscreenXAxis() - Method in class weka.gui.beans.DataVisualizer: Get the name of the attribute for the x-axis in offscreen plots
getOffscreenXAxis() - Method in class weka.gui.beans.ModelPerformanceChart: Get the name of the attribute for the x-axis in offscreen plots
getOffscreenXAxis() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get the name of the attribute for the x-axis in offscreen plots
getOffscreenXAxis() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the name of the attribute for the x-axis in offscreen plots
getOffscreenXAxis() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the name of the attribute for the x-axis in offscreen plots
getOffscreenYAxis() - Method in class weka.gui.beans.DataVisualizer: Get the name of the attribute for the y-axix of offscreen plots.
getOffscreenYAxis() - Method in class weka.gui.beans.ModelPerformanceChart: Get the name of the attribute for the y-axix of offscreen plots.
getOffscreenYAxis() - Method in class weka.knowledgeflow.steps.DataVisualizer: Get the name of the attribute for the y-axix of offscreen plots.
getOffscreenYAxis() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the name of the attribute for the y-axix of offscreen plots.
getOffset() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the offset property.
getOffsetValue() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the offsetValue property.
getOffsetVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the offsetVariable property.
getOmega() - Method in class weka.classifiers.functions.supportVector.Puk: Gets the omega value.
getOnDemandDirectory() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns the directory that will be searched for cost files when loading on demand.
getOnDemandDirectory() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns the directory that will be searched for cost files when loading on demand.
getOperator() - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Gets the value of the operator property.
getOperator() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Gets the value of the operator property.
getOperator() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Get the operator
getOptimizations() - Method in class weka.classifiers.rules.JRip: Gets the the number of optimization runs
getOptimumLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the optimumLiftGraph property.
getOption(char, String[]) - Static method in class weka.core.Utils: Gets an option indicated by a flag "-Char" from the given array of strings.
getOption(String, String[]) - Static method in class weka.core.Utils: Gets an option indicated by a flag "-String" from the given array of strings.
getOptionHandler() - Method in class weka.core.CheckOptionHandler: Get the OptionHandler used in the tests.
getOptionPos(char, String[]) - Static method in class weka.core.Utils: Gets the index of an option or flag indicated by a flag "-Char" from the given array of strings.
getOptionPos(String, String[]) - Static method in class weka.core.Utils: Gets the index of an option or flag indicated by a flag "-String" from the given array of strings.
getOptions() - Method in class weka.associations.AbstractAssociator: Gets the current settings of the associator
getOptions() - Method in class weka.associations.Apriori: Gets the current settings of the Apriori object.
getOptions() - Method in class weka.associations.CheckAssociator: Gets the current settings of the CheckAssociator.
getOptions() - Method in class weka.associations.FilteredAssociator: Gets the current settings of the Associator.
getOptions() - Method in class weka.associations.FPGrowth: Gets the current settings of the classifier.
getOptions() - Method in class weka.associations.SingleAssociatorEnhancer: Gets the current settings of the associator.
getOptions() - Method in class weka.attributeSelection.ASEvaluation: Gets the current settings of the evaluator.
getOptions() - Method in class weka.attributeSelection.ASSearch: Gets the current settings of the search.
getOptions() - Method in class weka.attributeSelection.BestFirst: Gets the current settings of BestFirst.
getOptions() - Method in class weka.attributeSelection.CfsSubsetEval: Gets the current settings of CfsSubsetEval
getOptions() - Method in class weka.attributeSelection.CheckAttributeSelection: Gets the current settings of the CheckAttributeSelection.
getOptions() - Method in class weka.attributeSelection.ClassifierAttributeEval: returns the current setup.
getOptions() - Method in class weka.attributeSelection.ClassifierSubsetEval: Gets the current settings of ClassifierSubsetEval
getOptions() - Method in class weka.attributeSelection.CorrelationAttributeEval: Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval: Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.GreedyStepwise: Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval: Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.OneRAttributeEval: returns the current setup.
getOptions() - Method in class weka.attributeSelection.PrincipalComponents: Gets the current settings of PrincipalComponents
getOptions() - Method in class weka.attributeSelection.Ranker: Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval: Gets the current settings of ReliefFAttributeEval.
getOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.attributeSelection.WrapperSubsetEval: Gets the current settings of WrapperSubsetEval.
getOptions() - Method in class weka.classifiers.AbstractClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.BayesNet: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.NaiveBayes: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.K2: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.K2: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Gets the current settings of the search algorithm.
getOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.BVDecompose: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.CheckClassifier: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.classifiers.CheckSource: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.classifiers.functions.GaussianProcesses: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.LinearRegression: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.Logistic: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron: Gets the current settings of NeuralNet.
getOptions() - Method in class weka.classifiers.functions.SGD: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SGDText: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SimpleLinearRegression: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SimpleLogistic: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.functions.SMO: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.SMOreg: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Gets the current settings of the CheckKernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.Kernel: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.Puk: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.supportVector.RegSMO: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Gets the current settings of the object.
getOptions() - Method in class weka.classifiers.functions.supportVector.StringKernel: Gets the current settings of the Kernel.
getOptions() - Method in class weka.classifiers.functions.VotedPerceptron: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.lazy.IBk: Gets the current settings of IBk.
getOptions() - Method in class weka.classifiers.lazy.KStar: Gets the current settings of K*.
getOptions() - Method in class weka.classifiers.lazy.LWL: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.meta.AdaBoostM1: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.AdditiveRegression: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Bagging: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.CVParameterSelection: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.FilteredClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.LogitBoost: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MultiClassClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.MultiScheme: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.RandomSubSpace: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Stacking: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.meta.Vote: Gets the current settings of Vote.
getOptions() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.misc.InputMappedClassifier: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.misc.SerializedClassifier: returns the options of the current setup
getOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableClassifier: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.rules.DecisionTable: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.rules.JRip: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.rules.OneR: Gets the current settings of the OneR classifier.
getOptions() - Method in class weka.classifiers.rules.PART: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.SingleClassifierEnhancer: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.HoeffdingTree: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.J48: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.LMT: Gets the current settings of the Classifier.
getOptions() - Method in class weka.classifiers.trees.m5.M5Base: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.M5P: Gets the current settings of the classifier.
getOptions() - Method in class weka.classifiers.trees.RandomForest: Gets the current settings of the forest.
getOptions() - Method in class weka.classifiers.trees.RandomTree: Gets options from this classifier.
getOptions() - Method in class weka.classifiers.trees.REPTree: Gets options from this classifier.
getOptions() - Method in class weka.clusterers.AbstractClusterer: Gets the current settings of the clusterer.
getOptions() - Method in class weka.clusterers.Canopy: Gets the current settings of Canopy.
getOptions() - Method in class weka.clusterers.CheckClusterer: Gets the current settings of the CheckClusterer.
getOptions() - Method in class weka.clusterers.Cobweb: Gets the current settings of Cobweb.
getOptions() - Method in class weka.clusterers.EM: Gets the current settings of EM.
getOptions() - Method in class weka.clusterers.FarthestFirst: Gets the current settings of FarthestFirst
getOptions() - Method in class weka.clusterers.FilteredClusterer: Gets the current settings of the clusterer.
getOptions() - Method in class weka.clusterers.HierarchicalClusterer: Gets the current settings of the clusterer.
getOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer: Gets the current settings of the clusterer.
getOptions() - Method in class weka.clusterers.RandomizableClusterer: Gets the current settings of the classifier.
getOptions() - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Gets the current settings of the classifier.
getOptions() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Gets the current settings of the classifier.
getOptions() - Method in class weka.clusterers.SimpleKMeans: Gets the current settings of SimpleKMeans.
getOptions() - Method in class weka.clusterers.SingleClustererEnhancer: Gets the current settings of the clusterer.
getOptions() - Method in class weka.core.Check: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.core.CheckGOE: Gets the current settings of the object.
getOptions() - Method in class weka.core.CheckOptionHandler: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.core.CheckScheme: Gets the current settings of the CheckClassifier.
getOptions() - Method in class weka.core.converters.AbstractFileSaver: Gets the current settings of the Saver object.
getOptions() - Method in class weka.core.converters.ArffSaver: returns the options of the current setup
getOptions() - Method in class weka.core.converters.C45Saver: Gets the current settings of the C45Saver object.
getOptions() - Method in class weka.core.converters.CSVLoader
getOptions() - Method in class weka.core.converters.CSVSaver: Gets the current settings of the Classifier.
getOptions() - Method in class weka.core.converters.DatabaseLoader: Gets the setting
getOptions() - Method in class weka.core.converters.DatabaseSaver: Gets the setting.
getOptions() - Method in class weka.core.converters.JSONSaver: returns the options of the current setup.
getOptions() - Method in class weka.core.converters.LibSVMSaver: returns the options of the current setup
getOptions() - Method in class weka.core.converters.MatlabSaver: returns the options of the current setup.
getOptions() - Method in class weka.core.converters.SVMLightSaver: returns the options of the current setup.
getOptions() - Method in class weka.core.converters.TextDirectoryLoader: Gets the setting
getOptions() - Method in class weka.core.converters.XRFFSaver: returns the options of the current setup
getOptions() - Method in class weka.core.DictionaryBuilder: Gets the current settings of the DictionaryBuilder
getOptions() - Method in class weka.core.FilteredDistance: Gets the current settings.
getOptions() - Method in class weka.core.FindWithCapabilities: Gets the current settings of this object.
getOptions() - Method in class weka.core.Javadoc: Gets the current settings of this object.
getOptions() - Method in class weka.core.ListOptions: Gets the current settings of this object.
getOptions() - Method in class weka.core.MinkowskiDistance: Gets the current settings of this object.
getOptions() - Method in class weka.core.neighboursearch.BallTree: Gets the current settings of KDtree.
getOptions() - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Gets the current settings of the object.
getOptions() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Gets the current settings.
getOptions() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Gets the current settings of the object.
getOptions() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Gets the current settings.
getOptions() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Gets the current settings of this BallTree MiddleOutConstructor.
getOptions() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Gets the current settings of KDtree.
getOptions() - Method in class weka.core.neighboursearch.CoverTree: Gets the current settings of KDtree.
getOptions() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Gets the current settings.
getOptions() - Method in class weka.core.neighboursearch.KDTree: Gets the current settings of KDtree.
getOptions() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Gets the current settings of the object.
getOptions() - Method in class weka.core.neighboursearch.LinearNNSearch: Gets the current settings.
getOptions() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Gets the current settings.
getOptions() - Method in class weka.core.NormalizableDistance: Gets the current settings.
getOptions(Object, Class<?>) - Static method in class weka.core.Option: Get the settings of the supplied object.
getOptions() - Method in interface weka.core.OptionHandler: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.OptionHandlerJavadoc: Gets the current settings of this object.
getOptions() - Method in class weka.core.stemmers.SnowballStemmer: Gets the current settings of the classifier.
getOptions() - Method in class weka.core.stopwords.AbstractFileBasedStopwords: Gets the current settings of the Classifier.
getOptions() - Method in class weka.core.stopwords.AbstractStopwords: Gets the current settings of the Classifier.
getOptions() - Method in class weka.core.stopwords.MultiStopwords: Gets the current settings of the Classifier.
getOptions() - Method in class weka.core.TechnicalInformationHandlerJavadoc: Gets the current settings of this object.
getOptions() - Method in class weka.core.TestInstances: Gets the current settings of this object.
getOptions() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.NGramTokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.core.tokenizers.Tokenizer: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.datagenerators.ClassificationGenerator: Gets the current settings of the classifier.
getOptions() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Gets the current settings of the datagenerator.
getOptions() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the current settings of the datagenerator.
getOptions() - Method in class weka.datagenerators.classifiers.classification.LED24: Gets the current settings of the datagenerator.
getOptions() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Gets the current settings of the datagenerator.
getOptions() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the current settings of the datagenerator RDG1.
getOptions() - Method in class weka.datagenerators.classifiers.regression.Expression: Gets the current settings of the datagenerator BIRCHCluster.
getOptions() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Gets the current settings of the datagenerator BIRCHCluster.
getOptions() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the current settings of the datagenerator BIRCHCluster.
getOptions() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Gets the current settings of the datagenerator.
getOptions() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Gets the current settings of the datagenerator BIRCHCluster.
getOptions() - Method in class weka.datagenerators.ClusterGenerator: Gets the current settings of the classifier.
getOptions() - Method in class weka.datagenerators.DataGenerator: Gets the current settings of the datagenerator RDG1.
getOptions() - Method in class weka.datagenerators.RegressionGenerator: Gets the current settings of the classifier.
getOptions() - Method in class weka.estimators.CheckEstimator: Gets the current settings of the CheckEstimator.
getOptions() - Method in class weka.estimators.Estimator: Gets the current settings of the Estimator.
getOptions() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the current set of options.
getOptions() - Method in class weka.experiment.AveragingResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.CrossValidationResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.CSVResultListener: Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.DatabaseResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.Experiment: Gets the current settings of the experiment iterator.
getOptions() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.InstanceQuery: Gets the current settings of InstanceQuery
getOptions() - Method in class weka.experiment.LearningRateResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.PairedTTester: Gets current settings of the PairedTTester.
getOptions() - Method in class weka.experiment.RandomSplitResultProducer: Gets the current settings of the result producer.
getOptions() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the current settings of the Classifier.
getOptions() - Method in class weka.experiment.ResultMatrix: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.filters.CheckSource: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.Filter: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.MultiFilter: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.AddClassification: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection: Gets the current settings for the attribute selection (search, evaluator) etc.
getOptions() - Method in class weka.filters.supervised.attribute.ClassOrder: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.Discretize: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.attribute.PartitionMembership: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.Resample: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Add: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddID: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Gets the current settings of the filter
getOptions() - Method in class weka.filters.unsupervised.attribute.AddValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Copy: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MathExpression: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NominalToString: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Normalize: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericToBinary
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.Remove: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveByName: returns the options of the current setup.
getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
getOptions() - Method in class weka.filters.unsupervised.attribute.Reorder: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
getOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SortLabels: Gets the current settings of the classifier.
getOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse
getOptions() - Method in class weka.filters.unsupervised.instance.Randomize: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.Resample: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Gets the current settings of the filter.
getOptions() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Gets the current settings of the filter.
getOptions() - Method in class weka.gui.explorer.AbstractPlotInstances: Gets the current option settings for the OptionHandler.
getOptions() - Method in class weka.gui.Main: returns the options of the current setup.
getOptions() - Method in class weka.gui.scripting.Script: Gets the current settings of the script.
getOptionsForHierarchy(Object, Class<?>) - Static method in class weka.core.Option: Get the settings of the supplied object.
getOPTYPE(int) - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Returns an OPTYPE for a weka attribute type.
getOptype() - Method in class weka.core.pmml.Expression: Get the optype of the result of applying this Expression.
getOptype() - Method in class weka.core.pmml.FieldMetaInfo: Get the optype.
getOptype() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.ParameterField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the optype property.
getOptype() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the optype property.
getOrder() - Method in enum weka.core.logging.Logger.Level: Returns the order of this level.
getOrder() - Method in class weka.core.MinkowskiDistance: Gets the order.
getOrderedFlag() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the ordered flag (option O).
getOrig() - Method in class weka.core.pmml.jaxbbindings.LinearNorm: Gets the value of the orig property.
getOriginalCoords() - Method in class weka.gui.beans.MetaBean: returns the vector containing the original coordinates (instances of class Point) for the inputs
getOtherCapabilities() - Method in class weka.core.Capabilities: returns all other capabilities, besides class and attribute related ones
getOutgoingConnectedStepsOfConnectionType(String) - Method in interface weka.knowledgeflow.StepManager: Get a list of downstream steps connected to this step with the given connection type.
getOutgoingConnectedStepsOfConnectionType(String) - Method in class weka.knowledgeflow.StepManagerImpl
getOutgoingConnectedStepWithName(String) - Method in interface weka.knowledgeflow.StepManager: Get a named step connected to this step with an outgoing connection
getOutgoingConnectedStepWithName(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get a named step connected to this step with an outgoing connection
getOutgoingConnections() - Method in interface weka.knowledgeflow.StepManager: Get a Map of all outgoing connections.
getOutgoingConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Get the map of downstream (outgoing connections) connected steps
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get the list of outgoing connection types that can be made given the current state of incoming connections
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Appender: Get a list of outgoing connection types that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get a list of output connections that can be produced given the current state of the step
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Get a list of outgoing connections from this step.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Associator: Get a list of outgoing connections that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Get a list of outgoing connections that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer: Get a list of outgoing connection types that this step can produce at this time.
getOutgoingConnectionTypes() - Method in interface weka.knowledgeflow.steps.BaseStepExtender: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Block: Get a list of outgoing connection types that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassAssigner: Get the outgoing connection types that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Classifier
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClassValuePicker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Clusterer: Get a list of outgoing connections that could be made from this step at this point in time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ClustererPerformanceEvaluator: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataGenerator: Get a list of outgoing connection types
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataGrid
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.DataVisualizer
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Dummy: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get a list of possible outgoing connection types at this point in time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Filter: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.GetDataFromResult
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.GraphViewer: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ImageSaver: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ImageViewer: Get a list of outgoing connections that can be generated given the current state of the step - will produce StepManager.CON_IMAGE data if we have at least one incoming image connection connection
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.InstanceStreamToBatchMaker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Job
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Join: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Loader: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Note: Get outgoing connections produced - none in the case of a note :-)
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.PredictionAppender: Get a list of outgoing connection types that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Saver: Get a list of outgoing connection types that this step can produce at this time
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SendToPerspective
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SetPropertiesFromEnvironment
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SetVariables: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.Sorter: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in interface weka.knowledgeflow.steps.Step: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.StripChart: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.SubstringReplacer: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TestSetMaker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TextSaver: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TextViewer: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TrainingSetMaker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Get a list of outgoing connection types that this step can produce.
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.WriteDataToResult
getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.WriteWekaLog: Get currently generatable outgoing connection types
getOutlierFactor() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets the factor for determining the thresholds for outliers.
getOutliers() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the outliers property.
getOutliers() - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Gets the value of the outliers property.
getOutlierTreatmentMethod() - Method in class weka.core.pmml.MiningFieldMetaInfo: Get the outlier treatment method used for this field.
getOutOfBagEvaluationObject() - Method in class weka.classifiers.meta.Bagging: Returns the out-of-bag evaluation object.
getOutput() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the output property.
getOutput() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the output property.
getOutput() - Method in class weka.datagenerators.DataGenerator: Gets the print writer.
getOutput() - Method in class weka.gui.explorer.DataGeneratorPanel: returns the generated output as text
getOutput() - Method in class weka.gui.scripting.FileScriptingPanel: Returns the text area that is used for displaying output on stdout and stderr.
getOutput() - Method in class weka.gui.scripting.ScriptingPanel: Returns the text area that is used for displaying output on stdout and stderr.
getOutput() - Method in class weka.gui.SimpleCLIPanel: Returns the text area that is used for displaying output on stdout and stderr.
getOutputAdditionalStats() - Method in class weka.classifiers.functions.LinearRegression: Get whether to output additional statistics (such as std.
getOutputAdditionalStats() - Method in class weka.classifiers.functions.SimpleLinearRegression: Get whether to output additional statistics (such as std.
getOutputArea() - Method in class weka.gui.SimpleCLIPanel: The output area.
getOutputClassification() - Method in class weka.filters.supervised.attribute.AddClassification: Get whether the classifiction of the classifier is output.
getOutputColumn() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the outputColumn property.
getOutputConfusionMatrix() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
getOutputDef() - Method in class weka.core.pmml.BuiltInArithmetic: Get the structure of the result produced by this function.
getOutputDef() - Method in class weka.core.pmml.BuiltInMath: Get the structure of the result produced by this function.
getOutputDef() - Method in class weka.core.pmml.BuiltInString: Get the structure of the result produced by this function.
getOutputDef() - Method in class weka.core.pmml.DefineFunction: Get the structure of the result produced by this function.
getOutputDef() - Method in class weka.core.pmml.FieldRef: Return the structure of the result of applying this Expression as an Attribute.
getOutputDef() - Method in class weka.core.pmml.Function: Get the structure of the result produced by this function.
getOutputDetailedInfo() - Method in class weka.attributeSelection.CorrelationAttributeEval: Get whether to output per-value correlation for nominal attributes
getOutputDirectory() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Get the directory to save to
getOutputDistribution() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns whether to output the class distribution as well.
getOutputDistribution() - Method in class weka.filters.supervised.attribute.AddClassification: Get whether the classifiction of the classifier is output.
getOutputEntropyMetrics() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
getOutputErrorFlag() - Method in class weka.filters.supervised.attribute.AddClassification: Get whether the classifiction of the classifier is output.
getOutputFields() - Method in class weka.core.pmml.jaxbbindings.Output: Gets the value of the outputField property.
getOutputFile() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the output file to write to.
getOutputFile() - Method in class weka.experiment.CrossValidationResultProducer: Get the value of OutputFile.
getOutputFile() - Method in class weka.experiment.CSVResultListener: Get the value of OutputFile.
getOutputFile() - Method in class weka.experiment.ExplicitTestsetResultProducer: Get the value of OutputFile.
getOutputFile() - Method in class weka.experiment.RandomSplitResultProducer: Get the value of OutputFile.
getOutputFilename() - Method in class weka.core.converters.TextDirectoryLoader: Gets whether the filename will be stored as an extra attribute.
getOutputFilename() - Method in class weka.gui.GenericPropertiesCreator: returns the name of the output file
getOutputFormat() - Method in class weka.core.Debug.Clock: returns the output format
getOutputFormat() - Method in class weka.filters.Filter: Gets the format of the output instances.
getOutputFormat() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Gets the format of the output instances.
getOutputFormat() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the classname (and optional options) of the ResultMatrix class, responsible for the output format.
getOutputItemSets() - Method in class weka.associations.Apriori: Gets whether itemsets are output as well
getOutputNeuron() - Method in class weka.core.pmml.jaxbbindings.NeuralOutput: Gets the value of the outputNeuron property.
getOutputNums() - Method in class weka.classifiers.functions.neural.NeuralConnection: Use this to get easy access to the output numbers.
getOutputOffsetMultiplier() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Gets whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.
getOutputOutOfBagComplexityStatistics() - Method in class weka.classifiers.meta.Bagging: Gets whether complexity statistics are output when OOB estimation is performed.
getOutputPerClassInfoRetrievalStats() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Get whether per-class information retrieval stats are to be output.
getOutputPerClassInfoRetrievalStats() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Get whether per-class information retrieval stats are to be output.
getOutputPerClassStats() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
getOutputProbsForSVM() - Method in class weka.classifiers.functions.SGDText: Get whether to fit a logistic regression (itself trained using SGD) to the outputs of the SVM (if an SVM is being learned).
getOutputProperties() - Method in class weka.gui.GenericPropertiesCreator: returns the output properties object (structure like the template, but filled with classes instead of packages)
getOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection: Use this to get easy access to the outputs.
getOutputs() - Method in class weka.gui.beans.MetaBean
getOutputStructure() - Method in class weka.gui.beans.SubstringLabelerRules: Get the output structure
getOutputTypes() - Method in class weka.core.Debug.DBO: Gets the current output type selection
getOutputWordCounts() - Method in class weka.core.DictionaryBuilder: Gets whether output instances contain 0 or 1 indicating word presence, or word counts.
getOutputWordCounts() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets whether output instances contain 0 or 1 indicating word presence, or word counts.
getOutputWordCounts() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets whether output instances contain 0 or 1 indicating word presence, or word counts.
getOverwriteWarning() - Method in class weka.gui.ConverterFileChooser: Returns whether a popup appears with a warning that the file already exists (only save dialog).
getOwner() - Method in class weka.core.Capabilities: returns the owner of this capabilities object
getOwner() - Static method in class weka.core.Copyright: returns the entity owning the copyright
getOwner() - Method in class weka.gui.scripting.Script.ScriptThread: Returns the owner.
getOwner() - Method in class weka.gui.simplecli.AbstractCommand: Returns the owner.
getP() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the proportion of instances that are common between two training sets.
getPackage() - Method in class weka.core.packageManagement.PackageConstraint: Get the package that this constraint applies to.
getPackage(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: returns the packages part of the partial classname.
getPackageArchiveInfo(String) - Method in class weka.core.packageManagement.DefaultPackageManager: Get package information from the supplied package archive file.
getPackageArchiveInfo(String) - Method in class weka.core.packageManagement.PackageManager: Get package information from the supplied package archive file.
getPackageArchiveInfo(String) - Static method in class weka.core.WekaPackageManager: Extract meta data from a package archive
getPackageClassLoader(String) - Method in class weka.core.WekaPackageClassLoaderManager: Get the classloader for the named package
getPackageClassLoadersForDependencies() - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Gets a list of class loaders for the packages that this one depends on
getPackageHome() - Method in class weka.core.packageManagement.PackageManager: Get the location (directory) of installed packages
getPackageHome() - Static method in class weka.core.WekaPackageManager
getPackageJarEntries() - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Get a Set of the names of all classes contained within top-level jar files in this package
getPackageJarFileClasses() - Method in class weka.core.WekaPackageClassLoaderManager: Get a set of all classes contained in all top-level jar files from Weka packages.
getPackageList(boolean) - Static method in class weka.core.WekaPackageManager: Just get a list of the package names.
getPackageMetaData() - Method in class weka.core.packageManagement.Package: Get the meta data for this package.
getPackageMetaDataElement(Object) - Method in class weka.core.packageManagement.Package: Gets the package meta data element associated with the supplied key.
getPackageName() - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Return the name of the package that this classloader loads classes for
getPackageRepositoryURL() - Method in class weka.core.packageManagement.PackageManager: Get the URL to the repository of package meta data.
getPackageRepositoryURL() - Static method in class weka.core.WekaPackageManager: Get the package repository URL
getPackageURL() - Method in class weka.core.packageManagement.DefaultPackage: Convenience method that returns the URL to the package (i.e the provider's URL).
getPackageURL() - Method in class weka.core.packageManagement.Package: Convenience method that returns the URL to the package (i.e the provider's URL).
getPaint() - Method in class weka.gui.visualize.PostscriptGraphics
getPairCounts() - Method in class weka.core.pmml.jaxbbindings.BayesInput: Gets the value of the pairCounts property.
getPalleteSelectedStep() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Return the currently selected step in the design palette
getPanel(int) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the specified panel, null if index is out of bounds
getPanel() - Method in class weka.gui.scripting.event.TitleUpdatedEvent: Returns the scripting panel that triggered the event.
getPanelCount() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the number of panels currently open
getPanels() - Static method in class weka.gui.experiment.AbstractSetupPanel: Returns a list of all available setup panels.
getPanels() - Method in class weka.gui.explorer.Explorer: returns all the panels, apart from the PreprocessPanel
getParameter() - Method in class weka.core.pmml.jaxbbindings.ParameterList: Gets the value of the parameter property.
getParameterField() - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Gets the value of the parameterField property.
getParameterHelp() - Method in class weka.gui.simplecli.AbstractCommand: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Capabilities: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Cls: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Echo: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Exit: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Help: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.History: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Java: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Kill: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Script: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Set: Returns the one-liner help string for the parameters.
getParameterHelp() - Method in class weka.gui.simplecli.Unset: Returns the one-liner help string for the parameters.
getParameterName() - Method in class weka.core.pmml.jaxbbindings.PCell: Gets the value of the parameterName property.
getParameterName() - Method in class weka.core.pmml.jaxbbindings.PPCell: Gets the value of the parameterName property.
getParameterNames() - Method in class weka.core.pmml.BuiltInArithmetic: Returns an array of the names of the parameters expected as input by this function
getParameterNames() - Method in class weka.core.pmml.BuiltInMath: Returns an array of the names of the parameters expected as input by this function.
getParameterNames() - Method in class weka.core.pmml.BuiltInString: Returns an array of the names of the parameters expected as input by this function.
getParameterNames() - Method in class weka.core.pmml.DefineFunction: Returns an array of the names of the parameters expected as input by this function.
getParameterNames() - Method in class weka.core.pmml.Function: Returns an array of the names of the parameters expected as input by this function.
getParent(int, int) - Method in class weka.classifiers.bayes.BayesNet: get node index of a parent of a node in the network structure
getParent(int) - Method in class weka.classifiers.bayes.net.ParentSet: returns index parent of parent specified by index
getParent() - Method in class weka.datagenerators.ClusterDefinition: returns the parent datagenerator this cluster belongs to
getParent(int) - Method in class weka.gui.treevisualizer.Node: Get the parent edge.
getParentCardinality(int) - Method in class weka.classifiers.bayes.BayesNet: get number of values the collection of parents of a node can take
getParentDialog(Container) - Static method in class weka.gui.PropertyDialog: Tries to determine the dialog this panel is part of.
getParentField() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the parentField property.
getParentFrame() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the parent frame, if it's a JFrame, otherwise null
getParentFrame() - Method in class weka.gui.GUIChooserApp.ChildFrameSDI: returns the parent frame, can be null.
getParentFrame() - Method in class weka.gui.Main.ChildFrameMDI: returns the parent frame, can be null.
getParentFrame() - Method in class weka.gui.Main.ChildFrameSDI: returns the parent frame, can be null.
getParentFrame(Container) - Static method in class weka.gui.PropertyDialog: Tries to determine the frame this panel is part of.
getParentFrame() - Method in class weka.gui.SetInstancesPanel: Returns the current frame the panel knows of, that it resides in.
getParentInternalFrame() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the parent frame, if it's a JInternalFrame, otherwise null
getParentInternalFrame(Container) - Static method in class weka.gui.PropertyDialog: Tries to determine the internal frame this panel is part of.
getParentLevelField() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the parentLevelField property.
getParents() - Method in class weka.classifiers.bayes.net.ParentSet
getParentSet(int) - Method in class weka.classifiers.bayes.BayesNet: get the parent set of a node
getParentSets() - Method in class weka.classifiers.bayes.BayesNet: Get full set of parent sets.
getPartialScore() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the partialScore property.
getPartition() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the partition property.
getPartition() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the partition property.
getPartitionFieldStats() - Method in class weka.core.pmml.jaxbbindings.Partition: Gets the value of the partitionFieldStats property.
getPartitionGenerator() - Method in class weka.filters.supervised.attribute.PartitionMembership: Get the generator used by this filter
getPassword() - Method in class weka.core.converters.DatabaseLoader: Returns the database password
getPassword() - Method in class weka.core.converters.DatabaseSaver: Returns the database password.
getPassword() - Method in class weka.experiment.DatabaseUtils: Get the database password.
getPassword() - Method in class weka.gui.DatabaseConnectionDialog: Returns password from dialog
getPassword() - Method in class weka.gui.sql.ConnectionPanel: returns the current Password.
getPassword() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the password that produced the table model
getPassword() - Method in class weka.gui.sql.ResultSetTable: returns the password that produced the table model
getPassword() - Method in class weka.gui.sql.SqlViewer: returns the password from the currently active tab in the ResultPanel, otherwise an empty string.
getPassword() - Method in class weka.gui.sql.SqlViewerDialog: returns the chosen password, if any.
getPasteBuffer() - Method in class weka.gui.beans.KnowledgeFlowApp: Get the contents of the paste buffer
getPasteBuffer() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the contents of the paste buffer
getPath() - Method in class weka.gui.PropertySelectorDialog: Gets the path of property nodes to the selected property.
getPathToWekaJarFile() - Method in class weka.core.WekaPackageClassLoaderManager: Return the path to the weka.jar file (if found) on the classpath.
getPattern() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the pattern type.
getPayloadElement(String) - Method in class weka.knowledgeflow.Data: Get a payload element from this Data object.
getPayloadElement(String, T) - Method in class weka.knowledgeflow.Data: Get a payload element from this Data object.
getPCell() - Method in class weka.core.pmml.jaxbbindings.ParamMatrix: Gets the value of the pCell property.
getPCol() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the pCol property.
getPCovCell() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix: Gets the value of the pCovCell property.
getPercent() - Method in class weka.filters.unsupervised.attribute.AddNoise: Gets the size of noise data as a percentage of the original set.
getPercent() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Gets the percent the attributes (dimensions) of the data will be reduced to
getPercentage() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Gets the percentage of instances to select.
getPercentageSplit() - Method in class weka.gui.explorer.ClassifierPanel: Get the percentage to use for percentage split evaluation
getPercentCompleted() - Method in class weka.gui.boundaryvisualizer.RemoteResult: Return the progress for this row
getPerformanceStats() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Gets the class object that contains the performance statistics of the search method.
getPeriod() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the period property.
getPeriodicPruning() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get how often to prune the dictionary
getPeriodicPruning() - Method in class weka.classifiers.functions.SGDText: Get how often to prune the dictionary
getPeriodicPruning() - Method in class weka.core.converters.DictionarySaver: Gets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
getPeriodicPruning() - Method in class weka.core.DictionaryBuilder: Gets the rate (number of instances) at which the dictionary is periodically pruned.
getPeriodicPruning() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
getPeriodicPruningRate() - Method in class weka.clusterers.Canopy: Get the how often to prune low density canopies during training
getPerspective(String) - Method in class weka.gui.PerspectiveManager: Get the perspective with the given ID
getPerspectiveIcon() - Method in class weka.gui.AbstractPerspective: Get the icon for this perspective
getPerspectiveIcon() - Method in class weka.gui.beans.AttributeSummarizer: Get the icon for this perspective.
getPerspectiveIcon() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Get the icon for this perspective.
getPerspectiveIcon() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective: Get the icon for this perspective
getPerspectiveIcon() - Method in class weka.gui.beans.ScatterPlotMatrix: Get the icon for this perspective.
getPerspectiveIcon() - Method in class weka.gui.beans.SQLViewerPerspective: Get the icon for this perspective.
getPerspectiveIcon() - Method in interface weka.gui.Perspective: Get the icon for this perspective
getPerspectiveIcon() - Method in class weka.gui.SimpleCLIPanel
getPerspectiveID() - Method in class weka.gui.AbstractPerspective: Get the ID of this perspective
getPerspectiveID() - Method in interface weka.gui.Perspective: Get the ID of this perspective
getPerspectiveID() - Method in class weka.gui.SimpleCLIPanel
getPerspectiveManager() - Method in class weka.gui.AbstractGUIApplication: Get the PerspectiveManager in use by this application
getPerspectiveManager() - Method in interface weka.gui.GUIApplication: Get the PerspectiveManager in use by this application
getPerspectiveManager() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Get the PerspectiveManager used by this application
getPerspectiveName() - Method in class weka.knowledgeflow.steps.SendToPerspective
GetPerspectiveNamesGraphicalCommand - Class in weka.gui.knowledgeflow: Class implementing a command for getting the names of all visible perspectives
GetPerspectiveNamesGraphicalCommand() - Constructor for class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand
getPerspectivesToolbarAlwaysHidden() - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Get whether the perspectives toolbar should always be hidden
getPerspectivesToolbarVisibleOnStartup() - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Get whether the perspectives toolbar should be visible in the GUI at application startup
getPerspectiveTipText() - Method in class weka.gui.AbstractPerspective: Get the tool tip text for this perspective
getPerspectiveTipText() - Method in class weka.gui.beans.AttributeSummarizer: Get the tool tip text for this perspective.
getPerspectiveTipText() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Get the tool tip text for this perspective.
getPerspectiveTipText() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective: Get the tool tip text for this perspective
getPerspectiveTipText() - Method in class weka.gui.beans.ScatterPlotMatrix: Get the tool tip text for this perspective.
getPerspectiveTipText() - Method in class weka.gui.beans.SQLViewerPerspective: Get the tool tip text for this perspective.
getPerspectiveTipText() - Method in interface weka.gui.Perspective: Get the tool tip text for this perspective
getPerspectiveTipText() - Method in class weka.gui.SimpleCLIPanel
getPerspectiveTitle() - Method in class weka.gui.AbstractPerspective: Get the title of this perspective
getPerspectiveTitle() - Method in class weka.gui.beans.AttributeSummarizer: Get the title of this perspective
getPerspectiveTitle() - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Get the title of this perspective
getPerspectiveTitle() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective: Get the title of this perspective
getPerspectiveTitle() - Method in class weka.gui.beans.ScatterPlotMatrix: Get the title of this perspective
getPerspectiveTitle() - Method in class weka.gui.beans.SQLViewerPerspective: Get the title of this perspective
getPerspectiveTitle() - Method in interface weka.gui.Perspective: Get the title of this perspective
getPerspectiveTitle() - Method in class weka.gui.SimpleCLIPanel
getPerspectiveToolBar() - Method in class weka.gui.PerspectiveManager: Get the panel that contains the perspectives toolbar
getPerturbationFraction() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Gets the perturbation fraction.
getPhase() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the phase property.
getPhi() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Gets the value of the phi property.
getPickList() - Method in class weka.core.Settings.SettingKey: Get the optional pick list for the setting
getPivot() - Method in class weka.core.matrix.LUDecomposition: Return pivot permutation vector
getPivot() - Method in class weka.core.neighboursearch.balltrees.BallNode: Returns the pivot/centre of the node's ball.
getPlainColumnName(int) - Method in class weka.gui.arffviewer.ArffTable: returns the basically the attribute name of the column and not the HTML column name via getColumnName(int)
getPlainTitle() - Method in class weka.gui.scripting.FileScriptingPanel: Returns the title (without the filename).
getPlainTitle() - Method in class weka.gui.scripting.GroovyPanel: Returns the title (without the filename).
getPlainTitle() - Method in class weka.gui.scripting.JythonPanel: Returns the title (without the filename).
getPlotData(String) - Method in class weka.gui.explorer.AbstractPlotInstances: Assembles and returns the plot.
getPlotInstances() - Method in class weka.gui.explorer.AbstractPlotInstances: Returns the generated plot instances.
getPlotInstances() - Method in class weka.gui.visualize.PlotData2D: Returns the instances for this plot
getPlotName() - Method in class weka.gui.visualize.PlotData2D: Get the name of this plot
getPlotNameHTML() - Method in class weka.gui.visualize.PlotData2D: Get the name of the plot for use in a tool tip text.
getPlotPanel() - Method in class weka.gui.visualize.VisualizePanel: Returns the underlying plot panel.
getPlots() - Method in class weka.gui.visualize.Plot2D: Return the list of plots
getPlots() - Method in class weka.knowledgeflow.steps.DataVisualizer
getPlots() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Get the plots currently stored in this step
getPlotShapes() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Get the vector of plot shapes (see weka.gui.visualize.Plot2D).
getPlotSizes() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Get the vector of plot sizes (see weka.gui.visualize.Plot2D).
getPlotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Returns true if training data is to be superimposed
getPlotTrainingData() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get whether to superimpose the training data points on the plot or not
getPluginInstance(String, String) - Static method in class weka.core.PluginManager: Get an instance of a concrete implementation of a plugin type
getPluginInstance(String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Get an instance of a concrete implementation of a plugin type
getPluginMetric(String) - Method in class weka.classifiers.evaluation.Evaluation: Get the named plugin evaluation metric
getPluginMetric(String) - Method in class weka.classifiers.Evaluation: Get the named plugin evaluation metric
getPluginMetricNames() - Static method in class weka.classifiers.evaluation.EvaluationMetricHelper: Get a list of plugin metric names
getPluginMetrics() - Static method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Gets a list of freshly instantiated concrete implementations of available plugin metrics or null if there are no plugin metrics available
getPluginMetrics() - Method in class weka.classifiers.evaluation.Evaluation: Returns the list of plugin metrics in use (or null if there are none)
getPluginMetrics() - Method in class weka.classifiers.Evaluation: Returns the list of plugin metrics in use (or null if there are none)
getPluginNamesOfType(String) - Static method in class weka.core.PluginManager: Get a set of names of plugins that implement the supplied interface.
getPluginNamesOfType(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Get a set of names of plugins that implement the supplied interface.
getPluginNamesOfTypeList(String) - Static method in class weka.core.PluginManager: Get a sorted list of names of plugins that implement the supplied interface.
getPluginResourceAsStream(String, String) - Static method in class weka.core.PluginManager: Get an input stream for a named resource under a given resource group ID.
getPluginResourceAsStream(String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Get an input stream for a named resource under a given resource group ID.
getPluginTemplateDescriptions() - Method in class weka.gui.knowledgeflow.TemplateManager: Get descriptions for plugin knowledge flow templates
getPluginTemplateFlow(String) - Method in class weka.gui.knowledgeflow.TemplateManager: Get the plugin template flow corresponding to the description
getPMMLModel(String) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLModel(File) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLModel(InputStream) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLModel(String, Logger) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLModel(File, Logger) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLModel(InputStream, Logger) - Static method in class weka.core.pmml.PMMLFactory: Read and return a PMML model.
getPMMLVersion() - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Get the PMML version used for this model.
getPMMLVersion() - Method in interface weka.core.pmml.PMMLModel: Get the version of PMML used to encode this model.
getPointSizeProportionalToMargin() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Get whether the point size should be proportional to the prediction margin (classification only).
getPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate: Gets the value of the poissonDistribution property.
getPoissonDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the poissonDistribution property.
getPoolSize() - Method in class weka.attributeSelection.CfsSubsetEval: Gets the number of threads.
getPoolSize() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Gets the number of threads.
getPoolSize() - Method in class weka.classifiers.meta.LogitBoost: Gets the number of threads.
getPopulationSize() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getPopulationSize() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getPopup() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: returns the currently set JPopupMenu.
getPositionX(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: get x position of a node
getPositionY(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: get y position of a node
getPositiveIndex() - Method in class weka.associations.FPGrowth: Get the index of the attribute value to consider as positive for binary attributes in normal dense instances.
getPositiveTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the positiveTargetFieldDisplayValue property.
getPositiveTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the positiveTargetFieldValue property.
getPossibleSplits(SplitMetric) - Method in class weka.classifiers.trees.ht.ActiveHNode: Returns a list of split candidates
getPostProcessor() - Method in class weka.core.CheckScheme: returns the current PostProcessor, can be null
getPostProcessor() - Method in class weka.estimators.CheckEstimator: returns the current PostProcessor, can be null
getPParameter() - Method in class weka.core.pmml.jaxbbindings.Minkowski: Gets the value of the pParameter property.
getPPCell() - Method in class weka.core.pmml.jaxbbindings.PPMatrix: Gets the value of the ppCell property.
getPRCArea(Instances) - Static method in class weka.classifiers.evaluation.ThresholdCurve: Calculates the area under the precision-recall curve (AUPRC).
getPreBuiltClassifiers() - Method in class weka.classifiers.meta.Vote: Get the paths to pre-built serialized classifiers to load and include in the ensemble
getPrecision() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the precision.
getPrecision() - Method in class weka.core.pmml.jaxbbindings.VerificationField: Gets the value of the precision property.
getPrecision() - Method in class weka.estimators.KernelEstimator: Return the precision of this kernel estimator.
getPrecision() - Method in class weka.estimators.NormalEstimator: Return the value of the precision of this normal estimator.
getPrecludedPackages(List<Package>) - Method in class weka.core.packageManagement.DefaultPackage: Compares this package's precluded list (if any) against the list of supplied packages.
getPrecludedPackages(List<Package>) - Method in class weka.core.packageManagement.Package: Compares this package's precluded list (if any) against the list of supplied packages.
getPreComputeCorrelationMatrix() - Method in class weka.attributeSelection.CfsSubsetEval: Get whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.
getPrediction(Classifier, Instance) - Method in class weka.classifiers.evaluation.EvaluationUtils: Generate a single prediction for a test instance given the pre-trained classifier.
getPredictions() - Method in class weka.classifiers.evaluation.output.prediction.InMemory: Returns the collected predictions.
getPredictiveModelQuality() - Method in class weka.core.pmml.jaxbbindings.ModelExplanation: Gets the value of the predictiveModelQuality property.
getPredictor() - Method in class weka.core.pmml.jaxbbindings.CovariateList: Gets the value of the predictor property.
getPredictor() - Method in class weka.core.pmml.jaxbbindings.FactorList: Gets the value of the predictor property.
getPredictorName() - Method in class weka.core.pmml.jaxbbindings.PPCell: Gets the value of the predictorName property.
getPredictorTerm() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the predictorTerm property.
getPredTargetColumn() - Method in class weka.experiment.ClassifierSplitEvaluator
getPreferredScrollableViewportSize() - Method in class weka.gui.AttributeSelectionPanel
getPrefix() - Method in class weka.gui.beans.SerializedModelSaver: Get the prefix to prepend to the model file names.
getPremise() - Method in class weka.associations.AssociationRule: Get the premise of this rule.
getPremise() - Method in class weka.associations.DefaultAssociationRule
getPremiseSupport() - Method in class weka.associations.AssociationRule: Get the support for the premise.
getPremiseSupport() - Method in class weka.associations.DefaultAssociationRule
getPreprocessing() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Gets the filter used for preprocessing
getPreprocessPanel() - Method in class weka.gui.explorer.Explorer: returns the instance of the PreprocessPanel being used in this instance of the Explorer
getPreserveInstancesOrder() - Method in class weka.clusterers.SimpleKMeans: Gets whether order of instances must be preserved.
getPreserveOrder() - Method in class weka.gui.beans.CrossValidationFoldMaker: Returns true if the order of the incoming instances is to be preserved under cross-validation (no randomization or stratification is done in this case).
getPreserveOrder() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Get whether to preserve the order of the input instances when creatinbg the folds
getPreserveOrder() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Get whether to preserve the order of the instances or not
getPreserveOrderInPercentageSplitEvaluation() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of PreserveOrderInPercentageSplitEvaluation.
getPrimaryMetricName() - Method in class weka.associations.AssociationRule: Get the name of the primary metric of this rule (e.g.
getPrimaryMetricName() - Method in class weka.associations.DefaultAssociationRule
getPrimaryMetricValue() - Method in class weka.associations.AssociationRule: Get the value of the metric for this rule.
getPrimaryMetricValue() - Method in class weka.associations.DefaultAssociationRule
getPrimaryPayload() - Method in class weka.knowledgeflow.Data: Get the primary payload of this data object (i.e.
getPrintClassifiers() - Method in class weka.classifiers.meta.Bagging: Get whether to print the individual ensemble classifiers in the output
getPrintColNames() - Method in class weka.experiment.ResultMatrix: returns whether column names or numbers instead are printed.
getPrintLeafModels() - Method in class weka.classifiers.trees.HoeffdingTree
getPrintNewick() - Method in class weka.clusterers.HierarchicalClusterer
getPrintRowNames() - Method in class weka.experiment.ResultMatrix: returns whether row names or numbers instead are printed.
getPriorProbability() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the priorProbability property.
getPriorProbability(String) - Method in class weka.core.pmml.TargetMetaInfo: Get the prior probability for the supplied value.
getProbabilities() - Method in class weka.gui.boundaryvisualizer.RemoteResult: Return the probability distributions for this row in the visualization
getProbability(int, int, int) - Method in class weka.classifiers.bayes.BayesNet: get particular probability of the conditional probability distribtion of a node given its parents.
getProbability(double) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Get a probability estimate for a value
getProbability() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Gets the value of the probability property.
getProbability(double, double) - Method in interface weka.estimators.ConditionalEstimator: Get a probability for a value conditional on another value
getProbability(double, double) - Method in class weka.estimators.DDConditionalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.DiscreteEstimator: Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.DKConditionalEstimator: Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.DNConditionalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.Estimator: Get a probability estimate for a value.
getProbability(double, double) - Method in class weka.estimators.KDConditionalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.KernelEstimator: Get a probability estimate for a value.
getProbability(double, double) - Method in class weka.estimators.KKConditionalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.MahalanobisEstimator: Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.NDConditionalEstimator: Get a probability estimate for a value
getProbability(double, double) - Method in class weka.estimators.NNConditionalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.NormalEstimator: Get a probability estimate for a value
getProbability(double) - Method in class weka.estimators.PoissonEstimator: Get a probability estimate for a value
getProbability() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Get the probability.
getProducer() - Method in class weka.associations.AssociationRules: Get a string describing the scheme that produced these rules.
getProgressBar() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Returns a handle to the progressBar of this LayoutEngine.
getProgressBar() - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method returns the progress bar for the LayoutEngine, which shows the progress of the layout process, if it takes a while to layout the graph
getProlog() - Method in class weka.core.OptionHandlerJavadoc: whether "Valid options are..." prolog is included in the Javadoc
getProlog() - Method in class weka.core.TechnicalInformationHandlerJavadoc: whether "Valid options are..." prolog is included in the Javadoc
getPrologue() - Method in class weka.datagenerators.DataGenerator: Gets the prologue string.
getProperties() - Method in class weka.core.converters.DatabaseConnection: Returns the underlying properties object.
getProperties() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the associated properties file.
getProperties() - Static method in class weka.gui.explorer.ExplorerDefaults: returns the associated properties file.
getProperty(String) - Method in class weka.core.EnvironmentProperties
getProperty() - Method in class weka.core.pmml.FieldMetaInfo.Value
getProperty() - Method in class weka.core.pmml.jaxbbindings.Value: Gets the value of the property property.
getPropertyArray() - Method in class weka.experiment.Experiment: Gets the array of values to set the custom property to.
getPropertyArrayLength() - Method in class weka.experiment.Experiment: Gets the number of custom iterator values that have been defined for the experiment.
getPropertyArrayValue(int) - Method in class weka.experiment.Experiment: Gets a specified value from the custom property iterator array.
getPropertyDescriptor(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath: returns the property associated with the given path, null if a problem occurred.
getPropertyDescriptor(Object, String) - Static method in class weka.core.PropertyPath: returns the property associated with the given path
getPropertyDescriptors() - Method in class weka.classifiers.misc.InputMappedClassifierBeanInfo: Get an array of PropertyDescriptors for the InputMappedClassifier's public properties.
getPropertyDescriptors() - Method in class weka.gui.beans.ClassAssignerBeanInfo: Returns the property descriptors
getPropertyDescriptors() - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorBeanInfo: Get the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.ClassValuePickerBeanInfo: Returns the property descriptors
getPropertyDescriptors() - Method in class weka.gui.beans.CrossValidationFoldMakerBeanInfo: Return the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo: Return the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.PredictionAppenderBeanInfo: Return the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.StripChartBeanInfo: Get the property descriptors for this bean
getPropertyDescriptors() - Method in class weka.gui.beans.TrainTestSplitMakerBeanInfo: Get the property descriptors for this bean
getPropertyGroupingCategory() - Method in class weka.gui.PropertySheetPanel
getPropertyPath() - Method in class weka.experiment.Experiment: Gets the path of properties taken to get to the custom property to iterate over.
getPropsInternalRep() - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
getPRow() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the pRow property.
getProxy() - Method in class weka.core.packageManagement.PackageManager: Get the proxy in use.
getPruningMethod() - Method in class weka.classifiers.functions.supportVector.StringKernel: Gets the method used for pruning.
getPValue() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the pValue property.
getPValueAlpha() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the pValueAlpha property.
getPValueFinal() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the pValueFinal property.
getPValueInitial() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the pValueInitial property.
getQ() - Method in class weka.core.matrix.QRDecomposition: Generate and return the (economy-sized) orthogonal factor
getQuality() - Method in class weka.gui.visualize.JPEGWriter: returns the quality the JPEG will be stored in.
getQuantile() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the quantile property.
getQuantileLimit() - Method in class weka.core.pmml.jaxbbindings.Quantile: Gets the value of the quantileLimit property.
getQuantileValue() - Method in class weka.core.pmml.jaxbbindings.Quantile: Gets the value of the quantileValue property.
getQuery() - Method in class weka.core.converters.DatabaseLoader: Gets the query to execute against the database
getQuery() - Method in class weka.experiment.InstanceQuery: Get the query to execute against the database
getQuery() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the query that was executed
getQuery() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the query that was executed
getQuery() - Method in class weka.gui.sql.QueryPanel: returns the currently displayed query.
getQuery() - Method in class weka.gui.sql.ResultSetTable: returns the query that produced the table model
getQuery() - Method in class weka.gui.sql.SqlViewer: returns the query from the currently active tab in the ResultPanel, otherwise an empty string.
getQuery() - Method in class weka.gui.sql.SqlViewerDialog: returns the chosen query, if any.
getQueryPanel() - Method in class weka.gui.sql.ResultPanel: returns the currently set QueryPanel, can be NULL
getQuoteDelimiters() - Method in class weka.gui.scripting.SyntaxDocument: Returns the quote delimiter characters to use.
getQuoteEscape() - Method in class weka.gui.scripting.SyntaxDocument: Returns the character for escaping a quote delimiter.
getR() - Method in class weka.core.matrix.QRDecomposition: Return the upper triangular factor
getRadius() - Method in class weka.core.neighboursearch.balltrees.BallNode: Returns the radius of the node's ball.
getRaiseExceptionOnCommandFailure() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get to raise an exception when a command fails completely (i.e.
getRandom() - Method in class weka.datagenerators.DataGenerator: Gets the random generator.
getRandomizeData() - Method in class weka.experiment.ExplicitTestsetResultProducer: Get if dataset is to be randomized.
getRandomizeData() - Method in class weka.experiment.RandomSplitResultProducer: Get if dataset is to be randomized
getRandomLiftGraph() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the randomLiftGraph property.
getRandomNumberGenerator(long) - Method in class weka.core.Instances: Returns a random number generator.
getRandomOrder() - Method in class weka.classifiers.bayes.net.search.global.K2: Get random order flag
getRandomOrder() - Method in class weka.classifiers.bayes.net.search.local.K2: Get random order flag
getRandomSeed() - Method in class weka.classifiers.functions.SMO: Get the value of randomSeed.
getRandomSeed() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns the seed value of random number generator.
getRandomSeed() - Method in class weka.filters.supervised.instance.Resample: Gets the random number seed.
getRandomSeed() - Method in class weka.filters.supervised.instance.SpreadSubsample: Gets the random number seed.
getRandomSeed() - Method in class weka.filters.unsupervised.attribute.AddNoise: Gets the random number seed.
getRandomSeed() - Method in class weka.filters.unsupervised.instance.Randomize: Get the random number generator seed value.
getRandomSeed() - Method in class weka.filters.unsupervised.instance.Resample: Gets the random number seed.
getRandomSeed() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Gets the random number seed.
getRandomSeed() - Method in class weka.gui.explorer.ClassifierPanel: Get the random seed
getRandomWidthFactor() - Method in class weka.classifiers.meta.MultiClassClassifier: Gets the multiplier when generating random codes.
getRange() - Method in class weka.core.InstanceComparator: Returns the attribute range to use in the comparison.
getRange(int) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets a single Range from the set of available Ranges.
getRanges() - Method in class weka.core.NormalizableDistance: Method to get the ranges.
getRanges() - Method in class weka.core.Range: Gets the string representing the selected range of values.
getRanges() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets the list of possible Ranges to choose from.
getRank() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the rank property.
getRankBasis() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the rankBasis property.
getRankingQuality() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the rankingQuality property.
getRankOrder() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the rankOrder property.
getRawOutput() - Method in class weka.experiment.CrossValidationResultProducer: Get if raw split evaluator output is to be saved
getRawOutput() - Method in class weka.experiment.ExplicitTestsetResultProducer: Get if raw split evaluator output is to be saved.
getRawOutput() - Method in class weka.experiment.RandomSplitResultProducer: Get if raw split evaluator output is to be saved
getRawResultOutput() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the raw output from the classifier
getRawResultOutput() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the raw output from the classifier
getRawResultOutput() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the raw output from the classifier
getRawResultOutput() - Method in interface weka.experiment.SplitEvaluator: Returns the raw output for the most recent call to getResult.
getReadable() - Method in class weka.core.Tag: Gets the string description of the Tag.
getReader(String, String) - Static method in class weka.gui.Loader: returns a Reader for the given filename and dir, can be NULL if it fails
getReader(String) - Method in class weka.gui.Loader: returns a Reader for the given filename, can be NULL if it fails
getReadIncrementally() - Method in class weka.gui.SetInstancesPanel: Gets whether instances are to be read incrementally or not.
getRealEigenvalues() - Method in class weka.core.matrix.EigenvalueDecomposition: Return the real parts of the eigenvalues
getREALEntries() - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Gets the value of the realEntries property.
getREALSparseArray() - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Gets the value of the realSparseArray property.
getReasonCode() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the reasonCode property.
getReasonCode() - Method in class weka.core.pmml.jaxbbindings.Characteristic: Gets the value of the reasonCode property.
getReasonCodeAlgorithm() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the reasonCodeAlgorithm property.
getRecall() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the recall.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Gets the value of the recordCount property.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.Node: Gets the value of the recordCount property.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the recordCount property.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Gets the value of the recordCount property.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the recordCount property.
getRecordCount() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the recordCount property.
getReducedErrorPruning() - Method in class weka.classifiers.rules.PART: Get the value of reducedErrorPruning.
getReducedErrorPruning() - Method in class weka.classifiers.trees.J48: Get the value of reducedErrorPruning.
getReduceNumberOfDistanceCalcsViaCanopies() - Method in class weka.clusterers.SimpleKMeans: Get whether to use canopies to reduce the number of distance computations required
getRefer() - Method in class weka.gui.treevisualizer.Node: Get the value of refer.
getReferencePoint() - Method in class weka.core.pmml.jaxbbindings.Parameter: Gets the value of the referencePoint property.
getRefreshFreq() - Method in class weka.gui.beans.StripChart: Get the refresh frequency
getRefreshFreq() - Method in class weka.knowledgeflow.steps.StripChart: Get the refresh frequency
getRefreshWidth() - Method in class weka.gui.beans.StripChart: Get how many pixels to shift the plot by every time a point is plotted
getRefreshWidth() - Method in class weka.knowledgeflow.steps.StripChart: Get how many pixels to shift the plot by every time a point is plotted
getRegex() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get whether this is a regular expression match or not
getRegex() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Get whether this is a regular expression match or not
getRegexMatch() - Method in class weka.filters.RenameRelation: Get the match string for regex modifications
getRegexMatch() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get the match string for regex modifications
getRegOptimizer() - Method in class weka.classifiers.functions.SMOreg: returns the learning algorithm
getRegressionModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the regressionModel property.
getRegressionTable() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the regressionTable property.
getRegressionTree() - Method in class weka.classifiers.trees.m5.Rule: Get the value of regressionTree.
getRegressionTree() - Method in class weka.classifiers.trees.m5.RuleNode: Get the value of regressionTree.
getRelation() - Method in class weka.core.TestInstances: returns the current name of the relation
getRelationalClassFormat() - Method in class weka.core.TestInstances: returns the current strcuture of the relational class attribute, can be null
getRelationalFormat(int) - Method in class weka.core.TestInstances: returns the format for the specified relational attribute, can be null
getRelationFind() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the currently set regular expression to use on the relation name.
getRelationForTableName() - Method in class weka.core.converters.DatabaseSaver: Gets whether or not the relation name is used as name of the table.
getRelationName() - Method in class weka.datagenerators.DataGenerator: Gets the relation name the dataset should have.
getRelationNameForFilename() - Method in class weka.gui.beans.Saver: Get whether the relation name is the primary part of the filename.
getRelationNameForFilename() - Method in class weka.knowledgeflow.steps.Saver: Get whether the relation name is the primary part of the filename.
getRelationReplace() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the currently set replacement string to use on the relation name.
getRemoteHosts() - Method in class weka.experiment.RemoteExperiment: Get the list of remote host names
getRemoveAllMissingCols() - Method in class weka.associations.Apriori: Returns whether columns containing all missing values are to be removed
getRemoveClassColumn() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Get whether the class column is to be removed.
getRemoveFilter() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Get the remove filter in use
getRemoveFilterClassnames() - Static method in class weka.gui.experiment.ExperimenterDefaults: whether the filter classnames in the dataset names are removed by default.
getRemoveFilterName() - Method in class weka.experiment.ResultMatrix: returns whether the filter classname is removed from the dataset name.
getRemoveOldClass() - Method in class weka.filters.supervised.attribute.AddClassification: Get whether the old class attribute is removed.
getRemoveUnused() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Gets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
getRenderingHint(RenderingHints.Key) - Method in class weka.gui.visualize.PostscriptGraphics
getRenderingHints() - Method in class weka.gui.visualize.PostscriptGraphics
getRepetitions() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the number of repetitions to use.
getReplace() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the regular expression to replace matching attribute names with.
getReplace() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Get the replace string
getReplaceAll() - Method in class weka.filters.RenameRelation: Get whether to replace all regular expression matches, or just the first.
getReplaceAll() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns whether all occurrences are replaced or just the first one.
getReplaceAll() - Method in class weka.knowledgeflow.steps.AlterRelationName: Get whether to replace all regular expression matches, or just the first.
getReplaceMissingValues() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Gets the current setting for using ReplaceMissingValues filter
getRepositoryPackageInfo(String) - Method in class weka.core.packageManagement.DefaultPackageManager: Get package information on the named package from the repository.
getRepositoryPackageInfo(String, Object) - Method in class weka.core.packageManagement.DefaultPackageManager: Get package information on the named package from the repository.
getRepositoryPackageInfo(String) - Method in class weka.core.packageManagement.PackageManager: Get package information on the named package from the repository.
getRepositoryPackageInfo(String, Object) - Method in class weka.core.packageManagement.PackageManager: Get package information on the named package from the repository.
getRepositoryPackageInfo(String) - Static method in class weka.core.WekaPackageManager: Get meta data for the latest version of a package from the repository
getRepositoryPackageInfo(String, String) - Static method in class weka.core.WekaPackageManager: Get meta data for a specific version of a package from the repository
getRepositoryPackageMetaDataOnlyAsZip(PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Gets an array of bytes containing a zip of all the repository meta data and supporting files.
getRepositoryPackageMetaDataOnlyAsZip(PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Gets an array of bytes containing a zip of all the repository meta data and supporting files.
getRepositoryPackageMetaDataOnlyAsZipLegacy(PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Gets an array of bytes containing a zip of all the repository meta data and supporting files using the legacy approach.
getRepositoryPackageVersions(String) - Method in class weka.core.packageManagement.DefaultPackageManager: Get a list of available versions of the named package.
getRepositoryPackageVersions(String) - Method in class weka.core.packageManagement.PackageManager: Get a list of available versions of the named package.
getRepositoryPackageVersions(String) - Static method in class weka.core.WekaPackageManager: Get the versions of the supplied package available on the server
getRepresentCopiesUsingWeights() - Method in class weka.classifiers.meta.Bagging: Get whether copies of instances are represented using weights rather than explicitly.
getRescaleConstant() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the rescaleConstant property.
getRescaleFactor() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the rescaleFactor property.
getReset() - Method in class weka.classifiers.functions.MultilayerPerceptron
getReset() - Method in class weka.gui.beans.ChartEvent: get the value of the reset flag
getResetIncrementalClassifier() - Method in class weka.gui.beans.Classifier: Get whether to reset (by calling buildClassifier()) an incremental classifier, and thus discarding any previously learned model, before processing the first instance in the incoming stream.
getResetIncrementalClassifier() - Method in class weka.knowledgeflow.steps.Classifier: Get whether to reset an incremental classifier at the start of an incoming instance stream
getResetValue() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the resetValue property.
getResolvedName() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the name of the attribute after substituting any environment variables
getResolvedType() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the type of the attribute after substituting any environment variables
getResolvedValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the value of the attribute after substituting any environment variables
getResource(String) - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Find a named resource.
getResources(String) - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Find an enumeration of resources matching the supplied name.
getResourcesWithGroupID(String) - Static method in class weka.core.PluginManager: Get a map of resources (description,path) registered under a given resource group ID.
getResourcesWithGroupID(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Get a map of resources (description,path) registered under a given resource group ID.
getResult() - Method in class weka.core.json.Parser: Returns the JSON data structure.
getResult(double[]) - Method in class weka.core.pmml.BuiltInArithmetic: Get the result of applying this function.
getResult(double[]) - Method in class weka.core.pmml.BuiltInMath: Get the result of applying this function.
getResult(double[]) - Method in class weka.core.pmml.BuiltInString: Get the result of applying this function.
getResult(double[]) - Method in class weka.core.pmml.Constant: Get the result of evaluating the expression.
getResult(double[]) - Method in class weka.core.pmml.DefineFunction: Get the result of applying this function.
getResult(double[]) - Method in class weka.core.pmml.Discretize: Get the result of evaluating the expression.
getResult(double[]) - Method in class weka.core.pmml.Expression: Get the result of evaluating the expression.
getResult(double[]) - Method in class weka.core.pmml.FieldRef
getResult(double[]) - Method in class weka.core.pmml.Function: Get the result of applying this function.
getResult(double[]) - Method in class weka.core.pmml.NormContinuous: Get the result of evaluating the expression.
getResult(double[]) - Method in class weka.core.pmml.NormDiscrete: Get the result of evaluating the expression.
getResult(Instances, Instances) - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in class weka.experiment.RegressionSplitEvaluator: Gets the results for the supplied train and test datasets.
getResult(Instances, Instances) - Method in interface weka.experiment.SplitEvaluator: Gets the results for the supplied train and test datasets.
getResult() - Method in class weka.gui.experiment.OutputFormatDialog: the result from the last display of the dialog, the same is returned from showDialog.
getResult() - Method in class weka.knowledgeflow.ExecutionResult: Get the result generated by the StepTask
getResultCategorical(double[]) - Method in class weka.core.pmml.Constant: Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
getResultCategorical(double[]) - Method in class weka.core.pmml.Discretize: Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
getResultCategorical(double[]) - Method in class weka.core.pmml.Expression: Gets the result of evaluating the expression when the optype is categorical or ordinal as the actual String value.
getResultCategorical(double[]) - Method in class weka.core.pmml.FieldRef
getResultCategorical(double[]) - Method in class weka.core.pmml.NormContinuous: Always throws an Exception since the result of NormContinuous must be continuous.
getResultCategorical(double[]) - Method in class weka.core.pmml.NormDiscrete: Always throws an Exception since the result of NormDiscrete must be continuous.
getResultContinuous(double[]) - Method in class weka.core.pmml.Expression: Get the result of evaluating the expression for continuous optype.
getResultData() - Method in class weka.knowledgeflow.JobEnvironment: Get a map of all the result data objects
getResultDataOfType(String) - Method in class weka.knowledgeflow.JobEnvironment: Get a list of any result data objects of the supplied connection type
getResultField() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the resultField property.
getResultField() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the resultField property.
getResultFromTable(String, ResultProducer, Object[]) - Method in class weka.experiment.DatabaseUtils: Executes a database query to extract a result for the supplied key from the database.
getResultHistory() - Method in class weka.gui.explorer.ClassifierPanel: Get the result history panel
getResultInverse(double[]) - Method in class weka.core.pmml.NormContinuous: Compute the inverse of the normalization (i.e.
getResultListener() - Method in class weka.experiment.Experiment: Gets the result listener where results will be sent.
getResultMatrix() - Method in class weka.experiment.PairedTTester: Gets the instance that produces the output.
getResultMatrix() - Method in interface weka.experiment.Tester: Gets the instance that produces the output.
getResultMatrix() - Method in class weka.gui.experiment.OutputFormatDialog: Gets the currently selected output format result matrix.
getResultNames() - Method in class weka.experiment.AveragingResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class weka.experiment.CrossValidationResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.DatabaseResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.LearningRateResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.RandomSplitResultProducer: Gets the names of each of the columns produced for a single run.
getResultNames() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in interface weka.experiment.ResultProducer: Gets the names of each of the result columns produced for a single run.
getResultNames() - Method in interface weka.experiment.SplitEvaluator: Gets the names of each of the result columns produced for a single run.
getResultProducer() - Method in class weka.experiment.AveragingResultProducer: Get the ResultProducer.
getResultProducer() - Method in class weka.experiment.DatabaseResultProducer: Get the ResultProducer.
getResultProducer() - Method in class weka.experiment.Experiment: Get the result producer used for the current experiment.
getResultProducer() - Method in class weka.experiment.LearningRateResultProducer: Get the ResultProducer.
getResults() - Method in class weka.knowledgeflow.steps.TextViewer: Get the textual results stored in this step
getResultSet() - Method in class weka.experiment.DatabaseUtils: Gets the results generated by a previous query.
getResultSet() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the resultset that was produced, can be null in case the query failed
getResultSet() - Method in class weka.gui.sql.ResultSetHelper: the underlying resultset.
getResultsetKeyColumns() - Method in class weka.experiment.PairedTTester: Get the value of ResultsetKeyColumns.
getResultsetKeyColumns() - Method in interface weka.experiment.Tester: Get the value of ResultsetKeyColumns.
getResultsetName(int) - Method in class weka.experiment.PairedTTester: Gets a string descriptive of the specified resultset.
getResultsetName(int) - Method in interface weka.experiment.Tester: Gets a string descriptive of the specified resultset.
getResultsTableName(ResultProducer) - Method in class weka.experiment.DatabaseUtils: Gets the name of the experiment table that stores results from a particular ResultProducer.
getResultTypes() - Method in class weka.experiment.AveragingResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.ClassifierSplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class weka.experiment.CrossValidationResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.DatabaseResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.LearningRateResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.RandomSplitResultProducer: Gets the data types of each of the columns produced for a single run.
getResultTypes() - Method in class weka.experiment.RegressionSplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in interface weka.experiment.ResultProducer: Gets the data types of each of the result columns produced for a single run.
getResultTypes() - Method in interface weka.experiment.SplitEvaluator: Gets the data types of each of the result columns produced for a single run.
getResume() - Method in class weka.classifiers.functions.MultilayerPerceptron: Returns true if the model is to be finalized (or has been finalized) after training.
getResume() - Method in interface weka.classifiers.IterativeClassifier: Returns true if the classifier will be able to be trained further (with more iterations) at a later date.
getResume() - Method in class weka.classifiers.meta.AdaBoostM1: Returns true if the model is to be finalized (or has been finalized) after training.
getResume() - Method in class weka.classifiers.meta.AdditiveRegression: Returns true if the model is to be finalized (or has been finalized) after training.
getResume() - Method in class weka.classifiers.meta.FilteredClassifier: Returns true if the model is to be finalized (or has been finalized) after training.
getResume() - Method in class weka.classifiers.meta.LogitBoost: Returns true if the model is to be finalized (or has been finalized) after training.
getRetainStringVals() - Method in class weka.core.converters.ArffLoader: Get whether to retain the values of string attributes in memory (in the header) when reading incrementally.
getRetainStringValues() - Method in class weka.core.converters.ArffLoader.ArffReader: Get whether to retain the values of string attributes in memory (in the header) when reading incrementally.
getReturnValue() - Method in class weka.gui.DatabaseConnectionDialog: Returns which of OK or cancel was clicked from dialog
getReturnValue() - Method in class weka.gui.sql.SqlViewerDialog: returns whether the user clicked OK (JOptionPane.OK_OPTION) or whether he cancelled the dialog (JOptionPane.CANCEL_OPTION).
getRevision() - Method in class weka.associations.AbstractAssociator: Returns the revision string.
getRevision() - Method in class weka.associations.Apriori: Returns the revision string.
getRevision() - Method in class weka.associations.AprioriItemSet: Returns the revision string.
getRevision() - Method in class weka.associations.AssociatorEvaluation: Returns the revision string.
getRevision() - Method in class weka.associations.CheckAssociator: Returns the revision string.
getRevision() - Method in class weka.associations.FilteredAssociator: Returns the revision string.
getRevision() - Method in class weka.associations.FPGrowth: Returns the revision string.
getRevision() - Method in class weka.associations.ItemSet: Returns the revision string.
getRevision() - Method in class weka.associations.LabeledItemSet: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.ASEvaluation: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.ASSearch: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.AttributeSelection: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.BestFirst: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.BestFirst.Link2: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.BestFirst.LinkedList2: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.CheckAttributeSelection: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.CorrelationAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.GainRatioAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.GreedyStepwise: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.OneRAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.PrincipalComponents: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.Ranker: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Returns the revision string.
getRevision() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the revision string.
getRevision() - Method in class weka.classifiers.AbstractClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.BayesNet: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.ADNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.BIFReader: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.EditableBayesNet: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.ParentSet: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.K2: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.global.TAN: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.K2: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.local.TAN: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: Returns the revision string.
getRevision() - Method in class weka.classifiers.bayes.net.VaryNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.BVDecompose: Returns the revision string.
getRevision() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns the revision string.
getRevision() - Method in class weka.classifiers.CheckClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.CheckSource: Returns the revision string.
getRevision() - Method in class weka.classifiers.CostMatrix: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.CostCurve: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.Evaluation: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.EvaluationUtils: Returns the revision string.
getRevision() - Method in class weka.classifiers.Evaluation
getRevision() - Method in class weka.classifiers.evaluation.MarginCurve: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.NominalPrediction: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.NumericPrediction: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.RegressionAnalysis: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.ThresholdCurve: Returns the revision string.
getRevision() - Method in class weka.classifiers.evaluation.TwoClassStats: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.LinearRegression: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.Logistic: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.MultilayerPerceptron: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.neural.LinearUnit: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.neural.NeuralNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.neural.SigmoidUnit: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SGD: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SGDText: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SMO.BinarySMO: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SMO: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.SMOreg: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.Puk: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.RBFKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.SMOset: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the revision string.
getRevision() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.IBk: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.KStar: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.kstar.KStarWrapper: Returns the revision string.
getRevision() - Method in class weka.classifiers.lazy.LWL: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.AdaBoostM1: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.AdditiveRegression: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.Bagging: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.CVParameterSelection: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.LogitBoost: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.MultiClassClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.MultiScheme: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.RandomCommittee: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.RandomSubSpace: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.Stacking: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.Vote: Returns the revision string.
getRevision() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.misc.SerializedClassifier: Returns the revision string.
getRevision() - Method in class weka.classifiers.pmml.consumer.GeneralRegression
getRevision() - Method in class weka.classifiers.pmml.consumer.NeuralNetwork
getRevision() - Method in class weka.classifiers.pmml.consumer.Regression
getRevision() - Method in class weka.classifiers.pmml.consumer.RuleSetModel: Get the revision string for this class
getRevision() - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel
getRevision() - Method in class weka.classifiers.pmml.consumer.TreeModel
getRevision() - Method in class weka.classifiers.rules.DecisionTable: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.DecisionTableHashKey: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.JRip.Antd: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.JRip: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.JRip.NominalAntd: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.JRip.NumericAntd: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.JRip.RipperRule: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.M5Rules: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.OneR: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.part.C45PruneableDecList: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.part.ClassifierDecList: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.PART: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.part.MakeDecList: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.part.PruneableDecList: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.RuleStats: Returns the revision string.
getRevision() - Method in class weka.classifiers.rules.ZeroR: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.DecisionStump: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.C45ModelSelection: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.C45Split: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.Distribution: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.EntropySplitCrit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.J48: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.NoSplit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.j48.Stats: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.LMT: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.lmt.ResidualSplit: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.Impurity: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.Rule: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.RuleNode: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.Values: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.M5P: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.RandomForest: Returns the revision string.
getRevision() - Method in class weka.classifiers.trees.REPTree: Returns the revision string.
getRevision() - Method in class weka.classifiers.xml.XMLClassifier: Returns the revision string.
getRevision() - Method in class weka.clusterers.AbstractClusterer: Returns the revision string.
getRevision() - Method in class weka.clusterers.CheckClusterer: Returns the revision string.
getRevision() - Method in class weka.clusterers.ClusterEvaluation: Returns the revision string.
getRevision() - Method in class weka.clusterers.Cobweb.CNode: Returns the revision string.
getRevision() - Method in class weka.clusterers.Cobweb: Returns the revision string.
getRevision() - Method in class weka.clusterers.EM: Returns the revision string.
getRevision() - Method in class weka.clusterers.FarthestFirst: Returns the revision string.
getRevision() - Method in class weka.clusterers.FilteredClusterer: Returns the revision string.
getRevision() - Method in class weka.clusterers.HierarchicalClusterer: Returns the revision string.
getRevision() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the revision string.
getRevision() - Method in class weka.clusterers.SimpleKMeans: Returns the revision string.
getRevision() - Method in class weka.core.AbstractInstance: Returns the revision string.
getRevision() - Method in class weka.core.AlgVector: Returns the revision string.
getRevision() - Method in class weka.core.AllJavadoc: Returns the revision string.
getRevision() - Method in class weka.core.Attribute: Returns the revision string.
getRevision() - Method in class weka.core.AttributeLocator: Returns the revision string.
getRevision() - Method in class weka.core.AttributeMetaInfo: Returns the revision string.
getRevision() - Method in class weka.core.AttributeStats: Returns the revision string.
getRevision() - Method in class weka.core.BinarySparseInstance: Returns the revision string.
getRevision() - Method in class weka.core.Capabilities: Returns the revision string.
getRevision() - Method in class weka.core.ChebyshevDistance: Returns the revision string.
getRevision() - Method in class weka.core.CheckGOE: Returns the revision string.
getRevision() - Method in class weka.core.CheckOptionHandler: Returns the revision string.
getRevision() - Method in class weka.core.CheckScheme.PostProcessor: Returns the revision string.
getRevision() - Method in class weka.core.ClassCache: Returns the revision string.
getRevision() - Method in class weka.core.ClassDiscovery: Returns the revision string.
getRevision() - Method in class weka.core.ClassDiscovery.StringCompare: Returns the revision string.
getRevision() - Method in class weka.core.ClassloaderUtil: Returns the revision string.
getRevision() - Method in class weka.core.ContingencyTables: Returns the revision string.
getRevision() - Method in class weka.core.converters.ArffLoader.ArffReader: Returns the revision string.
getRevision() - Method in class weka.core.converters.ArffLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.ArffSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.C45Loader: Returns the revision string.
getRevision() - Method in class weka.core.converters.C45Saver: Returns the revision string.
getRevision() - Method in class weka.core.converters.ConverterUtils.DataSink: Returns the revision string.
getRevision() - Method in class weka.core.converters.ConverterUtils.DataSource: Returns the revision string.
getRevision() - Method in class weka.core.converters.ConverterUtils: Returns the revision string.
getRevision() - Method in class weka.core.converters.CSVLoader
getRevision() - Method in class weka.core.converters.CSVSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.DatabaseConnection: Returns the revision string.
getRevision() - Method in class weka.core.converters.DatabaseLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.DatabaseSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.DictionarySaver
getRevision() - Method in class weka.core.converters.JSONLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.JSONSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.LibSVMLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.LibSVMSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.MatlabLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.MatlabSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.SerializedInstancesLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.SerializedInstancesSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.StreamTokenizerUtils
getRevision() - Method in class weka.core.converters.SVMLightLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.SVMLightSaver: Returns the revision string.
getRevision() - Method in class weka.core.converters.TextDirectoryLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.XRFFLoader: Returns the revision string.
getRevision() - Method in class weka.core.converters.XRFFSaver: Returns the revision string.
getRevision() - Method in class weka.core.Debug.Clock: Returns the revision string.
getRevision() - Method in class weka.core.Debug.DBO: Returns the revision string.
getRevision() - Method in class weka.core.Debug: Returns the revision string.
getRevision() - Method in class weka.core.Debug.Log: Returns the revision string.
getRevision() - Method in class weka.core.Debug.Random: Returns the revision string.
getRevision() - Method in class weka.core.Debug.SimpleLog: Returns the revision string.
getRevision() - Method in class weka.core.Debug.Timestamp: Returns the revision string.
getRevision() - Method in class weka.core.DenseInstance: Returns the revision string.
getRevision() - Method in class weka.core.Environment: Returns the revision string.
getRevision() - Method in class weka.core.EuclideanDistance: Returns the revision string.
getRevision() - Method in class weka.core.FastVector: Deprecated.

Returns the revision string.
getRevision() - Method in class weka.core.FindWithCapabilities: Returns the revision string.
getRevision() - Method in class weka.core.GlobalInfoJavadoc: Returns the revision string.
getRevision() - Method in class weka.core.InstanceComparator: Returns the revision string.
getRevision() - Method in class weka.core.Instances: Returns the revision string.
getRevision() - Method in class weka.core.ListOptions: Returns the revision string.
getRevision() - Method in class weka.core.logging.ConsoleLogger: Returns the revision string.
getRevision() - Method in class weka.core.logging.FileLogger: Returns the revision string.
getRevision() - Method in class weka.core.logging.OutputLogger: Returns the revision string.
getRevision() - Method in class weka.core.ManhattanDistance: Returns the revision string.
getRevision() - Method in class weka.core.matrix.CholeskyDecomposition: Returns the revision string.
getRevision() - Method in class weka.core.matrix.DoubleVector: Returns the revision string.
getRevision() - Method in class weka.core.matrix.EigenvalueDecomposition: Returns the revision string.
getRevision() - Method in class weka.core.matrix.ExponentialFormat: Returns the revision string.
getRevision() - Method in class weka.core.matrix.FlexibleDecimalFormat: Returns the revision string.
getRevision() - Method in class weka.core.matrix.FloatingPointFormat: Returns the revision string.
getRevision() - Method in class weka.core.Matrix: Deprecated.

Returns the revision string.
getRevision() - Method in class weka.core.matrix.IntVector: Returns the revision string.
getRevision() - Method in class weka.core.matrix.LinearRegression: Returns the revision string.
getRevision() - Method in class weka.core.matrix.LUDecomposition: Returns the revision string.
getRevision() - Method in class weka.core.matrix.Maths: Returns the revision string.
getRevision() - Method in class weka.core.matrix.Matrix: Returns the revision string.
getRevision() - Method in class weka.core.matrix.QRDecomposition: Returns the revision string.
getRevision() - Method in class weka.core.matrix.SingularValueDecomposition: Returns the revision string.
getRevision() - Method in class weka.core.Memory: Returns the revision string.
getRevision() - Method in class weka.core.MinkowskiDistance: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.BallTree: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.BallNode: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.CoverTree: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.covertrees.Stack: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the revision string
getRevision() - Method in class weka.core.neighboursearch.KDTree: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.LinearNNSearch: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the revision string.
getRevision() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the revision string.
getRevision() - Method in class weka.core.Option: Returns the revision string.
getRevision() - Method in class weka.core.OptionHandlerJavadoc: Returns the revision string.
getRevision() - Method in class weka.core.PropertyPath: Returns the revision string.
getRevision() - Method in class weka.core.PropertyPath.Path: Returns the revision string.
getRevision() - Method in class weka.core.PropertyPath.PathElement: Returns the revision string.
getRevision() - Method in class weka.core.ProtectedProperties: Returns the revision string.
getRevision() - Method in class weka.core.Queue: Returns the revision string.
getRevision() - Method in class weka.core.RandomVariates: Returns the revision string.
getRevision() - Method in class weka.core.Range: Returns the revision string.
getRevision() - Method in class weka.core.RelationalLocator: Returns the revision string.
getRevision() - Method in interface weka.core.RevisionHandler: Returns the revision string.
getRevision() - Method in class weka.core.scripting.Groovy: Returns the revision string.
getRevision() - Method in class weka.core.scripting.Jython: Returns the revision string.
getRevision() - Method in class weka.core.SelectedTag: Returns the revision string.
getRevision() - Method in class weka.core.SerializationHelper: Returns the revision string.
getRevision() - Method in class weka.core.SerializedObject: Returns the revision string.
getRevision() - Method in class weka.core.SingleIndex: Returns the revision string.
getRevision() - Method in class weka.core.SparseInstance: Returns the revision string.
getRevision() - Method in class weka.core.SpecialFunctions: Returns the revision string.
getRevision() - Method in class weka.core.Statistics: Returns the revision string.
getRevision() - Method in class weka.core.stemmers.IteratedLovinsStemmer: Returns the revision string.
getRevision() - Method in class weka.core.stemmers.LovinsStemmer: Returns the revision string.
getRevision() - Method in class weka.core.stemmers.NullStemmer: Returns the revision string.
getRevision() - Method in class weka.core.stemmers.SnowballStemmer: Returns the revision string.
getRevision() - Method in class weka.core.stemmers.Stemming: Returns the revision string.
getRevision() - Method in class weka.core.Stopwords: Returns the revision string.
getRevision() - Method in class weka.core.StringLocator: Returns the revision string.
getRevision() - Method in class weka.core.SystemInfo: Returns the revision string.
getRevision() - Method in class weka.core.Tag: Returns the revision string.
getRevision() - Method in class weka.core.TechnicalInformation: Returns the revision string.
getRevision() - Method in class weka.core.TechnicalInformationHandlerJavadoc: Returns the revision string.
getRevision() - Method in class weka.core.Tee: Returns the revision string.
getRevision() - Method in class weka.core.TestInstances: Returns the revision string.
getRevision() - Method in class weka.core.tokenizers.AlphabeticTokenizer: Returns the revision string.
getRevision() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns the revision string.
getRevision() - Method in class weka.core.tokenizers.NGramTokenizer: Returns the revision string.
getRevision() - Method in class weka.core.tokenizers.WordTokenizer: Returns the revision string.
getRevision() - Method in class weka.core.Trie: Returns the revision string.
getRevision() - Method in class weka.core.Trie.TrieIterator: Returns the revision string.
getRevision() - Method in class weka.core.Trie.TrieNode: Returns the revision string.
getRevision() - Method in class weka.core.Utils: Returns the revision string.
getRevision() - Method in class weka.core.Version: Returns the revision string.
getRevision() - Method in class weka.core.WekaEnumeration: Returns the revision string.
getRevision() - Method in class weka.core.xml.KOML: Returns the revision string.
getRevision() - Method in class weka.core.xml.MethodHandler: Returns the revision string.
getRevision() - Method in class weka.core.xml.PropertyHandler: Returns the revision string.
getRevision() - Method in class weka.core.xml.SerialUIDChanger: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLBasicSerialization: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLDocument: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLInstances: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLOptions: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLSerialization: Returns the revision string.
getRevision() - Method in class weka.core.xml.XMLSerializationMethodHandler: Returns the revision string.
getRevision() - Method in class weka.core.xml.XStream: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.LED24: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns the revision string.
getRevision() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the revision string.
getRevision() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the revision string.
getRevision() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the revision string.
getRevision() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the revision string.
getRevision() - Method in class weka.datagenerators.Test: Returns the revision string.
getRevision() - Method in class weka.estimators.CheckEstimator.AttrTypes: Returns the revision string.
getRevision() - Method in class weka.estimators.CheckEstimator.EstTypes: Returns the revision string.
getRevision() - Method in class weka.estimators.CheckEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.CheckEstimator.PostProcessor: Returns the revision string.
getRevision() - Method in class weka.estimators.DDConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.DiscreteEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.DKConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.DNConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.Estimator: Returns the revision string.
getRevision() - Method in class weka.estimators.EstimatorUtils: Returns the revision string.
getRevision() - Method in class weka.estimators.KDConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.KernelEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.KKConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.MahalanobisEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.NDConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.NNConditionalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.NormalEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.PoissonEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.UnivariateKernelEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the revision string.
getRevision() - Method in class weka.estimators.UnivariateNormalEstimator: Returns the revision string.
getRevision() - Method in class weka.experiment.AveragingResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the revision string.
getRevision() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns the revision string.
getRevision() - Method in class weka.experiment.CrossValidationResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.CrossValidationSplitResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.CSVResultListener: Returns the revision string.
getRevision() - Method in class weka.experiment.DatabaseResultListener: Returns the revision string.
getRevision() - Method in class weka.experiment.DatabaseResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.DatabaseUtils: Returns the revision string.
getRevision() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the revision string.
getRevision() - Method in class weka.experiment.Experiment: Returns the revision string.
getRevision() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.InstanceQuery: Returns the revision string.
getRevision() - Method in class weka.experiment.InstancesResultListener: Returns the revision string.
getRevision() - Method in class weka.experiment.LearningRateResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.OutputZipper: Returns the revision string.
getRevision() - Method in class weka.experiment.PairedCorrectedTTester: Returns the revision string.
getRevision() - Method in class weka.experiment.PairedStats: Returns the revision string.
getRevision() - Method in class weka.experiment.PairedStatsCorrected: Returns the revision string.
getRevision() - Method in class weka.experiment.PairedTTester: Returns the revision string.
getRevision() - Method in class weka.experiment.PropertyNode: Returns the revision string.
getRevision() - Method in class weka.experiment.RandomSplitResultProducer: Returns the revision string.
getRevision() - Method in class weka.experiment.RegressionSplitEvaluator: Returns the revision string.
getRevision() - Method in class weka.experiment.RemoteEngine: Returns the revision string.
getRevision() - Method in class weka.experiment.RemoteExperiment: Returns the revision string.
getRevision() - Method in class weka.experiment.RemoteExperimentSubTask: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixCSV: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixGnuPlot: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixHTML: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixLatex: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixPlainText: Returns the revision string.
getRevision() - Method in class weka.experiment.ResultMatrixSignificance: Returns the revision string.
getRevision() - Method in class weka.experiment.Stats: Returns the revision string.
getRevision() - Method in class weka.experiment.TaskStatusInfo: Returns the revision string.
getRevision() - Method in class weka.experiment.xml.XMLExperiment: Returns the revision string.
getRevision() - Method in class weka.filters.AllFilter: Returns the revision string.
getRevision() - Method in class weka.filters.CheckSource: Returns the revision string.
getRevision() - Method in class weka.filters.Filter: Returns the revision string.
getRevision() - Method in class weka.filters.MultiFilter: Returns the revision string.
getRevision() - Method in class weka.filters.RenameRelation: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.Discretize: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.attribute.PartitionMembership
getRevision() - Method in class weka.filters.supervised.instance.ClassBalancer: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.instance.Resample: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the revision string.
getRevision() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Add: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Center: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Obfuscate: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Standardize: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.SwapValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.attribute.Transpose: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.Randomize: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.Resample: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse: Returns the revision string.
getRevision() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns the revision string.
getRevision() - Method in class weka.gui.beans.FlowRunner
getRevision() - Method in class weka.gui.sql.DbUtils: Returns the revision string.
getRHSOperand() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Get the rhs operand
getRidge() - Method in class weka.classifiers.functions.LinearRegression: Get the value of Ridge.
getRidge() - Method in class weka.classifiers.functions.Logistic: Gets the ridge in the log-likelihood.
getRidge() - Method in class weka.estimators.MultivariateGaussianEstimator: Get the value of Ridge.
getRightMargin() - Method in class weka.core.pmml.jaxbbindings.Interval: Gets the value of the rightMargin property.
getRMSE() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the rmse property.
getROC() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the roc property.
getROCArea(Instances) - Static method in class weka.classifiers.evaluation.ThresholdCurve: Calculates the area under the ROC curve as the Wilcoxon-Mann-Whitney statistic.
getROCGraph() - Method in class weka.core.pmml.jaxbbindings.ROC: Gets the value of the rocGraph property.
getROCString() - Method in class weka.gui.visualize.ThresholdVisualizePanel: This extracts the ROC area string
getRoot() - Method in class weka.core.expressionlanguage.parser.Parser: Returns the root node of the program
getRoot() - Method in class weka.core.Trie: returns the root node of the trie
getRoot() - Method in class weka.gui.treevisualizer.Node: Get the value of root.
getRootMeanSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the rootMeanSquaredError property.
getRootNode() - Method in class weka.core.xml.XMLDocument: returns the current root node.
getRow(int) - Method in class weka.core.Matrix: Deprecated.

Gets a row of the matrix and returns it as double array.
getRow() - Method in class weka.core.pmml.jaxbbindings.InlineTable: Gets the value of the row property.
getRow() - Method in class weka.core.pmml.jaxbbindings.MatCell: Gets the value of the row property.
getRow() - Static method in class weka.gui.experiment.ExperimenterDefaults: the comma-separated list of attribute names that identify a row.
getRowCount() - Method in class weka.experiment.ResultMatrix: returns the number of rows.
getRowCount() - Method in class weka.gui.arffviewer.ArffTableModel: returns the number of rows in the model
getRowCount() - Method in class weka.gui.InteractiveTableModel
getRowCount() - Method in class weka.gui.SortedTableModel: Returns the number of rows in the model.
getRowCount() - Method in class weka.gui.sql.ResultSetHelper: returns the number of rows in the resultset.
getRowCount() - Method in class weka.gui.sql.ResultSetTableModel: returns the number of rows in the model.
getRowDimension() - Method in class weka.core.matrix.Matrix: Get row dimension.
getRowHidden(int) - Method in class weka.experiment.ResultMatrix: returns the hidden status of the row, if the index is valid, otherwise false.
getRowName(int) - Method in class weka.experiment.ResultMatrix: returns the name of the row, if the index is valid, otherwise null.
getRowNameWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the row names.
getRowOrder() - Method in class weka.experiment.ResultMatrix: returns the current order of the rows, null means the default order.
getRowPackedCopy() - Method in class weka.core.matrix.Matrix: Make a one-dimensional row packed copy of the internal array.
getRsource() - Method in class weka.gui.treevisualizer.Edge: Get the value of rsource.
getRSquared() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the rSquared property.
getRtarget() - Method in class weka.gui.treevisualizer.Edge: Get the value of rtarget.
getRule() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the rule property.
getRule() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the rule property.
getRuleFeature() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the ruleFeature property.
getRuleMetricNames() - Method in class weka.associations.Apriori: Gets a list of the names of the metrics output for each rule.
getRuleMetricNames() - Method in interface weka.associations.AssociationRulesProducer: Gets a list of the names of the metrics output for each rule.
getRuleMetricNames() - Method in class weka.associations.FilteredAssociator: Gets a list of the names of the metrics output for each rule.
getRuleMetricNames() - Method in class weka.associations.FPGrowth: Gets a list of the names of the metrics output for each rule.
getRules() - Method in class weka.associations.AssociationRules: Get the rules.
getRules() - Method in class weka.associations.FilteredAssociationRules: Get the rules.
getRules() - Method in class weka.gui.beans.BatchAssociationRulesEvent: Get the encapsulated association rules.
getRuleSelectionMethod() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the ruleSelectionMethod property.
getRuleset() - Method in class weka.classifiers.rules.JRip: Get the ruleset generated by Ripper
getRuleset() - Method in class weka.classifiers.rules.RuleStats: Get the ruleset of the stats
getRuleSetModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the ruleSetModel property.
getRulesetSize() - Method in class weka.classifiers.rules.RuleStats: Get the size of the ruleset in the stats
getRulesMustContain() - Method in class weka.associations.FPGrowth: Get the comma separated list of items that rules must contain in order to be output.
getRuleStats(int) - Method in class weka.classifiers.rules.JRip: Get the statistics of the ruleset in the given position
getRunColumn() - Method in class weka.experiment.PairedTTester: Get the value of RunColumn.
getRunColumn() - Method in interface weka.experiment.Tester: Get the value of RunColumn.
getRunLower() - Method in class weka.experiment.Experiment: Get the lower run number for the experiment.
getRunNumber() - Method in class weka.gui.beans.BatchClassifierEvent: Get the run number.
getRunNumber() - Method in class weka.gui.beans.TestSetEvent: Get the run number that this training set belongs to.
getRunNumber() - Method in class weka.gui.beans.TrainingSetEvent: Get the run number that this training set belongs to.
getRuns() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Returns the number of runs
getRuns() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getRuns() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getRuns() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
getRuns() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getRuns() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
getRunUpper() - Method in class weka.experiment.Experiment: Get the upper run number for the experiment.
getS() - Method in class weka.core.matrix.SingularValueDecomposition: Return the diagonal matrix of singular values
getSample() - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE: Gets the value of the sample property.
getSampleSize() - Method in class weka.attributeSelection.ReliefFAttributeEval: Get the number of instances used for estimating attributes
getSampleSize() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Gets the subsample size.
getSampleSizePercent() - Method in class weka.filters.supervised.instance.Resample: Gets the subsample size as a percentage of the original set.
getSampleSizePercent() - Method in class weka.filters.unsupervised.instance.Resample: Gets the subsample size as a percentage of the original set.
getSaveBinaryDictionary() - Method in class weka.core.converters.DictionarySaver: Get whether to save the dictionary as a binary serialized dictionary, rather than a plain text one
getSaveDialogTitle() - Method in class weka.gui.visualize.PrintableComponent: returns the title for the save dialog.
getSaveDialogTitle() - Method in interface weka.gui.visualize.PrintableHandler: returns the title for the save dialog
getSaveDialogTitle() - Method in class weka.gui.visualize.PrintablePanel: returns the title for the save dialog
getSaveDictionaryInBinaryForm() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set whether to save the dictionary in binary serialized form rather than as plain text
getSaveForVisualization() - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Returns whether the instances are saved for visualization for only evaluation of the prediction is to happen.
getSaveInstanceData() - Method in class weka.classifiers.trees.J48: Check whether instance data is to be saved.
getSaveInstanceData() - Method in class weka.clusterers.Cobweb: Get the value of saveInstances.
getSaveInstances() - Method in class weka.classifiers.trees.M5P: Get whether instance data is being save.
getSaver() - Method in class weka.gui.ConverterFileChooser: returns the saver that was chosen by the user, can be null in case the user aborted the dialog or the open dialog was shown.
getSaver() - Method in class weka.knowledgeflow.steps.Saver: Get the saver instance that is wrapped by this step.
getSaverForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the saver to use for this kind of extension, returns null if none can be found.
getSaverForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the saver to use for this kind of file, returns null if none can be found.
getSaverForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the saver to use for this kind of file, returns null if none can be found.
getSaversForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the savers to use for this kind of extension.
getSaversForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the savers to use for this kind of file.
getSaversForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the savers to use for this kind of file.
getSaverTemplate() - Method in class weka.gui.beans.Saver: Get the saver
getScale() - Method in class weka.filters.unsupervised.attribute.Normalize: Get the scaling factor.
getScaleWidthToFit() - Method in class weka.gui.DocumentPrinting: Returns whether the width is to be scaled.
getScalingEnabled() - Method in class weka.gui.visualize.JComponentWriter: whether scaling is enabled or ignored
getScore() - Method in class weka.core.pmml.jaxbbindings.Node: Gets the value of the score property.
getScore() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the score property.
getScorecard() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the scorecard property.
getScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.RuleSet: Gets the value of the scoreDistribution property.
getScoreDistribution() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the scoreDistribution property.
getScoreType() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: get quality measure to be used in searching for networks.
getScript() - Method in class weka.gui.scripting.event.ScriptExecutionEvent: Returns the script that triggered the event.
getScrollableTracksViewportHeight() - Method in class weka.gui.ETable: Changes the behavior of a table in a JScrollPane to be more like the behavior of JList, which expands to fill the available space.
getSearch() - Method in class weka.attributeSelection.CheckAttributeSelection: Get the current search method
getSearch() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Gets the search method used
getSearch() - Method in class weka.classifiers.rules.DecisionTable: Gets the current search method
getSearch() - Method in class weka.filters.supervised.attribute.AttributeSelection: Get the name of the search method
getSearchAlgorithm() - Method in class weka.classifiers.bayes.BayesNet: Get the SearchAlgorithm used as the search algorithm
getSearchBackwards() - Method in class weka.attributeSelection.GreedyStepwise: Get whether to search backwards
getSearchMethod() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Gets the search method used.
getSearchStrategy() - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Get the search strategy wrapped by this step
getSearchString() - Method in class weka.gui.arffviewer.ArffTable: returns the search string, can be NULL if no search string is set
getSearchTermination() - Method in class weka.attributeSelection.BestFirst: Get the termination criterion (number of non-improving nodes).
getSeasonalityExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the seasonalityExpoSmooth property.
getSecondInputStructure() - Method in class weka.knowledgeflow.steps.Join: Get the Instances structure being produced by the second input
getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Get the index of the second value used.
getSecondValueIndex() - Method in class weka.filters.unsupervised.attribute.SwapValues: Get the index of the second value used.
getSeed() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the random number seed used for cross validation
getSeed() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get the random seed used to randomize the data before performing a percentage split
getSeed() - Method in class weka.attributeSelection.OneRAttributeEval: Get the random number seed
getSeed() - Method in class weka.attributeSelection.ReliefFAttributeEval: Get the seed used for randomly sampling instances.
getSeed() - Method in class weka.attributeSelection.WrapperSubsetEval: Get the random number seed used for cross validation
getSeed() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getSeed() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Returns the random seed
getSeed() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getSeed() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getSeed() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
getSeed() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getSeed() - Method in class weka.classifiers.BVDecompose: Gets the random number seed
getSeed() - Method in class weka.classifiers.BVDecomposeSegCVSub: Gets the random number seed
getSeed() - Method in class weka.classifiers.evaluation.EvaluationUtils: Gets the seed for randomization during cross-validation
getSeed() - Method in class weka.classifiers.functions.MultilayerPerceptron
getSeed() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Gets the current seed value for the random number generator
getSeed() - Method in class weka.classifiers.functions.VotedPerceptron: Get the value of Seed.
getSeed() - Method in class weka.classifiers.meta.MultiScheme: Gets the random number seed.
getSeed() - Method in class weka.classifiers.RandomizableClassifier: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.rules.JRip: Gets the current seed value to use in randomizing the data
getSeed() - Method in class weka.classifiers.rules.PART: Get the value of Seed.
getSeed() - Method in class weka.classifiers.trees.J48: Get the value of Seed.
getSeed() - Method in class weka.classifiers.trees.RandomTree: Gets the seed for the random number generations
getSeed() - Method in class weka.classifiers.trees.REPTree: Get the value of Seed.
getSeed() - Method in class weka.clusterers.RandomizableClusterer: Gets the seed for the random number generations
getSeed() - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Gets the seed for the random number generations
getSeed() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Gets the seed for the random number generations
getSeed() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns the seed for random number generator.
getSeed() - Method in interface weka.core.Randomizable: Gets the seed for the random number generations
getSeed() - Method in class weka.core.TestInstances: returns the current seed value
getSeed() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Gets the random number seed.
getSeed() - Method in class weka.datagenerators.DataGenerator: Gets the random number seed.
getSeed() - Method in class weka.estimators.UnivariateMixtureEstimator: Gets the seed for the random number generations
getSeed() - Method in class weka.filters.MultiFilter: Gets the seed for the random number generations
getSeed() - Method in class weka.filters.supervised.attribute.ClassOrder: Get the current randomization seed
getSeed() - Method in class weka.filters.supervised.instance.Resample
getSeed() - Method in class weka.filters.supervised.instance.SpreadSubsample
getSeed() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets the random number seed used for shuffling the dataset.
getSeed() - Method in class weka.filters.unsupervised.attribute.AddNoise
getSeed() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Gets the random seed of the random number generator
getSeed() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Get the seed value for the random number generator.
getSeed() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Get the random number generator seed value.
getSeed() - Method in class weka.filters.unsupervised.instance.Randomize
getSeed() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets the random number seed used for shuffling the dataset.
getSeed() - Method in class weka.filters.unsupervised.instance.Resample
getSeed() - Method in class weka.filters.unsupervised.instance.ReservoirSample
getSeed() - Method in class weka.gui.beans.CrossValidationFoldMaker: Get the currently set seed
getSeed() - Method in class weka.gui.beans.TrainTestSplitMaker: Get the value of the random seed
getSeed() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Get the random seed
getSeed() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Get the random seed to use
getSegment() - Method in class weka.core.pmml.jaxbbindings.Segmentation: Gets the value of the segment property.
getSegmentId() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the segmentId property.
getSelectedAttributes() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
getSelectedAttributes() - Method in class weka.gui.AttributeSelectionPanel: Gets an array containing the indices of all selected attributes.
getSelectedBeans() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getSelectedBeans(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getSelectedBuffer() - Method in class weka.gui.ResultHistoryPanel: Gets the buffer associated with the currently selected item in the list.
getSelectedClassIndex() - Method in class weka.gui.explorer.ClassifierPanel: Get the selected (0-based) class index
getSelectedEnumValue() - Method in class weka.core.EnumHelper: Get the selected/wrapped enum value (as obtained by calling toString() on the enum value)
getSelectedEvalMetrics() - Method in class weka.gui.EvaluationMetricSelectionDialog: Get the list of selected evaluation metrics
getSelectedName() - Method in class weka.gui.ResultHistoryPanel: Get the name of the currently selected item in the list
getSelectedObject() - Method in class weka.gui.ResultHistoryPanel: Gets the object associated with the currently selected item in the list.
getSelectedRange() - Method in class weka.core.DictionaryBuilder: Get the value of m_SelectedRange.
getSelectedRange() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Get the value of m_SelectedRange.
getSelectedTag() - Method in class weka.core.SelectedTag: Gets the selected Tag.
getSelection() - Method in class weka.core.Range: Gets an array containing all the selected values, in the order that they were selected (or ascending order if range inversion is on).
getSelectionModel() - Method in class weka.gui.AttributeListPanel: Gets the selection model used by the table.
getSelectionModel() - Method in class weka.gui.AttributeSelectionPanel: Gets the selection model used by the table.
getSelectionModel() - Method in class weka.gui.ResultHistoryPanel: Gets the selection model used by the results list.
getSeparateTestSetClassIndex() - Method in class weka.gui.explorer.ClassifierPanel: Get the class index specified for the separate test set
getSeparateTestSetLoader() - Method in class weka.gui.explorer.ClassifierPanel: Get the loader object used for loading a separate test set
getSeperator() - Method in class weka.gui.HierarchyPropertyParser: Get the seperator between levels.
getSeqId() - Method in class weka.core.pmml.jaxbbindings.SequenceReference: Gets the value of the seqId property.
getSequenceModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the sequenceModel property.
getSequenceReference() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence: Gets the value of the sequenceReference property.
getSequenceReference() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence: Gets the value of the sequenceReference property.
getSerializedClassifierFile() - Method in class weka.filters.supervised.attribute.AddClassification: Gets the file pointing to a serialized, trained classifier.
getSerializedClustererFile() - Method in class weka.filters.unsupervised.attribute.AddCluster: Gets the file pointing to a serialized, built clusterer.
getSetId() - Method in class weka.core.pmml.jaxbbindings.SetReference: Gets the value of the setId property.
getSetNumber() - Method in class weka.gui.beans.BatchClassifierEvent: Get the set number (ie which fold this is)
getSetNumber() - Method in class weka.gui.beans.BatchClustererEvent: Get the set number (ie which fold this is)
getSetNumber() - Method in class weka.gui.beans.TestSetEvent: Get the test set number (eg.
getSetNumber() - Method in class weka.gui.beans.TrainingSetEvent: Get the set number (eg.
getSetReference() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the setReference property.
getSetting(String, String, T, Environment) - Method in class weka.core.Settings
getSetting(String, Settings.SettingKey, T) - Method in class weka.core.Settings: Get the value of a setting
getSetting(String, Settings.SettingKey, T, Environment) - Method in class weka.core.Settings: Get the value of a setting
getSetting(Settings.SettingKey, T) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the value of a setting for the main perspective
getSettings(String) - Method in class weka.core.Settings: Get the settings for a given ID
getSettings() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Get the settings object for the application
getSettings() - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Get the settings object
getSettings() - Method in class weka.knowledgeflow.BaseExecutionEnvironment
getSettings() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get knowledge flow settings for this execution environment
getSettings() - Method in interface weka.knowledgeflow.FlowExecutor: Convenience method for getting current settings - implementers should delegate the the execution environment
getSettings() - Method in class weka.knowledgeflow.FlowRunner: Get the settings in use when executing the Flow
getSettings() - Method in interface weka.knowledgeflow.StepManager: Get the knowledge flow settings
getSettings() - Method in class weka.knowledgeflow.StepManagerImpl: Get the current knowledge flow settings
getSettingsIDs() - Method in class weka.core.Settings: Get a list of settings IDs
getSetupPanel() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the class name of the default setup panel.
getShape() - Method in class weka.gui.treevisualizer.Node: Get the value of shape.
getShapeSize() - Method in class weka.gui.visualize.PlotData2D: Get the shape sizes for the plot data
getShapeType() - Method in class weka.gui.visualize.PlotData2D: Get the shape types for the plot data
getShowAttBars() - Method in class weka.gui.visualize.VisualizePanel: Gets whether or not attribute bars are being displayed.
getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffPanel: Returns whether to display the attribute index in the header.
getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffSortedTableModel: Returns whether to display the attribute index in the header.
getShowAttributeIndex() - Method in class weka.gui.arffviewer.ArffTableModel: Returns whether to display the attribute index in the header.
getShowAverage() - Method in class weka.experiment.ResultMatrix: returns whether average per column is displayed or not.
getShowAverage() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns whether the Average is shown by default.
getShowClassPanel() - Method in class weka.gui.visualize.VisualizePanel: Gets whether or not the class panel is being displayed.
getShowGlobalInfoToolTips() - Method in class weka.gui.GenericObjectEditor
getShowStdDev() - Method in class weka.experiment.ResultMatrix: returns whether std deviations are displayed or not.
getShowStdDevs() - Method in class weka.experiment.PairedTTester: Returns true if standard deviations have been requested.
getShowStdDevs() - Method in interface weka.experiment.Tester: Returns true if standard deviations have been requested.
getShowStdDevs() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns whether StdDevs are shown by default.
getShowZeroInstancesAsUnknown() - Method in class weka.gui.InstancesSummaryPanel: Get whether to show zero instances as unknown (i.e.
getShrinkage() - Method in class weka.classifiers.meta.AdditiveRegression: Get the shrinkage rate.
getShrinkage() - Method in class weka.classifiers.meta.LogitBoost: Get the value of Shrinkage.
getSigma() - Method in class weka.attributeSelection.ReliefFAttributeEval: Get the value of sigma.
getSigma() - Method in class weka.classifiers.BVDecompose: Get the calculated sigma squared
getSigma() - Method in class weka.classifiers.functions.supportVector.Puk: Gets the sigma value.
getSignificance(int, int) - Method in class weka.experiment.ResultMatrix: returns the significance at the given position, if the position is valid, otherwise SIGNIFICANCE_ATIE.
getSignificance() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default significance.
getSignificanceCount(int, int) - Method in class weka.experiment.ResultMatrix: counts the occurrences of the given significance type in the given column.
getSignificanceLevel() - Method in class weka.associations.Apriori: Get the value of significanceLevel.
getSignificanceLevel() - Method in class weka.experiment.PairedTTester: Get the value of SignificanceLevel.
getSignificanceLevel() - Method in interface weka.experiment.Tester: Get the value of SignificanceLevel.
getSignificanceLevel() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Gets the significance level.
getSignificanceWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the significance.
getSilent() - Method in class weka.core.Check: Get whether silent mode is turned on
getSilent() - Method in class weka.core.Javadoc: whether output in the console is suppressed
getSilent() - Method in class weka.estimators.CheckEstimator: Get whether silent mode is turned on
getSimilarityScale() - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Gets the value of the similarityScale property.
getSimilarityType() - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity: Gets the value of the similarityType property.
getSimpleMatching() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the simpleMatching property.
getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the simplePredicate property.
getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the simplePredicate property.
getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the simplePredicate property.
getSimplePredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the simplePredicate property.
getSimplePredicateOrCompoundPredicateOrSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate: Gets the value of the simplePredicateOrCompoundPredicateOrSimpleSetPredicate property.
getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the simpleSetPredicate property.
getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the simpleSetPredicate property.
getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the simpleSetPredicate property.
getSimpleSetPredicate() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the simpleSetPredicate property.
getSimpleStats(int) - Method in class weka.classifiers.rules.RuleStats: Get the simple stats of one rule, including 6 parameters: 0: coverage; 1:uncoverage; 2: true positive; 3: true negatives; 4: false positives; 5: false negatives
getSIndex() - Method in class weka.gui.visualize.VisualizePanel: Get the index of the shape selected for creating splits.
getSingleIndex() - Method in class weka.core.SingleIndex: Gets the string representing the selected range of values.
getSingleLineCommentStart() - Method in class weka.gui.scripting.SyntaxDocument: Retrusn the single line comment start string.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.LED24: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the single mode flag.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.regression.Expression: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleModeFlag() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Gets the single mode flag.
getSingleModeFlag() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Gets the single mode flag.
getSingleModeFlag() - Method in class weka.datagenerators.DataGenerator: Return if single mode is set for the given data generator mode depends on option setting and or generator type.
getSingleton() - Static method in class weka.core.logging.Logger: Returns the singleton instance of the logger.
getSingleton() - Static method in class weka.gui.beans.KnowledgeFlowApp: Return the singleton instance of the KnowledgeFlow
getSingleton() - Static method in class weka.gui.Main: Return the singleton instance of the Main GUI.
getSingularValues() - Method in class weka.core.matrix.SingularValueDecomposition: Return the one-dimensional array of singular values
getSize() - Method in class weka.core.Debug.Log: returns the size of the files
getSize() - Method in class weka.core.pmml.jaxbbindings.Cluster: Gets the value of the size property.
getSize() - Method in class weka.core.pmml.jaxbbindings.Partition: Gets the value of the size property.
getSize() - Method in class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
getSize() - Method in class weka.gui.EnvironmentField.WideComboBox
getSkipIdentical() - Method in class weka.core.neighboursearch.LinearNNSearch: Gets whether if identical instances are skipped from the neighbourhood.
getSlope() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns the slope of the function.
getSlope() - Method in class weka.classifiers.trees.lmt.SimpleLinearRegression: Returns the slope of the function.
getSmoothedValue() - Method in class weka.core.pmml.jaxbbindings.Level: Gets the value of the smoothedValue property.
getSmoothedValue() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Gets the value of the smoothedValue property.
getSmoothing() - Method in class weka.classifiers.trees.m5.Rule: Get whether or not smoothing has been turned on
getSnapToGrid() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Return true if the snap-to-grid button is selected
getSons() - Method in class weka.classifiers.trees.j48.ClassifierTree
getSort() - Method in class weka.filters.unsupervised.attribute.AddValues: Gets whether the labels are sorted or not.
getSortColumn() - Method in class weka.experiment.PairedTTester: Returns the column to sort on, -1 means the default sorting.
getSortColumn() - Method in interface weka.experiment.Tester: Returns the column to sort on, -1 means the default sorting.
getSortColumnName() - Method in class weka.experiment.PairedTTester: Returns the name of the column to sort on.
getSortColumnName() - Method in interface weka.experiment.Tester: Returns the name of the column to sort on.
getSortDetails() - Method in class weka.gui.beans.Sorter: Get the sort rules to use
getSortDetails() - Method in class weka.knowledgeflow.steps.Sorter: Get the sort rules to use
getSortDictionary() - Method in class weka.core.DictionaryBuilder: Get whether to keep the dictionary sorted alphabetically as it is built.
getSorting() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default sorting (empty string means none).
getSortType() - Method in class weka.filters.unsupervised.attribute.SortLabels: Gets the sort type to be used.
getSource() - Method in class weka.core.packageManagement.Dependency: Get the source package.
getSource() - Method in class weka.gui.beans.BeanConnection: returns the source BeanInstance for this connection
getSource() - Method in class weka.gui.treevisualizer.Edge: Get the value of source.
getSourceCode() - Method in class weka.classifiers.CheckSource: Gets the class to test.
getSourceCode() - Method in class weka.filters.CheckSource: Gets the class to test.
getSourceCodeClassName() - Method in class weka.gui.explorer.ClassifierPanel: Gets the name of the source code class to be generated
getSourceStep() - Method in class weka.knowledgeflow.Data: Get the source step producing this Data object
getSparseData() - Method in class weka.core.converters.DatabaseLoader: Gets whether data is to be returned as a set of sparse instances
getSparseData() - Method in class weka.experiment.InstanceQuery: Gets whether data is to be returned as a set of sparse instances
getSparseData() - Method in interface weka.experiment.InstanceQueryAdapter: Gets whether data is to be returned as a set of sparse instances
getSplitByDataSet() - Method in class weka.experiment.RemoteExperiment: Returns true if sub experiments are to be created on the basis of data set.
getSplitByProperty() - Method in class weka.experiment.RemoteExperiment: Returns true if sub experiments are to be created on the basis of property.
getSplitCharacteristic() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the splitCharacteristic property.
getSplitCharacteristic() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the splitCharacteristic property.
getSplitConfidence() - Method in class weka.classifiers.trees.HoeffdingTree: Get the allowable error in a split decision.
getSplitCriterion() - Method in class weka.classifiers.trees.HoeffdingTree: Get the split criterion to use (either Gini or info gain).
getSplitDim() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode: Gets the splitting dimension.
getSplitEvaluator() - Method in class weka.experiment.CrossValidationResultProducer: Get the SplitEvaluator.
getSplitEvaluator() - Method in class weka.experiment.ExplicitTestsetResultProducer: Get the SplitEvaluator.
getSplitEvaluator() - Method in class weka.experiment.RandomSplitResultProducer: Get the SplitEvaluator.
getSplitOnResiduals() - Method in class weka.classifiers.trees.LMT: Get the value of splitOnResiduals.
getSplitPercent() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get the split percentage to use
getSplitPercentage() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of SplitPercentage.
getSplitPoint() - Method in class weka.associations.NumericItem: Gets the numeric test.
getSplitPoint() - Method in class weka.classifiers.rules.JRip.NumericAntd: Get split point of this numeric antecedent
getSplitPoint() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Get the split point used for numeric selection
getSplitValue() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode: Gets the splitting value.
getSpreadAttributeWeight() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: If true, when generating attributes, spread weight of old attribute across new attributes.
getSpreadAttributeWeight() - Method in class weka.filters.supervised.attribute.Discretize: If true, when generating binary attributes, spread weight of old attribute across new attributes.
getSpreadAttributeWeight() - Method in class weka.filters.supervised.attribute.NominalToBinary: If true, when generating binary attributes, spread weight of old attribute across new attributes.
getSpreadAttributeWeight() - Method in class weka.filters.unsupervised.attribute.Discretize: If true, when generating binary attributes, spread weight of old attribute across new attributes.
getSpreadAttributeWeight() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: If true, when generating binary attributes, spread weight of old attribute across new attributes.
getSpreadInitialCount() - Method in class weka.classifiers.trees.REPTree: Get the value of SpreadInitialCount.
getSqlWhere() - Method in class weka.core.pmml.jaxbbindings.Aggregate: Gets the value of the sqlWhere property.
getSquaredError() - Method in class weka.clusterers.SimpleKMeans: Gets the squared error for all clusters.
getSquaredEuclidean() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the squaredEuclidean property.
getSSB() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Gets the value of the ssb property.
getSSE() - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Gets the value of the sse property.
getStamp() - Method in class weka.core.Debug.Timestamp: returns the associated date/time
getStandardDeviation(Instance) - Method in class weka.classifiers.functions.GaussianProcesses: Gives standard deviation of the prediction at the given instance.
getStandardDeviation() - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Gets the value of the standardDeviation property.
getStandardDeviation() - Method in class weka.core.pmml.jaxbbindings.Time: Gets the value of the standardDeviation property.
getStandardError() - Method in class weka.core.pmml.jaxbbindings.TimeValue: Gets the value of the standardError property.
getStart() - Method in class weka.core.Debug.Clock: returns the start time
getStartMessage() - Method in class weka.gui.beans.Loader: Gets a string that describes the start action.
getStartMessage() - Method in class weka.gui.beans.MetaBean
getStartMessage() - Method in interface weka.gui.beans.Startable: Gets a string that describes the start action.
getStartPoints(Integer...) - Static method in class weka.gui.beans.BeanInstance: Returns a list of start points (if any) in the indexed flow
getStartSequentially() - Method in class weka.gui.beans.FlowRunner: Gets whether Startable beans will be launched sequentially or all in parallel.
getStartSet() - Method in class weka.attributeSelection.BestFirst: Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.GreedyStepwise: Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in class weka.attributeSelection.Ranker: Returns a list of attributes (and or attribute ranges) as a String
getStartSet() - Method in interface weka.attributeSelection.StartSetHandler: Returns a list of attributes (and or attribute ranges) as a String
getStartTime() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the startTime property.
getStartTimeVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the startTimeVariable property.
getStaticArgs() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the arguments for the static command
getStaticCmd() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the static command to be executed
getStaticIcon() - Method in class weka.gui.beans.BeanVisual: Returns the static icon
getStaticWorkingDir() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get the working directory for the static command
getStatistic(String) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Get the value of the named statistic
getStatistic(String, int) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric: Get the value of the named statistic for the given class index.
getStatisticNames() - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Get a list of the names of the statistics that this metrics computes.
getStats() - Method in class weka.core.neighboursearch.PerformanceStats: Returns a string representation of the statistics.
getStats() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns a string representation of the statistics.
getStatus() - Method in class weka.gui.beans.IncrementalClassifierEvent: Get the status
getStatus() - Method in class weka.gui.beans.InstanceEvent: Get the status
getStatusFrequency() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Get how often progress is reported to the status bar.
getStatusFrequency() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Get how often progress is reported to the status bar.
getStatusMessage() - Method in class weka.experiment.TaskStatusInfo: Get the status message.
getStatusTable() - Method in class weka.gui.beans.LogPanel: The JTable used for the status messages (in case clients want to attach listeners etc.)
getStatusVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the statusVariable property.
getStdDev() - Method in class weka.estimators.KernelEstimator: Return the standard deviation of this kernel estimator.
getStdDev() - Method in class weka.estimators.NormalEstimator: Return the value of the standard deviation of this normal estimator.
getStdDev(int, int) - Method in class weka.experiment.ResultMatrix: returns the std deviation at the given position, if the position is valid, otherwise 0.
getStdDevCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the standard deviation of coords per point.
getStdDevIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the standard deviation of internal nodes visited.
getStdDevLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the standard deviation of leaves visited.
getStdDevPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the standard deviation of points visited.
getStdDevPrec() - Method in class weka.experiment.ResultMatrix: returns the current standard deviation precision.
getStdDevPrecision() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the default precision for the stddevs.
getStddevValue() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition
getStdDevWidth() - Method in class weka.experiment.ResultMatrix: returns the current width for the std dev.
getStdError() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the stdError property.
getStemmer() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the current stemming algorithm, null if none is used.
getStemmer() - Method in class weka.classifiers.functions.SGDText: Returns the current stemming algorithm, null if none is used.
getStemmer() - Method in class weka.core.converters.DictionarySaver: Returns the current stemming algorithm, null if none is used.
getStemmer() - Method in class weka.core.DictionaryBuilder: Returns the current stemming algorithm, null if none is used.
getStemmer() - Method in class weka.core.stemmers.SnowballStemmer: returns the name of the current stemmer, null if none is set.
getStemmer() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Returns the current stemming algorithm, null if none is used.
getStemmer() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the current stemming algorithm, null if none is used.
getStep() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Get the step that owns this viewer.
getStepInteractiveViewActionNames() - Method in class weka.gui.knowledgeflow.StepVisual: Get a set of fully qualified names of interactive viewers that the wrapped step provides.
getStepInteractiveViewComponent(String) - Method in class weka.gui.knowledgeflow.StepVisual: Gets an instance of the named step interactive viewer component
getStepManager() - Method in class weka.gui.knowledgeflow.StepVisual: Get the step manager for this visual
getStepManager() - Method in class weka.knowledgeflow.steps.BaseStep: Get the step manager for this step
getStepManager() - Method in interface weka.knowledgeflow.steps.Step: Get the step manager in use with this step
getStepMustRunSingleThreaded() - Method in interface weka.knowledgeflow.StepManager: Returns true if the step managed by this step manager has been marked as one that must run single-threaded.
getStepMustRunSingleThreaded() - Method in class weka.knowledgeflow.StepManagerImpl: Get whether the managed step must run single-threaded.
getStepName() - Method in class weka.gui.knowledgeflow.StepVisual: Convenience method for getting the name of the step that this visual wraps
getStepOutgoingConnectionTypes() - Method in class weka.knowledgeflow.StepManagerImpl: Used by the rendering routine in LayoutPanel to ensure that connections downstream from a deleted connection get rendered in grey rather than red.
getStepProperties(String) - Method in class weka.knowledgeflow.JobEnvironment: Get the step properties for a named step
getStepProperty(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get a named property for this step.
getSteps() - Method in class weka.knowledgeflow.Flow: Get a list of the Steps in this Flow
getStepSize() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of StepSize.
getStepsize() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the stepsize property.
getStepSize() - Method in class weka.experiment.LearningRateResultProducer: Get the value of StepSize.
getStepToWaitFor() - Method in class weka.knowledgeflow.steps.Block: Get the step to wait for
getStepVisual() - Method in class weka.knowledgeflow.StepManagerImpl: Get the step visual in use (if running in a visual environment)
getStop() - Method in class weka.core.Debug.Clock: returns the stop time or, if still running, the current time
getStopwords() - Method in class weka.core.stopwords.AbstractFileBasedStopwords: returns the file used for obtaining the stopwords, if the file represents a directory then the default ones are used.
getStopwords() - Method in class weka.core.stopwords.MultiStopwords: Returns the stopwords algorithms.
getStopwordsHandler() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Gets the stopwords handler.
getStopwordsHandler() - Method in class weka.classifiers.functions.SGDText: Gets the stopwords handler.
getStopwordsHandler() - Method in class weka.core.converters.DictionarySaver: Gets the stopwords handler.
getStopwordsHandler() - Method in class weka.core.DictionaryBuilder: Gets the stopwords handler.
getStopwordsHandler() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets the stopwords handler.
getStopwordsHandler() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets the stopwords handler.
getStoreName() - Method in class weka.core.Settings: Get the store name for these settings
getStoreOutOfBagPredictions() - Method in class weka.classifiers.meta.Bagging: Get whether the out of bag predictions are stored.
getString() - Method in class weka.core.Trie.TrieNode: returns the full string up to the root
getStringAttributes() - Method in class weka.core.converters.CSVLoader: Returns the current attribute range to be forced to type string.
getStringSelection() - Method in class weka.gui.arffviewer.ArffTable: returns the selected content in a StringSelection that can be copied to the clipboard and used in Excel, if nothing is selected the whole table is copied to the clipboard
getStroke() - Method in class weka.gui.visualize.PostscriptGraphics
getStructure() - Method in class weka.core.converters.AbstractLoader
getStructure() - Method in class weka.core.converters.ArffLoader.ArffReader: Returns the header format
getStructure() - Method in class weka.core.converters.ArffLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.C45Loader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.ConverterUtils.DataSource: returns the structure of the data.
getStructure(int) - Method in class weka.core.converters.ConverterUtils.DataSource: returns the structure of the data, with the defined class index.
getStructure() - Method in class weka.core.converters.CSVLoader
getStructure() - Method in class weka.core.converters.DatabaseLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.JSONLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.LibSVMLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in interface weka.core.converters.Loader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.MatlabLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.SerializedInstancesLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.SVMLightLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.TextDirectoryLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure() - Method in class weka.core.converters.XRFFLoader: Determines and returns (if possible) the structure (internally the header) of the data set as an empty set of instances.
getStructure(String) - Method in class weka.gui.beans.Associator: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.ClassAssigner: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.ClassValuePicker
getStructure(String) - Method in class weka.gui.beans.CrossValidationFoldMaker: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.FlowByExpression: Get the structure of the output encapsulated in the named event.
getStructure() - Method in class weka.gui.beans.IncrementalClassifierEvent: Get the instances structure (may be null if this is not a NEW_BATCH event)
getStructure() - Method in class weka.gui.beans.InstanceEvent: Get the instances structure (may be null if this is not a FORMAT_AVAILABLE event)
getStructure(String) - Method in class weka.gui.beans.Join: Get the output instances structure given an input event type
getStructure(String) - Method in class weka.gui.beans.Loader: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.Sorter: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in interface weka.gui.beans.StructureProducer: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.TestSetMaker: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.TrainingSetMaker: Get the structure of the output encapsulated in the named event.
getStructure(String) - Method in class weka.gui.beans.TrainTestSplitMaker: Get the structure of the output encapsulated in the named event.
getSubFlow() - Method in class weka.gui.beans.MetaBean
getSubjectIDVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the subjectIDVariable property.
getSubmenuTitle() - Method in interface weka.gui.MainMenuExtension: Returns the name of the submenu.
getSubsequenceLength() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the length of the subsequence
getSubSpaceSize() - Method in class weka.classifiers.meta.RandomSubSpace: Gets the size of each subSpace, as a percentage of the training set size.
getSubtreeRaising() - Method in class weka.classifiers.trees.J48: Get the value of subtreeRaising.
getSuccess() - Method in class weka.core.CheckGOE: returns the success of the tests
getSuccess() - Method in class weka.core.CheckOptionHandler: returns the success of the tests
getSuitableTargets(EventSetDescriptor) - Method in class weka.gui.beans.MetaBean: Return a list of input beans capable of receiving the supplied event
getSummary() - Method in class weka.gui.SetInstancesPanel: Gets the instances summary panel associated with this panel.
getSumOfCounts() - Method in class weka.estimators.DiscreteEstimator: Get the sum of all the counts
getSumOfSquares() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the sumOfSquares property.
getSumOfWeights() - Method in class weka.estimators.NormalEstimator: Return the sum of the weights for this normal estimator.
getSumSquaredError() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the sumSquaredError property.
getSumSquaredRegression() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the sumSquaredRegression property.
getSupport() - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Gets the value of the support property.
getSupport() - Method in class weka.core.pmml.jaxbbindings.Itemset: Gets the value of the support property.
getSupport() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the support property.
getSupport() - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Gets the value of the support property.
getSupportedCursorScrollType() - Method in class weka.experiment.DatabaseUtils: Returns the type of scrolling that the cursor supports, -1 if not supported or not connected.
getSupportVector() - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Gets the value of the supportVector property.
getSupportVectorMachineModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the supportVectorMachineModel property.
getSupportVectors() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the supportVectors property.
getSuppressMappingReport() - Method in class weka.classifiers.misc.InputMappedClassifier: Get whether to suppress output the report of model to input mappings.
getSuppressOutput() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns whether to the regular output is suppressed in case the output is stored in a file.
getSvmRepresentation() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the svmRepresentation property.
getSymbolContainer() - Method in class weka.core.expressionlanguage.parser.Parser
getSymbolContainer() - Method in class weka.core.json.Parser
getSystemInfo() - Method in class weka.core.SystemInfo: returns a copy of the system info.
getSystemLookAndFeel() - Static method in class weka.gui.LookAndFeel: returns the system LnF classname
getSystemWide() - Static method in class weka.core.Environment: Get the singleton system-wide (visible to every class in the running VM) set of environment variables.
getT1() - Method in class weka.clusterers.Canopy: Get the T1 distance.
getT2() - Method in class weka.clusterers.Canopy: Get the T2 distance to use.
getTabbedPane() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns the tabbedpane instance
getTabbedPane() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getTabbedPane() - Method in class weka.gui.explorer.Explorer: returns the tabbed pane of the Explorer
getTable() - Method in class weka.gui.arffviewer.ArffPanel: returns the table component
getTable() - Method in class weka.gui.InteractiveTablePanel: Get the JTable component
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class weka.gui.arffviewer.ArffTableCellRenderer: Returns the default table cell renderer.
getTableCellRendererComponent(JTable, Object, boolean, boolean, int, int) - Method in class weka.gui.sql.ResultSetTableCellRenderer: Returns the default table cell renderer.
getTableLocator() - Method in class weka.core.pmml.jaxbbindings.ChildParent: Gets the value of the tableLocator property.
getTableLocator() - Method in class weka.core.pmml.jaxbbindings.MapValues: Gets the value of the tableLocator property.
getTableLocator() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the tableLocator property.
getTableModel() - Method in class weka.gui.AttributeSelectionPanel: Get the table model in use (or null if no instances have been set yet).
getTableName() - Method in class weka.core.converters.DatabaseSaver: Gets the table's name.
getTabs() - Static method in class weka.gui.explorer.ExplorerDefaults: returns an array with the classnames of all the additional panels to display as tabs in the Explorer.
getTabTitle(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getTabTitle() - Method in class weka.gui.explorer.AssociationsPanel: Returns the title for the tab in the Explorer
getTabTitle() - Method in class weka.gui.explorer.AttributeSelectionPanel: Returns the title for the tab in the Explorer
getTabTitle() - Method in class weka.gui.explorer.ClassifierPanel: Returns the title for the tab in the Explorer.
getTabTitle() - Method in class weka.gui.explorer.ClustererPanel: Returns the title for the tab in the Explorer
getTabTitle() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel: Returns the title for the tab in the Explorer
getTabTitle() - Method in class weka.gui.explorer.PreprocessPanel: Returns the title for the tab in the Explorer
getTabTitle() - Method in class weka.gui.explorer.VisualizePanel: Returns the title for the tab in the Explorer
getTabTitle(int) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the title of the tab at the supplied index
getTabTitleToolTip() - Method in class weka.gui.explorer.AssociationsPanel: Returns the tooltip for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.AttributeSelectionPanel: Returns the tooltip for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.ClassifierPanel: Returns the tooltip for the tab in the Explorer.
getTabTitleToolTip() - Method in class weka.gui.explorer.ClustererPanel: Returns the tooltip for the tab in the Explorer
getTabTitleToolTip() - Method in interface weka.gui.explorer.Explorer.ExplorerPanel: Returns the tooltip for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.PreprocessPanel: Returns the tooltip for the tab in the Explorer
getTabTitleToolTip() - Method in class weka.gui.explorer.VisualizePanel: Returns the tooltip for the tab in the Explorer
getTabuList() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
getTabuList() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
getTags() - Method in class weka.core.SelectedTag: Gets the set of all valid Tags.
getTags() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getTags() - Method in class weka.gui.ColorEditor: Not applicable - returns null
getTags() - Method in class weka.gui.CostMatrixEditor: Some objects can return tags, but a cost matrix cannot.
getTags() - Method in class weka.gui.EnvironmentField
getTags() - Method in class weka.gui.GenericArrayEditor: Returns null as we don't support getting values as tags.
getTags() - Method in class weka.gui.GenericObjectEditor: Returns null as we don't support getting values as tags.
getTags() - Method in class weka.gui.PasswordField
getTags() - Method in class weka.gui.SelectedTagEditor: Gets the list of tags that can be selected from.
getTags() - Method in class weka.gui.SimpleDateFormatEditor: Some objects can return tags, but a date format cannot.
getTanimoto() - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Gets the value of the tanimoto property.
getTarget() - Method in class weka.core.packageManagement.Dependency: Get the target package constraint.
getTarget() - Method in class weka.core.pmml.jaxbbindings.Anova: Gets the value of the target property.
getTarget() - Method in class weka.core.pmml.jaxbbindings.Targets: Gets the value of the target property.
getTarget() - Method in class weka.gui.beans.BeanConnection: Returns the target BeanInstance for this connection
getTarget() - Method in class weka.gui.treevisualizer.Edge: Get the value of target.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.MultivariateStats: Gets the value of the targetCategory property.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PCell: Gets the value of the targetCategory property.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the targetCategory property.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.PPCell: Gets the value of the targetCategory property.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Gets the value of the targetCategory property.
getTargetCategory() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the targetCategory property.
getTargetField() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the targetField property.
getTargetField() - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Gets the value of the targetField property.
getTargetFieldDisplayValue() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the targetFieldDisplayValue property.
getTargetFieldName() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the targetFieldName property.
getTargetFieldValue() - Method in class weka.core.pmml.jaxbbindings.LiftData: Gets the value of the targetFieldValue property.
getTargetMetaData() - Method in class weka.core.pmml.MiningSchema: Get the Target meta data.
getTargetReferenceCategory() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the targetReferenceCategory property.
getTargets() - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Gets the value of the targets property.
getTargets() - Method in class weka.core.pmml.jaxbbindings.Regression: Gets the value of the targets property.
getTargetValue() - Method in class weka.core.pmml.jaxbbindings.Target: Gets the value of the targetValue property.
getTargetValueCount() - Method in class weka.core.pmml.jaxbbindings.TargetValueCounts: Gets the value of the targetValueCount property.
getTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.BayesOutput: Gets the value of the targetValueCounts property.
getTargetValueCounts() - Method in class weka.core.pmml.jaxbbindings.PairCounts: Gets the value of the targetValueCounts property.
getTargetVariableName() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the targetVariableName property.
getTaskResult() - Method in class weka.experiment.TaskStatusInfo: Get the returnable result of this task.
getTaskStatus() - Method in class weka.experiment.RemoteExperimentSubTask
getTaskStatus() - Method in interface weka.experiment.Task: Clients should be able to call this method at any time to obtain information on a current task.
getTaskStatus() - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Return status information for this sub task
getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.DataDictionary: Gets the value of the taxonomy property.
getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the taxonomy property.
getTaxonomy() - Method in class weka.core.pmml.jaxbbindings.TextDictionary: Gets the value of the taxonomy property.
getTCol() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the tCol property.
getTechnicalInformation() - Method in class weka.associations.Apriori: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.associations.FPGrowth: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.attributeSelection.CfsSubsetEval: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayes: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.ADNode: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.BIFReader: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.K2: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.global.TAN: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.K2: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.bayes.net.search.local.TAN: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.BVDecompose: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.GaussianProcesses: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.Logistic: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.SimpleLogistic: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.SMO: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.SMOreg: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.Puk: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.functions.VotedPerceptron: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.lazy.IBk: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.lazy.KStar: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.lazy.LWL: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.AdaBoostM1: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.AdditiveRegression: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.Bagging: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.CVParameterSelection: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.LogitBoost: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.RandomSubSpace: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.Stacking: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.meta.Vote: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.rules.DecisionTable: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.rules.JRip: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.rules.M5Rules: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.rules.OneR: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.rules.PART: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.HoeffdingTree: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.J48: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.LMT: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.m5.M5Base: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.classifiers.trees.RandomForest: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.clusterers.Canopy
getTechnicalInformation() - Method in class weka.clusterers.Cobweb: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.clusterers.FarthestFirst: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.clusterers.SimpleKMeans
getTechnicalInformation() - Method in class weka.core.ChebyshevDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.ConjugateGradientOptimization: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.EuclideanDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.ManhattanDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.MinkowskiDistance: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.BallTree: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.CoverTree: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.KDTree: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.Optimization: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.core.stemmers.LovinsStemmer: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in interface weka.core.TechnicalInformationHandler: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.datagenerators.classifiers.classification.LED24: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.experiment.PairedCorrectedTTester: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.supervised.attribute.Discretize: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.supervised.attribute.PartitionMembership: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTechnicalInformation() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Returns an instance of a TechnicalInformation object, containing detailed information about the technical background of this class, e.g., paper reference or book this class is based on.
getTempDir() - Static method in class weka.core.Debug: returns the system temp directory
getTempDirectory() - Method in class weka.gui.beans.Sorter: Get the directory to use for temporary files during incremental operation
getTempDirectory() - Method in class weka.knowledgeflow.steps.Sorter: Get the directory to use for temporary files during incremental operation
getTemplateFlow(String) - Method in class weka.gui.knowledgeflow.TemplateManager: Get the flow for the supplied description
getTemplateManager() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Get the template manager
getTester() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the display name of the preferred Tester algorithm.
getTestEvaluator() - Method in class weka.attributeSelection.CheckAttributeSelection: Gets whether the evaluator is being tested or the search method.
getTestOrTrain() - Method in class weka.gui.beans.BatchClustererEvent: Get whether the set of instances is a test or a training set
getTestPredictions(Classifier, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils: Generate a bunch of predictions ready for processing, by performing a evaluation on a test set assuming the classifier is already trained.
getTestSet() - Method in class weka.gui.beans.BatchClassifierEvent: Get the test set
getTestSet() - Method in class weka.gui.beans.BatchClustererEvent: Get the training/test set
getTestSet() - Method in class weka.gui.beans.TestSetEvent: Get the test set instances
getTestsetDir() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the currently set directory for the test sets.
getTestsetPrefix() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the currently set prefix.
getTestsetSuffix() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the currently set suffix.
getTestStatistic() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the testStatistic property.
getText() - Method in class weka.gui.beans.BeanVisual: Get the visual's label
getText() - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Return the text from the combo box.
getText() - Method in class weka.gui.beans.TextEvent: Describe getText method here.
getText() - Method in class weka.gui.EnvironmentField: Return the text from the combo box.
getText() - Method in class weka.gui.PasswordField
getTextDocument() - Method in class weka.core.pmml.jaxbbindings.TextCorpus: Gets the value of the textDocument property.
getTextModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the textModel property.
getTextTitle() - Method in class weka.gui.beans.TextEvent: Describe getTextTitle method here.
getTFTransform() - Method in class weka.core.DictionaryBuilder: Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
getTFTransform() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
getTFTransform() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
getThreshold() - Method in class weka.attributeSelection.ClassifierAttributeEval: Get the value of the threshold
getThreshold() - Method in class weka.attributeSelection.GreedyStepwise: Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold() - Method in interface weka.attributeSelection.RankedOutputSearch: Gets the threshold by which attributes can be discarded.
getThreshold() - Method in class weka.attributeSelection.Ranker: Returns the threshold so that the AttributeSelection module can discard attributes from the ranking.
getThreshold() - Method in class weka.attributeSelection.WrapperSubsetEval: Get the value of the threshold
getThreshold() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the value of the threshold property.
getThreshold() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the threshold property.
getThreshold() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the threshold property.
getThreshold() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the threshold property.
getThreshold() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Gets the value of the threshold property.
getThreshold() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the threshold property.
getThreshold() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Gets the threshold for the max error when predicting a numeric class.
getThresholdInstance(Instances, double) - Static method in class weka.classifiers.evaluation.ThresholdCurve: Gets the index of the instance with the closest threshold value to the desired target
getThresholds() - Method in interface weka.classifiers.evaluation.ThresholdProducingMetric: Returns the threshold values, one for each class value, associated with the value of the measure that is returned.
getTime() - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence: Gets the value of the time property.
getTime() - Method in class weka.core.pmml.jaxbbindings.BaselineCell: Gets the value of the time property.
getTime() - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence: Gets the value of the time property.
getTime() - Method in class weka.core.pmml.jaxbbindings.Sequence: Gets the value of the time property.
getTime() - Method in class weka.core.pmml.jaxbbindings.TimeValue: Gets the value of the time property.
getTimeAnchor() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the timeAnchor property.
getTimeCycle() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the timeCycle property.
getTimeException() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the timeException property.
getTimeSeriesModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the timeSeriesModel property.
getTimestamp() - Method in class weka.core.pmml.jaxbbindings.Header: Gets the value of the timestamp property.
getTimestamp() - Method in class weka.core.pmml.jaxbbindings.TimeValue: Gets the value of the timestamp property.
getTimestamp() - Static method in class weka.experiment.CrossValidationResultProducer: Gets a Double representing the current date and time.
getTimestamp() - Static method in class weka.experiment.ExplicitTestsetResultProducer: Gets a Double representing the current date and time.
getTimestamp() - Static method in class weka.experiment.RandomSplitResultProducer: Gets a Double representing the current date and time.
getTimeValue() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the timeValue property.
getTimeValue() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the timeValue property.
getTitle() - Method in class weka.gui.arffviewer.ArffPanel: returns the title for the Tab, i.e.
getTitle() - Method in class weka.gui.scripting.FileScriptingPanel: Returns the current title for the frame/dialog.
getTitle() - Method in class weka.gui.scripting.ScriptingPanel: Returns the current title for the frame/dialog.
getTitle() - Method in class weka.gui.SimpleCLIPanel: Returns the current title for the frame/dialog.
getToken(StreamTokenizer) - Static method in class weka.core.converters.ConverterUtils: Gets token.
getToken(StreamTokenizer) - Static method in class weka.core.converters.StreamTokenizerUtils: Gets token.
getTokenizer() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the current tokenizer algorithm.
getTokenizer() - Method in class weka.classifiers.functions.SGDText: Returns the current tokenizer algorithm.
getTokenizer() - Method in class weka.core.converters.DictionarySaver: Returns the current tokenizer algorithm.
getTokenizer() - Method in class weka.core.DictionaryBuilder: Returns the current tokenizer algorithm.
getTokenizer() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Returns the current tokenizer algorithm.
getTokenizer() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the current tokenizer algorithm.
getTolerance() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: returns the current tolerance
getToleranceParameter() - Method in class weka.classifiers.functions.SMO: Get the value of tolerance parameter.
getToolTip() - Method in class weka.core.Settings.SettingKey: Get the tool tip text for this setting
getToolTipLocation(MouseEvent) - Method in class weka.gui.ETable: Places tool tips over the cell they correspond to.
getToolTipText() - Method in class weka.experiment.PairedCorrectedTTester: returns a string that is displayed as tooltip on the "perform test" button in the experimenter
getToolTipText() - Method in class weka.experiment.PairedTTester: returns a string that is displayed as tooltip on the "perform test" button in the experimenter
getToolTipText() - Method in interface weka.experiment.Tester: returns a string that is displayed as tooltip on the "perform test" button in the experimenter
getToolTipText(MouseEvent) - Method in class weka.gui.AttributeVisualizationPanel: Returns "<nominal value> [<nominal value count>]" if displaying a bar plot and mouse is on some bar.
getToolTipText() - Method in class weka.gui.GenericObjectEditor.GOETreeNode: Get the tool tip for this node
getToolTipText(MouseEvent) - Method in class weka.gui.knowledgeflow.StepTree: Get tool tip text for the step closest to the mouse location in the StepTree.
getToolTipText() - Method in class weka.gui.knowledgeflow.StepTreeLeafDetails: Get the tool tip for this leaf
getToolTipText(PrintableComponent) - Static method in class weka.gui.visualize.PrintableComponent: Returns a tooltip only if the user wants it.
getTop() - Method in class weka.gui.treevisualizer.Node: Get the value of top.
getTotalCoordsPerPoint() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the total sum of coords per point.
getTotalCount(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the total number of nodes there are.
getTotalFreq() - Method in class weka.core.pmml.jaxbbindings.Counts: Gets the value of the totalFreq property.
getTotalGCount(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the total number of groups of siblings there are.
getTotalHeight(Node, int) - Static method in class weka.gui.treevisualizer.Node: Recursively finds the total number of levels there are.
getTotalIntNodesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the total number of internal nodes visited.
getTotalLeavesVisited() - Method in class weka.core.neighboursearch.TreePerformanceStats: Returns the total number of leaves visited.
getTotalPointsVisited() - Method in class weka.core.neighboursearch.PerformanceStats: Returns the total number of points visited.
getTotalSquaresSum() - Method in class weka.core.pmml.jaxbbindings.ContStats: Gets the value of the totalSquaresSum property.
getTotalSupport() - Method in class weka.associations.AssociationRule: Get the total support for this rule (premise + consequence).
getTotalSupport() - Method in class weka.associations.DefaultAssociationRule
getTotalTransactions() - Method in class weka.associations.AssociationRule: Get the total number of transactions in the data.
getTotalTransactions() - Method in class weka.associations.DefaultAssociationRule
getTotalTransactions() - Method in class weka.associations.ItemSet: Get the total number of transactions
getTotalValuesSum() - Method in class weka.core.pmml.jaxbbindings.ContStats: Gets the value of the totalValuesSum property.
getToYear() - Static method in class weka.core.Copyright: returns the end year of the copyright (i.e., current year)
getTrainingData() - Method in class weka.classifiers.trees.j48.ClassifierTree
getTrainingSet() - Method in class weka.gui.beans.TrainingSetEvent: Get the training instances
getTrainingTime() - Method in class weka.classifiers.functions.MultilayerPerceptron
getTrainIterations() - Method in class weka.classifiers.BVDecompose: Gets the maximum number of boost iterations
getTrainPercent() - Method in class weka.experiment.RandomSplitResultProducer: Get the value of TrainPercent.
getTrainPercent() - Method in class weka.gui.beans.TrainTestSplitMaker: Get the percentage of the data that will be in the training portion of the split
getTrainPercent() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Get the training percentage
getTrainPercentage() - Static method in class weka.gui.experiment.ExperimenterDefaults: returns the training percentage in case of splits.
getTrainPoolSize() - Method in class weka.classifiers.BVDecompose: Get the number of instances in the training pool.
getTrainSet() - Method in class weka.gui.beans.BatchClassifierEvent: Get the train set
getTrainSize() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the training size
getTrainTestPredictions(Classifier, Instances, Instances) - Method in class weka.classifiers.evaluation.EvaluationUtils: Generate a bunch of predictions ready for processing, by performing a evaluation on a test set after training on the given training set.
getTransactionsMustContain() - Method in class weka.associations.FPGrowth: Gets the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
getTransform() - Method in class weka.gui.visualize.PostscriptGraphics
getTransformAllValues() - Method in class weka.filters.supervised.attribute.NominalToBinary: Gets if all nominal values are turned into new attributes, not only if there are more than 2.
getTransformAllValues() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Gets if all nominal values are turned into new attributes, not only if there are more than 2.
getTransformation() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the transformation property.
getTransformationDictionary() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the transformationDictionary property.
getTransformationDictionary() - Method in class weka.core.pmml.MiningSchema: Get the transformation dictionary .
getTransformBackToOriginal() - Method in class weka.attributeSelection.PrincipalComponents: Gets whether the data is to be transformed back to the original space.
getTranslation() - Method in class weka.filters.unsupervised.attribute.Normalize: Get the translation.
getTreatMissingValuesAsZero() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Get whether missing values are to be treated in the same way as zeros
getTreatXValFoldsSeparately() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get whether to output separate results for each fold of a cross-validation, rather than averaging over folds.
getTreatZeroAsMissing() - Method in class weka.associations.Apriori: Gets whether zeros (i.e.
getTreeModel() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the treeModel property.
getTreeRoot() - Method in class weka.clusterers.Cobweb: Get the root of the tree.
getTrend() - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Gets the value of the trend property.
getTrendExpoSmooth() - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Gets the value of the trendExpoSmooth property.
getTrialsValue() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the trialsValue property.
getTrialsVariable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the trialsVariable property.
getTrim() - Method in class weka.classifiers.misc.InputMappedClassifier: Get whether to trim white space from each end of names before matching.
getTRow() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the tRow property.
getTrue() - Method in class weka.core.pmml.jaxbbindings.Attribute: Gets the value of the true property.
getTrue() - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Gets the value of the true property.
getTrue() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the true property.
getTrue() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the true property.
getTrueNegative() - Method in class weka.classifiers.evaluation.TwoClassStats: Gets the number of negative instances predicted as negative
getTruePositive() - Method in class weka.classifiers.evaluation.TwoClassStats: Gets the number of positive instances predicted as positive
getTruePositiveRate() - Method in class weka.classifiers.evaluation.TwoClassStats: Calculate the true positive rate.
getTrueStepName() - Method in class weka.gui.beans.FlowByExpression: Get the name of the connected step to send "true" instances to
getTrueStepName() - Method in class weka.knowledgeflow.steps.FlowByExpression: Get the name of the connected step to send "true" instances to
getTruncate() - Method in class weka.core.converters.DatabaseSaver: Get whether to truncate (i.e.
getTStart() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
getTStart() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
getTValue() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the tValue property.
getTwoClassStats(int) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the performance with respect to one of the classes as a TwoClassStats object.
getType() - Method in class weka.classifiers.functions.neural.NeuralConnection
getType() - Method in class weka.core.AttributeLocator: returns the type of attribute that is located
getType() - Method in class weka.core.pmml.Array: Get the type of this array.
getType() - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.ArrayType: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.PCovMatrix: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Gets the value of the type property.
getType() - Method in class weka.core.pmml.jaxbbindings.TimeException: Gets the value of the type property.
getType(RevisionHandler) - Static method in class weka.core.RevisionUtils: Determines the type of a (sanitized) revision string returned by the RevisionHandler.
getType(String) - Static method in class weka.core.RevisionUtils: Determines the type of a (sanitized) revision string.
getType() - Method in class weka.core.TechnicalInformation: returns the type of this technical information
getType() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the type of the new attribute
getType(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the TYPE of the attribute at the given position
getType(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns the TYPE of the attribute at the given position
getType(int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the TYPE of the attribute at the given position
getType(int, int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the TYPE of the attribute at the given position
getType() - Method in class weka.gui.scripting.event.ScriptExecutionEvent: Returns the type of event.
getType() - Method in class weka.gui.sql.event.ConnectionEvent: returns the type of this event, CONNECT or DISCONNECT
getU() - Method in class weka.core.Matrix: Deprecated.

Returns the U part of the matrix.
getU() - Method in class weka.core.matrix.LUDecomposition: Return upper triangular factor
getU() - Method in class weka.core.matrix.SingularValueDecomposition: Return the left singular vectors
getUID(String) - Static method in class weka.core.SerializationHelper: reads or creates the serialVersionUID for the given class.
getUID(Class<?>) - Static method in class weka.core.SerializationHelper: reads or creates the serialVersionUID for the given class.
getUnderlyingPackageManager() - Static method in class weka.core.WekaPackageManager: Get the underlying package manager implementation
getUndoBuffer() - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getUndoBuffer(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.Alternate: Gets the value of the uniformDistribution property.
getUniformDistribution() - Method in class weka.core.pmml.jaxbbindings.Baseline: Gets the value of the uniformDistribution property.
getUnit() - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Gets the value of the unit property.
getUnivariateStats() - Method in class weka.core.pmml.jaxbbindings.ModelStats: Gets the value of the univariateStats property.
getUnpruned() - Method in class weka.classifiers.rules.PART: Get the value of unpruned.
getUnpruned() - Method in class weka.classifiers.trees.J48: Get the value of unpruned.
getUnpruned() - Method in class weka.classifiers.trees.m5.M5Base: Get whether unpruned tree/rules are being generated
getUnpruned() - Method in class weka.classifiers.trees.m5.Rule: Get whether unpruned tree/rules are being generated
getUnsortedEigenVectors() - Method in class weka.attributeSelection.PrincipalComponents: Return the unsorted eigenvectors
getUpdateCount() - Method in class weka.core.converters.DatabaseConnection: Dewtermines if the current query retrieves a result set or updates a table
getUpdateIncrementalClassifier() - Method in class weka.gui.beans.Classifier: Get whether an incremental classifier will be updated on the incoming instance stream.
getUpdateIncrementalClassifier() - Method in class weka.knowledgeflow.steps.Classifier: Get whether to update an incremental classifier on an incoming instance stream
getUpdateWeightsOnly() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Gets whether only weights should be udpated.*
getUpper() - Method in class weka.core.pmml.jaxbbindings.UniformDistribution: Gets the value of the upper property.
getUpper() - Method in class weka.gui.experiment.RunNumberPanel: Gets the current upper run number.
getUpperBound() - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Get the upper bound of this range
getUpperBoundMinSupport() - Method in class weka.associations.Apriori: Get the value of upperBoundMinSupport.
getUpperBoundMinSupport() - Method in class weka.associations.FPGrowth: Get the value of upperBoundMinSupport.
getUpperCase() - Method in class weka.core.converters.DatabaseConnection: Check if the property checkUpperCaseNames in the DatabaseUtils file is set to true or false.
getUpperComparison() - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Get the upper comparison
getUpperNumericBound() - Method in class weka.core.Attribute: Returns the upper bound of a numeric attribute.
getUpperSize() - Method in class weka.experiment.LearningRateResultProducer: Get the value of UpperSize.
getUrl() - Method in interface weka.core.converters.DatabaseConverter
getUrl() - Method in class weka.core.converters.DatabaseLoader: Gets the URL
getUrl() - Method in class weka.core.converters.DatabaseSaver: Gets the database URL.
getURL() - Static method in class weka.core.Copyright: returns the URL of the owner
getURL() - Method in class weka.gui.DatabaseConnectionDialog: Returns URL from dialog
getURL(String, String) - Static method in class weka.gui.Loader: returns a URL for the given filename, can be NULL if it fails
getURL(String) - Method in class weka.gui.Loader: returns a URL for the given filename, can be NULL if it fails
getURL() - Method in class weka.gui.sql.ConnectionPanel: returns the current URL.
getURL() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the database URL that produced the table model
getURL() - Method in class weka.gui.sql.ResultSetTable: returns the database URL that produced the table model
getURL() - Method in class weka.gui.sql.SqlViewer: returns the database URL from the currently active tab in the ResultPanel, otherwise an empty string.
getURL() - Method in class weka.gui.sql.SqlViewerDialog: returns the chosen URL, if any.
getURLFileLoaders() - Static method in class weka.core.converters.ConverterResources: Returns the URL file loaders.
getURLFileLoaders() - Static method in class weka.core.converters.ConverterUtils: returns a vector with the classnames of all the URL file loaders.
getURLLoaderForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loader to use for this kind of extension, returns null if none can be found.
getURLLoaderForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loader to use for this kind of file, returns null if none can be found.
getURLLoaderForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loader to use for this kind of file, returns null if none can be found.
getURLLoadersForExtension(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loaders to use for this kind of extension.
getURLLoadersForFile(String) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loader to use for this kind of file.
getURLLoadersForFile(File) - Static method in class weka.core.converters.ConverterUtils: tries to determine the URL loaders to use for this kind of file.
getURLPackageInfo(URL) - Method in class weka.core.packageManagement.DefaultPackageManager: Get package information on the package at the given URL.
getURLPackageInfo(URL) - Method in class weka.core.packageManagement.PackageManager: Get package information on the package at the given URL.
getUsage() - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Gets the value of the usage property.
getUsageType() - Method in class weka.core.pmml.jaxbbindings.MiningField: Gets the value of the usageType property.
getUsageType() - Method in class weka.core.pmml.MiningFieldMetaInfo: Get the usage type of this field.
getUseADTree() - Method in class weka.classifiers.bayes.BayesNet: Method declaration
getUseAIC() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of useAIC.
getUseAIC() - Method in class weka.classifiers.trees.LMT: Get the value of useAIC.
getUseAIC() - Method in class weka.classifiers.trees.lmt.LogisticBase: Get the value of useAIC.
getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: get use the arc reversal operation
getUseArcReversal() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: get use the arc reversal operation
getUseAverage() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Get the value of UseAverage.
getUseBetterEncoding() - Method in class weka.filters.supervised.attribute.Discretize: Gets whether better encoding is to be used for MDL.
getUseBinNumbers() - Method in class weka.filters.supervised.attribute.Discretize: Gets whether bin numbers rather than ranges should be used for discretized attributes.
getUseBinNumbers() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets whether bin numbers rather than ranges should be used for discretized attributes.
getUseBlanks() - Method in class weka.gui.scripting.SyntaxDocument: Returns whether blanks are used instead of tabs.
getUseClassification() - Static method in class weka.gui.experiment.ExperimenterDefaults: whether classification or regression is used.
getUseConjugateGradientDescent() - Method in class weka.classifiers.functions.Logistic: Gets whether to use conjugate gradient descent rather than BFGS updates.
getUseCpuTime() - Method in class weka.core.Debug.Clock: returns whether the use of CPU is time is enabled/disabled (regardless whether the system supports it or not)
getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseCrossOver() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseCrossValidation() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of useCrossValidation.
getUseCustomDimensions() - Method in class weka.gui.visualize.JComponentWriter: whether custom dimensions are to used for the size of the image
getUsedAttributes() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns an array of the indices of the attributes used in the logistic model.
getUseDouble() - Method in class weka.core.converters.MatlabSaver: Returns whether double or single precision is used.
getUseDynamic() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get whether to execute dynamic commands
getUseEnvironmentPropertyEditors() - Method in class weka.gui.PropertySheetPanel: Get whether to use environment property editors for string and file properties
getUseEqualFrequency() - Method in class weka.classifiers.meta.RegressionByDiscretization: Get the value of UseEqualFrequency.
getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.Discretize: Get the value of UseEqualFrequency.
getUseEqualFrequency() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Get the value of UseEqualFrequency.
getUseEstimatedPriors() - Method in class weka.classifiers.meta.LogitBoost: Get whether resampling is turned on
getUseGUI() - Method in class weka.core.Memory: whether to display a dialog in case of a problem (= TRUE) or just print on stderr (= FALSE)
getUseIBk() - Method in class weka.classifiers.rules.DecisionTable: Gets whether IBk is being used instead of the majority class
getUseKernelEstimator() - Method in class weka.classifiers.bayes.NaiveBayes: Gets if kernel estimator is being used.
getUseKononenko() - Method in class weka.filters.supervised.attribute.Discretize: Gets whether Kononenko's MDL criterion is to be used.
getUseLaplace() - Method in class weka.classifiers.trees.J48: Get the value of useLaplace.
getUseLeastValues() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Gets whether to use values with least or most instances
getUseLowerOrder() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Gets whether lower-order terms are used.
getUseMDLcorrection() - Method in class weka.classifiers.rules.PART: Get the value of useMDLcorrection.
getUseMDLcorrection() - Method in class weka.classifiers.trees.J48: Get the value of useMDLcorrection.
getUseMissing() - Method in class weka.filters.unsupervised.attribute.AddNoise: Gets the flag if missing values are treated as extra values.
getUseMutation() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseMutation() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseNormalization() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns whether normalization is used.
getUseNormalizedEntropy() - Method in class weka.estimators.UnivariateMixtureEstimator
getUseORForMustContainList() - Method in class weka.associations.FPGrowth: Gets whether OR is to be used rather than AND when considering must contain lists.
getUsePairwiseCoupling() - Method in class weka.classifiers.meta.MultiClassClassifier: Gets whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.
getUsePercentageSplit() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get whether to perform a percentage split on the training data for evaluation
getUseProb() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
getUsePropertyIterator() - Method in class weka.experiment.Experiment: Gets whether the custom property iterator should be used.
getUsePruning() - Method in class weka.classifiers.rules.JRip: Gets whether pruning is performed
getUseQRDecomposition() - Method in class weka.classifiers.functions.LinearRegression: Get whether to use QR decomposition.
getUser() - Method in interface weka.core.converters.DatabaseConverter
getUser() - Method in class weka.core.converters.DatabaseLoader: Gets the user name
getUser() - Method in class weka.core.converters.DatabaseSaver: Gets the database user.
getUser() - Method in class weka.gui.sql.ConnectionPanel: returns the current User.
getUser() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the user that produced the table model
getUser() - Method in class weka.gui.sql.ResultSetTable: returns the user that produced the table model
getUser() - Method in class weka.gui.sql.SqlViewer: returns the user from the currently active tab in the ResultPanel, otherwise an empty string.
getUser() - Method in class weka.gui.sql.SqlViewerDialog: returns the chosen user, if any.
getUseRelativePath() - Method in class weka.core.converters.AbstractFileLoader: Gets whether relative paths are to be used
getUseRelativePath() - Method in class weka.core.converters.AbstractFileSaver: Gets whether relative paths are to be used
getUseRelativePath() - Method in interface weka.core.converters.FileSourcedConverter: Gets whether relative paths are to be used
getUseRelativePath() - Method in class weka.gui.beans.SerializedModelSaver: Get whether to use relative paths for the directory.
getUseRelativePaths() - Static method in class weka.gui.experiment.ExperimenterDefaults: whether relative paths are used by default.
getUseResampling() - Method in class weka.classifiers.meta.AdaBoostM1: Get whether resampling is turned on
getUseResampling() - Method in class weka.classifiers.meta.LogitBoost: Get whether resampling is turned on
getUsername() - Method in class weka.experiment.DatabaseUtils: Get the database username.
getUsername() - Method in class weka.gui.DatabaseConnectionDialog: Returns Username from dialog
getUserOptions() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns the options the user supplied for the kernel
getUserOptions() - Method in class weka.core.CheckOptionHandler: Gets the current user-supplied options (creates a copy)
getUserVisiblePerspectives() - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Get the list of perspectives that the user has specified should be visible in the application
getUseShortIdentifiers() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Get whether short identifiers are to be output.
getUseShortIDs() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Get whether short IDs are to be used.
getUseStars() - Method in class weka.core.Javadoc: whether the Javadoc is prefixed with "*"
getUseSupervisedDiscretization() - Method in class weka.classifiers.bayes.NaiveBayes: Get whether supervised discretization is to be used.
getUseTab() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns whether tab is used as separator.
getUseTabs() - Method in class weka.core.converters.MatlabSaver: Returns whether tabs are used instead of blanks.
getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
getUseTournamentSelection() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
getUseTraining() - Method in class weka.attributeSelection.ClassifierSubsetEval: Get if training data is to be used instead of hold out/test data
getUseTree() - Method in class weka.classifiers.trees.m5.Rule: get whether an m5 tree is being used rather than rules
getUseUnsmoothed() - Method in class weka.classifiers.trees.m5.M5Base: Get whether or not smoothing is being used
getUseWordFrequencies() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Get whether to use word frequencies rather than binary bag of words representation.
getUseWordFrequencies() - Method in class weka.classifiers.functions.SGDText: Get whether to use word frequencies rather than binary bag of words representation.
getV() - Method in class weka.core.matrix.EigenvalueDecomposition: Return the eigenvector matrix
getV() - Method in class weka.core.matrix.SingularValueDecomposition: Return the right singular vectors
getValidating() - Method in class weka.core.xml.XMLDocument: returns whether a validating parser is used.
getValidating() - Method in class weka.core.xml.XMLOptions: returns whether a validating parser is used.
getValidationSetSize() - Method in class weka.classifiers.functions.MultilayerPerceptron
getValidationThreshold() - Method in class weka.classifiers.functions.MultilayerPerceptron
getValue() - Method in class weka.core.expressionlanguage.common.Primitives.BooleanVariable
getValue() - Method in class weka.core.expressionlanguage.common.Primitives.DoubleVariable
getValue() - Method in class weka.core.expressionlanguage.common.Primitives.StringVariable
getValue() - Method in class weka.core.json.JSONNode: Returns the stored value.
getValue(Object) - Method in class weka.core.json.JSONNode: Returns the stored value.
getValue() - Method in class weka.core.pmml.FieldMetaInfo.Value
getValue() - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Category: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Coefficient: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Constant: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Decision: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.DerivedField: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.EventValues: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Extension: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.FieldValue: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Item: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.MatCell: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.OutputField: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.PairCounts: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.PCovCell: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.PPCell: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.ResultField: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.TargetValue: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.TargetValueCount: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.TimeValue: Gets the value of the value property.
getValue() - Method in class weka.core.pmml.jaxbbindings.Value: Gets the value of the value property.
getValue(Object, PropertyPath.Path) - Static method in class weka.core.PropertyPath: returns the value specified by the given path from the object
getValue(Object, String) - Static method in class weka.core.PropertyPath: returns the value specified by the given path from the object
getValue(TechnicalInformation.Field) - Method in class weka.core.TechnicalInformation: returns the value associated with the given field, or empty if field is not currently stored.
getValue() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Get the value of the new attribute.
getValue() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
getValue() - Method in class weka.gui.ColorEditor: Get the current color
getValue() - Method in class weka.gui.CostMatrixEditor: Gets the cost matrix that is being edited.
getValue() - Method in class weka.gui.EnvironmentField
getValue() - Method in class weka.gui.FileEnvironmentField
getValue() - Method in class weka.gui.GenericArrayEditor: Gets the current object array.
getValue() - Method in class weka.gui.GenericObjectEditor: Gets the current, configured object.
getValue() - Method in class weka.gui.HierarchyPropertyParser: Get the value of current node
getValue() - Method in class weka.gui.PasswordField
getValue() - Method in class weka.gui.SimpleDateFormatEditor: Gets the date format that is being edited.
getValue() - Method in class weka.gui.SortedTableModel.SortContainer: Returns the value to sort on.
getValueAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel: returns the value for the cell at columnIndex and rowIndex
getValueAt(int, int) - Method in class weka.gui.InteractiveTableModel
getValueAt(int, int) - Method in class weka.gui.SortedTableModel: Returns the value for the cell at columnIndex and rowIndex.
getValueAt(int, int) - Method in class weka.gui.sql.ResultSetTableModel: returns the value for the cell at columnindex and rowIndex.
getValueIndex() - Method in class weka.associations.NominalItem: Get the value index for this item.
getValueIndices() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Get the indices of the indicator values.
getValueName(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns value of a node
getValueRange() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Get the range containing the indicator values.
getValueReplacements() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
getValues(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns array of values of a node
getValues(int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns array of values of a node
getValues() - Method in class weka.core.pmml.jaxbbindings.DataField: Gets the value of the value property.
getValues() - Method in class weka.core.pmml.TargetMetaInfo: Get the values (discrete case only) for this Target.
getValues() - Method in class weka.core.pmml.VectorInstance: Get the Array of values encapsulated in this vector instance
getValues(InterquartileRange.ValueType) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the values for the specified type.
getValues() - Method in class weka.gui.visualize.VisualizePanelEvent
getValuesList() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: returns the range for each attribute as string
getVarbValues() - Method in class weka.core.Optimization: Get the variable values.
getVariable(String) - Method in class weka.core.expressionlanguage.common.NoVariables: Tries to fetch the variable.
getVariable(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Tries to fetch a declared variable
getVariable(String) - Method in class weka.core.expressionlanguage.common.VariableDeclarationsCompositor: Tries to fetch a variable from one of the combined declarations.
getVariable(String) - Method in interface weka.core.expressionlanguage.core.VariableDeclarations: Tries to fetch a variable
getVariable(String) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Tries to fetch a variable of an instance value
getVariable(String) - Method in class weka.core.expressionlanguage.weka.StatsHelper: Tries to fetch a Stats field
getVariableNames() - Method in class weka.core.Environment: Get the names of the variables (keys) stored in the internal map.
getVariables() - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer: Returns the set of variable names that can be initialized
getVariables() - Method in class weka.gui.SimpleCLIPanel: Returns the variables.
getVariableValue(String) - Method in class weka.core.Environment: Get the value for a particular variable.
getVariance() - Method in class weka.classifiers.BVDecompose: Get the calculated variance
getVariance() - Method in class weka.core.pmml.jaxbbindings.AnyDistribution: Gets the value of the variance property.
getVariance() - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution: Gets the value of the variance property.
getVarianceCovered() - Method in class weka.attributeSelection.PrincipalComponents: Gets the proportion of total variance to account for when retaining principal components
getVarianceCovered() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Gets the proportion of total variance to account for when retaining principal components.
getVarsInternalRep() - Method in class weka.knowledgeflow.steps.SetVariables: Get the variables to set (in internal representation)
getVector(String) - Method in class weka.core.pmml.VectorDictionary: Gets a vector from the dictionary corresponding to the supplied ID
getVectorDictionary(Element, MiningSchema) - Static method in class weka.core.pmml.VectorDictionary: Returns a new VectorDictionary constructed from the supplied XML container
getVectorFields() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Gets the value of the vectorFields property.
getVectorFields() - Method in class weka.core.pmml.VectorInstance: Get the mining fields that are indexed by this vector instance
getVectorId() - Method in class weka.core.pmml.jaxbbindings.SupportVector: Gets the value of the vectorId property.
getVectorInstance() - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Gets the value of the vectorInstance property.
getVectorizedFormat() - Method in class weka.core.DictionaryBuilder: Get the output format
getVectorOfAttrTypes() - Method in class weka.estimators.CheckEstimator.AttrTypes
getVerbose() - Method in class weka.associations.Apriori: Gets whether algorithm is run in verbose mode
getVerificationField() - Method in class weka.core.pmml.jaxbbindings.VerificationFields: Gets the value of the verificationField property.
getVerificationFields() - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Gets the value of the verificationFields property.
getVersion() - Method in class weka.core.pmml.jaxbbindings.Application: Gets the value of the version property.
getVersion() - Method in class weka.core.pmml.jaxbbindings.PMML: Gets the value of the version property.
getVersion() - Method in class weka.core.xml.XMLSerialization: returns the WEKA version with which the serialized object was created
getVersionComparison() - Method in class weka.core.packageManagement.VersionPackageConstraint
getViewerName() - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView: The name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.CostBenefitAnalysisInteractiveView: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.GraphViewerInteractiveView: Get the name of this viewr
getViewerName() - Method in class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView: Get the name of the viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView: Get the name of the viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Get the name of this viewer
getViewerName() - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Get the viewer name
getVisible() - Method in class weka.gui.treevisualizer.Node: Get the value of visible.
getVisibleColCount() - Method in class weka.experiment.ResultMatrix: returns the number of visible columns.
getVisiblePerspectives() - Method in class weka.gui.PerspectiveManager: Get a list of visible perspectives.
getVisibleRowCount() - Method in class weka.experiment.ResultMatrix: returns the number of visible rows.
getVisual() - Method in class weka.gui.beans.AbstractDataSink: Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.AbstractDataSource: Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.AbstractEvaluator: Get the visual
getVisual() - Method in class weka.gui.beans.AbstractTestSetProducer: Get the visual for this bean
getVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Get the visual for this bean
getVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer: Get the visual for this bean
getVisual() - Method in class weka.gui.beans.Appender: Get the visual representation
getVisual() - Method in class weka.gui.beans.Associator: Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.ClassAssigner
getVisual() - Method in class weka.gui.beans.Classifier: Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.ClassValuePicker
getVisual() - Method in class weka.gui.beans.Clusterer: Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.CostBenefitAnalysis
getVisual() - Method in class weka.gui.beans.DataVisualizer: Return the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.Filter: Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.FlowByExpression
getVisual() - Method in class weka.gui.beans.GraphViewer: Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.ImageSaver
getVisual() - Method in class weka.gui.beans.ImageViewer
getVisual() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.Join: Get the visual for this step
getVisual() - Method in class weka.gui.beans.MetaBean: Gets the visual appearance of this wrapper bean
getVisual() - Method in class weka.gui.beans.ModelPerformanceChart: Return the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.PredictionAppender: Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.SerializedModelSaver: Get the visual being used by this data source.
getVisual() - Method in class weka.gui.beans.Sorter: Get the visual representation
getVisual() - Method in class weka.gui.beans.StripChart: Get the visual appearance of this bean
getVisual() - Method in class weka.gui.beans.SubstringLabeler: Get the visual representation
getVisual() - Method in class weka.gui.beans.SubstringReplacer: Get the visual representation
getVisual() - Method in class weka.gui.beans.TextSaver
getVisual() - Method in class weka.gui.beans.TextViewer: Get the visual appearance of this bean
getVisual() - Method in interface weka.gui.beans.Visible: Get the visual representation
getVisualizeMenuItem(AssociationRules, String) - Method in interface weka.gui.visualize.plugins.AssociationRuleVisualizePlugin: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the association rules.
getVisualizeMenuItem(Instances) - Method in interface weka.gui.visualize.plugins.ErrorVisualizePlugin: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the classifier errors.
getVisualizeMenuItem(String, String) - Method in interface weka.gui.visualize.plugins.GraphVisualizePlugin: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the graph in XML BIF format.
getVisualizeMenuItem(String, String) - Method in interface weka.gui.visualize.plugins.TreeVisualizePlugin: Get a JMenu or JMenuItem which contain action listeners that perform the visualization of the tree in GraphViz's dotty format.
getVisualizeMenuItem(ArrayList<Prediction>, Attribute) - Method in interface weka.gui.visualize.plugins.VisualizePlugin: Get a JMenu or JMenuItem which contain action listeners that perform the visualization, using some but not necessarily all of the data.
getVoteFlag() - Method in class weka.datagenerators.classifiers.classification.RDG1: Gets the vote flag.
getWBias() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated bias according to the Webb definition
getWeight() - Method in class weka.core.pmml.jaxbbindings.Con1: Gets the value of the weight property.
getWeight() - Method in class weka.core.pmml.jaxbbindings.Item: Gets the value of the weight property.
getWeight() - Method in class weka.core.pmml.jaxbbindings.Segment: Gets the value of the weight property.
getWeight() - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Gets the value of the weight property.
getWeight() - Method in class weka.filters.unsupervised.attribute.Add: Get the weight of the attribute used.
getWeightByDistance() - Method in class weka.attributeSelection.ReliefFAttributeEval: Get whether nearest neighbours are being weighted by distance
getWeighted() - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Gets the value of the weighted property.
getWeighted() - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Gets the value of the weighted property.
getWeightField() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the weightField property.
getWeightingKernel() - Method in class weka.classifiers.lazy.LWL: Gets the kernel weighting method to use.
getWeights() - Method in class weka.classifiers.functions.neural.NeuralNode: call this function to get the weights array.
getWeights() - Method in class weka.classifiers.functions.SGD
getWeights() - Method in class weka.estimators.KernelEstimator: Return the weights of the kernels.
getWeights() - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Get weights
getWeights() - Method in class weka.gui.boundaryvisualizer.KDDataGenerator
getWeightThreshold() - Method in class weka.classifiers.meta.AdaBoostM1: Get the degree of weight thresholding
getWeightThreshold() - Method in class weka.classifiers.meta.LogitBoost: Get the degree of weight thresholding
getWeightTrimBeta() - Method in class weka.classifiers.functions.SimpleLogistic: Get the value of weightTrimBeta.
getWeightTrimBeta() - Method in class weka.classifiers.trees.LMT: Get the value of weightTrimBeta.
getWeightTrimBeta() - Method in class weka.classifiers.trees.lmt.LogisticBase: Get the value of weightTrimBeta.
getWekaClassloaderClasspathEntries() - Method in class weka.core.WekaPackageClassLoaderManager: Get the entries in the Weka class loader (i.e.
getWekaHome() - Static method in class weka.core.ResourceUtils: Returns the Weka home directory.
getWekaJFrame(String, Component) - Static method in class weka.core.Utils: Returns a JFrame with the given title.
getWekaPackageClassLoaderManager() - Static method in class weka.core.WekaPackageClassLoaderManager: Gets the singleton instance of the WekaPackageClassLoaderManager
getWidget(String) - Method in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar
getWidth() - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Gets the value of the width property.
getWidth() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the width property.
getWidth() - Method in class weka.core.pmml.jaxbbindings.Neuron: Gets the value of the width property.
getWidth() - Method in class weka.gui.beans.BeanInstance: Gets the width of this bean
getWindow(Class<?>) - Method in class weka.gui.Main: returns the first instance of the given window class, null if none can be found.
getWindow(String) - Method in class weka.gui.Main: returns the first window with the given title, null if none can be found.
getWindowList() - Method in class weka.gui.Main: returns all currently open frames.
getWindowSize() - Method in class weka.classifiers.lazy.IBk: Gets the maximum number of instances allowed in the training pool.
getWindowSize() - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Gets the value of the windowSize property.
getWithPrefix(String) - Method in class weka.core.Trie: returns all stored strings that match the given prefix
getWords() - Method in class weka.core.CheckScheme: returns the words used for assembling strings in a comma-separated list.
getWords() - Method in class weka.core.TestInstances: returns the words used for assembling strings in a comma-separated list.
getWordSeparators() - Method in class weka.core.CheckScheme: returns the word separators (chars) to use for assembling strings.
getWordSeparators() - Method in class weka.core.TestInstances: returns the word separators (chars) to use for assembling strings.
getWordsToKeep() - Method in class weka.core.converters.DictionarySaver: Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.
getWordsToKeep() - Method in class weka.core.DictionaryBuilder: Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.
getWordsToKeep() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Gets the number of words (per class if there is a class attribute assigned) to attempt to keep.
getWrappedAlgorithm() - Method in class weka.gui.beans.Associator: Returns the wrapped associator
getWrappedAlgorithm() - Method in class weka.gui.beans.Classifier: Returns the wrapped classifier
getWrappedAlgorithm() - Method in class weka.gui.beans.Clusterer: Returns the wrapped clusterer
getWrappedAlgorithm() - Method in class weka.gui.beans.Filter: Get the filter wrapped by this bean
getWrappedAlgorithm() - Method in class weka.gui.beans.Loader: Get the loader
getWrappedAlgorithm() - Method in class weka.gui.beans.Saver: Get the saver
getWrappedAlgorithm() - Method in interface weka.gui.beans.WekaWrapper: Get the algorithm
getWrappedAlgorithm() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.ASEvaluator: Get the class of Weka algorithm wrapped by this wrapper
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Get the class of the algorithm wrapped by this wrapper step (ASSearch in this case).
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Associator: Get the class of the algorithm being wrapped
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Classifier
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Clusterer: Get the class of the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.DataGenerator: Get the class of the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Filter: Get the class of the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Loader: Get the class of the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.Saver: Get the class of the wrapped algorithm
getWrappedAlgorithmClass() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get the class of the algorithm being wrapped
getWrappedRules() - Method in class weka.associations.FilteredAssociationRules: Get the wrapped AssociationRules object.
getWriteMode() - Method in class weka.core.converters.AbstractSaver: Gets the write mode.
getWriteMode() - Method in interface weka.core.converters.Saver: Gets the write mode
getWriter() - Method in class weka.core.converters.AbstractFileSaver: Gets the writer
getWriter(String) - Method in class weka.gui.visualize.PrintableComponent: returns the JComponentWriter associated with the given name, is null if not found.
getWriter(String) - Method in interface weka.gui.visualize.PrintableHandler: returns the JComponentWriter associated with the given name, is null if not found
getWriter(String) - Method in class weka.gui.visualize.PrintablePanel: returns the JComponentWriter associated with the given name, is null if not found
getWriters() - Method in class weka.gui.visualize.PrintableComponent: returns a Hashtable with the current available JComponentWriters in the save dialog.
getWriters() - Method in interface weka.gui.visualize.PrintableHandler: returns a Hashtable with the current available JComponentWriters in the save dialog.
getWriters() - Method in class weka.gui.visualize.PrintablePanel: returns a Hashtable with the current available JComponentWriters in the save dialog.
getWriteTitleString() - Method in class weka.knowledgeflow.steps.TextSaver: Get whether the title string will be written to the file
getWVariance() - Method in class weka.classifiers.BVDecomposeSegCVSub: Get the calculated variance according to the Webb definition
getX() - Method in class weka.classifiers.functions.neural.NeuralConnection
getX() - Method in class weka.gui.beans.BeanInstance: Gets the x coordinate of this bean
getX() - Method in class weka.gui.knowledgeflow.StepVisual: Get the x coordinate of this step on the graphical layout
getXAttName() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the name/index of the X axis attribute
getXCoordinates() - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Gets the value of the xCoordinates property.
getXCoordinates() - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Gets the value of the xCoordinates property.
getXindex() - Method in class weka.gui.visualize.PlotData2D: Get the currently set x index of the data
getXIndex() - Method in class weka.gui.visualize.VisualizePanel: Get the index of the attribute on the x axis
getXLabelFreq() - Method in class weka.gui.beans.StripChart: Get the frequency by which x axis values are printed
getXLabelFreq() - Method in class weka.knowledgeflow.steps.StripChart: Get the x label frequency
getXMLDocument() - Method in class weka.core.xml.XMLOptions: returns the handler of the XML document.
getXScale() - Method in class weka.gui.visualize.JComponentWriter: returns the scale factor for the x-axis
getXScale() - Method in class weka.gui.visualize.PrintableComponent: returns the scale factor for the x-axis.
getXScale() - Method in interface weka.gui.visualize.PrintableHandler: returns the scale factor for the x-axis
getXScale() - Method in class weka.gui.visualize.PrintablePanel: returns the scale factor for the x-axis
getY() - Method in class weka.classifiers.functions.neural.NeuralConnection
getY() - Method in class weka.gui.beans.BeanInstance: Gets the y coordinate of this bean
getY() - Method in class weka.gui.knowledgeflow.StepVisual: Get the y coordinate of this step on the graphical layout
getYAttName() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the name/index of the Y axis attribute
getYCoordinates() - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Gets the value of the yCoordinates property.
getYCoordinates() - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Gets the value of the yCoordinates property.
getYindex() - Method in class weka.gui.visualize.PlotData2D: Get the currently set y index of the data
getYIndex() - Method in class weka.gui.visualize.VisualizePanel: Get the index of the attribute on the y axis
getYScale() - Method in class weka.gui.visualize.JComponentWriter: returns the scale factor for the y-axis
getYScale() - Method in class weka.gui.visualize.PrintableComponent: returns the scale factor for the y-axis.
getYScale() - Method in interface weka.gui.visualize.PrintableHandler: returns the scale factor for the y-axis
getYScale() - Method in class weka.gui.visualize.PrintablePanel: returns the scale factor for the y-axis
getZeroThreshold() - Method in class weka.core.pmml.jaxbbindings.VerificationField: Gets the value of the zeroThreshold property.
getZMax() - Method in class weka.classifiers.meta.LogitBoost: Get the Z max threshold on the responses
getZoomSetting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
getZoomSetting() - Method in class weka.gui.knowledgeflow.VisibleLayout: Get the current zoom setting for this layout
gini(Map<String, WeightMass>) - Static method in class weka.classifiers.trees.ht.GiniSplitMetric: Return the gini metric computed from the supplied distribution
GINI_SPLIT - Static variable in class weka.classifiers.trees.HoeffdingTree
GiniSplitMetric - Class in weka.classifiers.trees.ht: Implements the gini splitting criterion
GiniSplitMetric() - Constructor for class weka.classifiers.trees.ht.GiniSplitMetric
globalBlendTipText() - Method in class weka.classifiers.lazy.KStar: Returns the tip text for this property
globalInfo() - Method in class weka.associations.Apriori: Returns a string describing this associator
globalInfo() - Method in class weka.associations.FilteredAssociator: Returns a string describing this Associator
globalInfo() - Method in class weka.associations.FPGrowth: Returns a string describing this associator
globalInfo() - Method in class weka.attributeSelection.BestFirst: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.CfsSubsetEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns a string describing this attribute evaluator.
globalInfo() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.CorrelationAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.GainRatioAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.GreedyStepwise: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.PrincipalComponents: Returns a string describing this attribute transformer
globalInfo() - Method in class weka.attributeSelection.Ranker: Returns a string describing this search method
globalInfo() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.bayes.BayesNet: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayes: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.NaiveBayesUpdateable: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.bayes.net.BIFReader: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: This will return a string describing the class.
globalInfo() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.search.ci.CISearchAlgorithm: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.search.fixed.NaiveBayes: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.K2: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.global.TAN: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.K2: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: This will return a string describing the search algorithm.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.bayes.net.search.local.TAN: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.BVDecompose: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns a string describing this object
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.HTML: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.InMemory: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.Null: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.PlainText: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.evaluation.output.prediction.XML: Returns a string describing the output generator.
globalInfo() - Method in class weka.classifiers.functions.GaussianProcesses: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.LinearRegression: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.Logistic: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.MultilayerPerceptron: This will return a string describing the classifier.
globalInfo() - Method in class weka.classifiers.functions.SGD: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SGDText: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.functions.SimpleLogistic: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SMO: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.SMOreg: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.Puk: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.RBFKernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns a string describing the object
globalInfo() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns a string describing the kernel
globalInfo() - Method in class weka.classifiers.functions.VotedPerceptron: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.lazy.IBk: Returns a string describing classifier.
globalInfo() - Method in class weka.classifiers.lazy.KStar: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.lazy.LWL: Returns a string describing classifier.
globalInfo() - Method in class weka.classifiers.meta.AdaBoostM1: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.AdditiveRegression: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns a string describing this search method
globalInfo() - Method in class weka.classifiers.meta.Bagging: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.ClassificationViaRegression: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.CostSensitiveClassifier
globalInfo() - Method in class weka.classifiers.meta.CVParameterSelection: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.meta.FilteredClassifier: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.LogitBoost: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.MultiClassClassifier
globalInfo() - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable
globalInfo() - Method in class weka.classifiers.meta.MultiScheme: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.RandomCommittee: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.meta.RandomSubSpace: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.Stacking: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.Vote: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns a string describing this classifier
globalInfo() - Method in class weka.classifiers.misc.SerializedClassifier: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.DecisionTable: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.JRip: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.M5Rules: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.OneR: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.PART: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.rules.ZeroR: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.DecisionStump: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.HoeffdingTree: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.J48: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.LMT: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.M5P: returns information about the classifier
globalInfo() - Method in class weka.classifiers.trees.RandomForest: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.RandomTree: Returns a string describing classifier
globalInfo() - Method in class weka.classifiers.trees.REPTree: Returns a string describing classifier
globalInfo() - Method in class weka.clusterers.Canopy: Returns a string describing this clusterer.
globalInfo() - Method in class weka.clusterers.Cobweb: Returns a string describing this clusterer
globalInfo() - Method in class weka.clusterers.EM: Returns a string describing this clusterer
globalInfo() - Method in class weka.clusterers.FarthestFirst: Returns a string describing this clusterer
globalInfo() - Method in class weka.clusterers.FilteredClusterer: Returns a string describing this clusterer.
globalInfo() - Method in class weka.clusterers.HierarchicalClusterer: This will return a string describing the clusterer.
globalInfo() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns a string describing classifier
globalInfo() - Method in class weka.clusterers.SimpleKMeans: Returns a string describing this clusterer.
globalInfo() - Method in class weka.core.ChebyshevDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.converters.ArffLoader: Returns a string describing this Loader
globalInfo() - Method in class weka.core.converters.ArffSaver: Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.C45Loader: Returns a string describing this attribute evaluator
globalInfo() - Method in class weka.core.converters.C45Saver: Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.CSVLoader: Returns a string describing this attribute evaluator.
globalInfo() - Method in class weka.core.converters.CSVSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.DatabaseLoader: Returns a string describing this Loader
globalInfo() - Method in class weka.core.converters.DatabaseSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.DictionarySaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.JSONLoader: Returns a string describing this Loader.
globalInfo() - Method in class weka.core.converters.JSONSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.LibSVMLoader: Returns a string describing this Loader.
globalInfo() - Method in class weka.core.converters.LibSVMSaver: Returns a string describing this Saver
globalInfo() - Method in class weka.core.converters.MatlabLoader: Returns a string describing this Loader.
globalInfo() - Method in class weka.core.converters.MatlabSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.SerializedInstancesLoader: Returns a string describing this object
globalInfo() - Method in class weka.core.converters.SerializedInstancesSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.SVMLightLoader: Returns a string describing this Loader.
globalInfo() - Method in class weka.core.converters.SVMLightSaver: Returns a string describing this Saver.
globalInfo() - Method in class weka.core.converters.TextDirectoryLoader: Returns a string describing this loader
globalInfo() - Method in class weka.core.converters.XRFFLoader: Returns a string describing this Loader
globalInfo() - Method in class weka.core.converters.XRFFSaver: Returns a string describing this Saver
globalInfo() - Method in class weka.core.EuclideanDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.FilteredDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.ManhattanDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.MinkowskiDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.neighboursearch.BallTree: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.BottomUpConstructor: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Returns a string describing this object.
globalInfo() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.CoverTree: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns a string describing this object.
globalInfo() - Method in class weka.core.neighboursearch.KDTree: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.LinearNNSearch: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns a string describing this nearest neighbour search algorithm.
globalInfo() - Method in class weka.core.NormalizableDistance: Returns a string describing this object.
globalInfo() - Method in class weka.core.stemmers.IteratedLovinsStemmer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.stemmers.LovinsStemmer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.stemmers.NullStemmer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.stemmers.SnowballStemmer: Returns a string describing the stemmer.
globalInfo() - Method in class weka.core.stopwords.AbstractStopwords: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.core.stopwords.MultiStopwords
globalInfo() - Method in class weka.core.stopwords.Null: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.core.stopwords.Rainbow: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.core.stopwords.RegExpFromFile: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.core.stopwords.WordsFromFile: Returns a string describing the stopwords scheme.
globalInfo() - Method in class weka.core.tokenizers.AlphabeticTokenizer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns a string describing the tokenizer
globalInfo() - Method in class weka.core.tokenizers.NGramTokenizer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.tokenizers.Tokenizer: Returns a string describing the stemmer
globalInfo() - Method in class weka.core.tokenizers.WordTokenizer: Returns a string describing the stemmer
globalInfo() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.classification.LED24: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.ClusterDefinition: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns a string describing this data generator.
globalInfo() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns a string describing this data generator.
globalInfo() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns a string describing the estimator.
globalInfo() - Method in class weka.estimators.UnivariateKernelEstimator: Returns a string describing the estimator.
globalInfo() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns a string describing the estimator.
globalInfo() - Method in class weka.estimators.UnivariateNormalEstimator: Returns a string describing the estimator.
globalInfo() - Method in class weka.experiment.AveragingResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.CrossValidationResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.CrossValidationSplitResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.CSVResultListener: Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.DatabaseResultListener: Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.DatabaseResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns a string describing this result producer.
globalInfo() - Method in class weka.experiment.InstancesResultListener: Returns a string describing this result listener
globalInfo() - Method in class weka.experiment.LearningRateResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.RandomSplitResultProducer: Returns a string describing this result producer
globalInfo() - Method in class weka.experiment.RegressionSplitEvaluator: Returns a string describing this split evaluator
globalInfo() - Method in class weka.experiment.ResultMatrix: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixCSV: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixGnuPlot: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixHTML: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixLatex: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixPlainText: Returns a string describing the matrix.
globalInfo() - Method in class weka.experiment.ResultMatrixSignificance: Returns a string describing the matrix.
globalInfo() - Method in class weka.filters.AllFilter: Returns a string describing this filter
globalInfo() - Method in class weka.filters.MultiFilter: Returns a string describing this filter
globalInfo() - Method in class weka.filters.RenameRelation: Returns a string describing this filter
globalInfo() - Method in class weka.filters.SimpleFilter: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.supervised.attribute.AddClassification: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Global help info for this method
globalInfo() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.Discretize: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.attribute.PartitionMembership: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.instance.ClassBalancer: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.supervised.instance.Resample: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns a string describing this filter
globalInfo() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Add: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddID: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Center: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Copy: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector
globalInfo() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
globalInfo() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.Obfuscate: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.Remove: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns a string describing this classifier.
globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Global help info
globalInfo() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.Standardize: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.attribute.SwapValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta: Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate: Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.attribute.Transpose: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.Randomize: Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Returns a string describing this filter.
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.Resample: Returns a string describing this classifier
globalInfo() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.SparseToNonSparse: Returns a string describing this filter
globalInfo() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns a string describing this filter.
globalInfo() - Method in class weka.gui.beans.Associator: Global info (if it exists) for the wrapped classifier
globalInfo() - Method in class weka.gui.beans.AttributeSummarizer: Global info for this bean
globalInfo() - Method in class weka.gui.beans.ClassAssigner: Global info for this bean
globalInfo() - Method in class weka.gui.beans.Classifier: Global info (if it exists) for the wrapped classifier
globalInfo() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Global info for this bean
globalInfo() - Method in class weka.gui.beans.ClassValuePicker: Global info for this bean
globalInfo() - Method in class weka.gui.beans.Clusterer: Global info (if it exists) for the wrapped classifier
globalInfo() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Global info for this bean
globalInfo() - Method in class weka.gui.beans.CostBenefitAnalysis: Global info for this bean
globalInfo() - Method in class weka.gui.beans.CrossValidationFoldMaker: Global info for this bean
globalInfo() - Method in class weka.gui.beans.DataVisualizer: Global info for this bean
globalInfo() - Method in class weka.gui.beans.Filter: Global info (if it exists) for the wrapped filter
globalInfo() - Method in class weka.gui.beans.FlowByExpression
globalInfo() - Method in class weka.gui.beans.GraphViewer: Global info for this bean
globalInfo() - Method in class weka.gui.beans.ImageSaver: Global info for this bean
globalInfo() - Method in class weka.gui.beans.ImageViewer: Global info for this bean
globalInfo() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Global info for this bean
globalInfo() - Method in class weka.gui.beans.Join: Global info for the method
globalInfo() - Method in class weka.gui.beans.Loader: Global info (if it exists) for the wrapped loader
globalInfo() - Method in class weka.gui.beans.ModelPerformanceChart: Global info for this bean
globalInfo() - Method in class weka.gui.beans.PredictionAppender: Global description of this bean
globalInfo() - Method in class weka.gui.beans.Saver: Global info (if it exists) for the wrapped loader
globalInfo() - Method in class weka.gui.beans.ScatterPlotMatrix: Global info for this bean
globalInfo() - Method in class weka.gui.beans.SerializedModelSaver: Global info for this bean.
globalInfo() - Method in class weka.gui.beans.Sorter: Help information suitable for displaying in the GUI.
globalInfo() - Method in class weka.gui.beans.StripChart: Global info for this bean
globalInfo() - Method in class weka.gui.beans.SubstringLabeler: Help information suitable for displaying in the GUI.
globalInfo() - Method in class weka.gui.beans.SubstringReplacer: About information
globalInfo() - Method in class weka.gui.beans.TestSetMaker: Global info for this bean
globalInfo() - Method in class weka.gui.beans.TextSaver: Global info for this bean
globalInfo() - Method in class weka.gui.beans.TextViewer: Global info for this bean
globalInfo() - Method in class weka.gui.beans.TrainingSetMaker: Global info for this bean
globalInfo() - Method in class weka.gui.beans.TrainTestSplitMaker: Global info for this bean
globalInfo() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Returns a string describing this tool
globalInfo() - Method in class weka.knowledgeflow.steps.BaseStep: Attempt to get default "about" information for this step by grabbing the toolTip from the KFStep annotation.
globalInfo() - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Get global "help" info.
GLOBALINFO_ENDTAG - Static variable in class weka.core.GlobalInfoJavadoc: the end comment tag for inserting the generated Javadoc
GLOBALINFO_METHOD - Static variable in class weka.core.GlobalInfoJavadoc: the globalInfo method name
GLOBALINFO_STARTTAG - Static variable in class weka.core.GlobalInfoJavadoc: the start comment tag for inserting the generated Javadoc
GlobalInfoJavadoc - Class in weka.core: Generates Javadoc comments from the class's globalInfo method.
GlobalInfoJavadoc() - Constructor for class weka.core.GlobalInfoJavadoc: default constructor
GlobalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses cross validation to estimate classification accuracy.
GlobalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
goDown(String) - Method in class weka.gui.HierarchyPropertyParser: Go to a certain node of the tree down from the current node according to the specified relative path.
GOECustomizer - Interface in weka.gui.beans: Extends BeanCustomizer.
GOEPanel() - Constructor for class weka.gui.GenericObjectEditor.GOEPanel: Creates the GUI editor component.
GOEStepEditorDialog - Class in weka.gui.knowledgeflow: A step editor dialog that uses the GOE mechanism to provide property editors.
GOEStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.GOEStepEditorDialog: Constructor
GOETreeNode() - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode: Creates a tree node that has no parent and no children, but which allows children.
GOETreeNode(Object) - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode: Creates a tree node with no parent, no children, but which allows children, and initializes it with the specified user object.
GOETreeNode(Object, boolean) - Constructor for class weka.gui.GenericObjectEditor.GOETreeNode: Creates a tree node with no parent, no children, initialized with the specified user object, and that allows children only if specified.
goTo(String) - Method in class weka.gui.HierarchyPropertyParser: Go to a certain node of the tree according to the specified path Note that the path must be absolute path from the root.
goToChild(String) - Method in class weka.gui.HierarchyPropertyParser: Go to one child node from the current position in the tree according to the given value
If the child node with the given value cannot be found it returns false, true otherwise.
goToChild(int) - Method in class weka.gui.HierarchyPropertyParser: Go to one child node from the current position in the tree according to the given position
goToParent() - Method in class weka.gui.HierarchyPropertyParser: Go to the parent from the current position in the tree If the current position is the root, it stays there and does not move
goToRoot() - Method in class weka.gui.HierarchyPropertyParser: Go to the root of the tree
GPCIgnore - Annotation Type in weka.gui: Marker annotation.
gr(double, double) - Static method in class weka.core.Utils: Tests if a is greater than b.
gracePeriodTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
graph(FPGrowth.FPTreeRoot) - Method in class weka.associations.FPGrowth: Assemble a dot graph representation of the FP-tree.
graph() - Method in class weka.classifiers.bayes.BayesNet: Returns a BayesNet graph in XMLBIF ver 0.3 format.
graph() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.CVParameterSelection: Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.meta.FilteredClassifier: Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns graph describing the classifier (if possible).
graph() - Method in class weka.classifiers.pmml.consumer.TreeModel
graph() - Method in class weka.classifiers.trees.HoeffdingTree
graph() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.J48: Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.LMT: Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns graph describing the tree.
graph(StringBuffer) - Method in class weka.classifiers.trees.m5.RuleNode: Assign a unique identifier to each node in the tree and then calls graphTree
graph() - Method in class weka.classifiers.trees.M5P: Return a dot style String describing the tree.
graph() - Method in class weka.classifiers.trees.RandomTree: Returns graph describing the tree.
graph() - Method in class weka.classifiers.trees.REPTree: Outputs the decision tree as a graph
graph() - Method in class weka.clusterers.Cobweb: Generates the graph string of the Cobweb tree
graph() - Method in class weka.clusterers.FilteredClusterer: Returns graph describing the clusterer (if possible).
graph() - Method in class weka.clusterers.HierarchicalClusterer
graph() - Method in interface weka.core.Drawable: Returns a string that describes a graph representing the object.
GraphConstants - Interface in weka.gui.graphvisualizer: GraphConstants.java
GraphEdge - Class in weka.gui.graphvisualizer: This class represents an edge in the graph
GraphEdge(int, int, int) - Constructor for class weka.gui.graphvisualizer.GraphEdge
GraphEdge(int, int, int, String, String) - Constructor for class weka.gui.graphvisualizer.GraphEdge
GraphEvent - Class in weka.gui.beans: Event for graphs
GraphEvent(Object, String, String, int) - Constructor for class weka.gui.beans.GraphEvent: Creates a new GraphEvent instance.
GraphicalEnvironmentCommandHandler - Interface in weka.gui.knowledgeflow: Interface for graphical command handlers
GraphListener - Interface in weka.gui.beans: Describe interface TextListener here.
GraphNode - Class in weka.gui.graphvisualizer: This class represents a node in the Graph.
GraphNode(String, String) - Constructor for class weka.gui.graphvisualizer.GraphNode: Constructor
GraphNode(String, String, int) - Constructor for class weka.gui.graphvisualizer.GraphNode: Constructor
graphTree(StringBuffer) - Method in class weka.classifiers.trees.ht.HNode
graphTree(StringBuffer) - Method in class weka.classifiers.trees.ht.SplitNode
graphType() - Method in class weka.classifiers.bayes.BayesNet: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.CVParameterSelection: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.pmml.consumer.TreeModel
graphType() - Method in class weka.classifiers.trees.HoeffdingTree
graphType() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.J48: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.LMT: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.M5P: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.RandomTree: Returns the type of graph this classifier represents.
graphType() - Method in class weka.classifiers.trees.REPTree: Returns the type of graph this classifier represents.
graphType() - Method in class weka.clusterers.Cobweb: Returns the type of graphs this class represents
graphType() - Method in class weka.clusterers.FilteredClusterer: Returns the type of graph this clusterer represents.
graphType() - Method in class weka.clusterers.HierarchicalClusterer
graphType() - Method in interface weka.core.Drawable: Returns the type of graph representing the object.
GraphViewer - Class in weka.gui.beans: A bean encapsulating weka.gui.treevisualize.TreeVisualizer
GraphViewer() - Constructor for class weka.gui.beans.GraphViewer
GraphViewer - Class in weka.knowledgeflow.steps: Step for collecting and visualizing graph output from Drawable schemes.
GraphViewer() - Constructor for class weka.knowledgeflow.steps.GraphViewer
GraphViewerBeanInfo - Class in weka.gui.beans: Bean info class for the graph viewer
GraphViewerBeanInfo() - Constructor for class weka.gui.beans.GraphViewerBeanInfo
GraphViewerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the GraphViewer step.
GraphViewerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.GraphViewerInteractiveView
GraphVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize graphs in the explorer.
GraphVisualizer - Class in weka.gui.graphvisualizer: This class displays the graph we want to visualize.
GraphVisualizer() - Constructor for class weka.gui.graphvisualizer.GraphVisualizer: Constructor
Sets up the gui and initializes all the other previously uninitialized variables.
greaterEqual(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '>=' greater equal operator
greaterThan(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '>' greater than operator
GreedyStepwise - Class in weka.attributeSelection: GreedyStepwise :

Performs a greedy forward or backward search through the space of attribute subsets.
GreedyStepwise() - Constructor for class weka.attributeSelection.GreedyStepwise: Constructor
GRID - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: Constant set for choice of pattern.
GRID_COLOR - Static variable in class weka.knowledgeflow.KFDefaults
GRID_COLOR_KEY - Static variable in class weka.knowledgeflow.KFDefaults
GRID_SPACING - Static variable in class weka.knowledgeflow.KFDefaults
GRID_SPACING_KEY - Static variable in class weka.knowledgeflow.KFDefaults
Groovy - Class in weka.core.scripting: A helper class for Groovy.
Groovy() - Constructor for class weka.core.scripting.Groovy: default constructor, tries to instantiate a Groovy classloader.
GroovyPanel - Class in weka.gui.scripting: A scripting panel for Groovy.
GroovyPanel() - Constructor for class weka.gui.scripting.GroovyPanel
GroovyScript - Class in weka.gui.scripting: Represents a Groovy script.
GroovyScript() - Constructor for class weka.gui.scripting.GroovyScript: Initializes the script.
GroovyScript(Document) - Constructor for class weka.gui.scripting.GroovyScript: Initializes the script.
GroovyScript(Document, File) - Constructor for class weka.gui.scripting.GroovyScript: Initializes the script.
GroovyScript.GroovyThread - Class in weka.gui.scripting: Executes a Groovy script in a thread.
GroovyThread(Script, String[]) - Constructor for class weka.gui.scripting.GroovyScript.GroovyThread: Initializes the thread.
grOrEq(double, double) - Static method in class weka.core.Utils: Tests if a is greater or equal to b.
grouping(boolean) - Method in class weka.core.matrix.FlexibleDecimalFormat
grow(Instances) - Method in class weka.classifiers.rules.JRip.RipperRule: Build one rule using the growing data
grow(Instances) - Method in class weka.classifiers.rules.Rule: Build this rule
GT - Static variable in interface weka.core.expressionlanguage.parser.sym
GUI - Class in weka.classifiers.bayes.net: GUI interface to Bayesian Networks.
GUI() - Constructor for class weka.classifiers.bayes.net.GUI: Constructor
Sets up the gui and initializes all the other previously uninitialized variables.
GUI_MDI - Static variable in class weka.gui.Main: displays the GUI as MDI.
GUI_SDI - Static variable in class weka.gui.Main: displays the GUI as SDI.
GUIApplication - Interface in weka.gui: Interface to a GUIApplication that can have multiple "perspectives" and provide application-level and perspective-level settings.
GUIChooser - Class in weka.gui: Launcher class for the Weka GUIChooser.
GUIChooser() - Constructor for class weka.gui.GUIChooser
GUIChooser.GUIChooserMenuPlugin - Interface in weka.gui: Interface for plugin components that can be accessed from either the Visualization or Tools menu.
GUIChooser.GUIChooserMenuPlugin.Menu - Enum in weka.gui: Enum listing possible menus that plugins can appear in
GUIChooserApp - Class in weka.gui: The main class for the Weka GUIChooser.
GUIChooserApp() - Constructor for class weka.gui.GUIChooserApp: Creates the experiment environment gui with no initial experiment
GUIChooserApp.ChildFrameSDI - Class in weka.gui: Specialized JFrame class.
GUIChooserApp.GUIChooserDefaults - Class in weka.gui: Inner class for defaults
GUIChooserDefaults() - Constructor for class weka.gui.GUIChooserApp.GUIChooserDefaults: Constructor
GUIEDITORS_PROPERTY_FILE - Static variable in class weka.gui.GenericObjectEditor: the properties files containing the class/editor mappings.
GUITipText() - Method in class weka.classifiers.functions.MultilayerPerceptron

H

handles(Capabilities.Capability) - Method in class weka.core.Capabilities: returns true if the classifier handler has the specified capability
handles(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: returns true if the given capability can be handled.
hasAdditional() - Method in class weka.core.TechnicalInformation: returns true if there are further technical informations stored in this
hasAdditional() - Method in class weka.gui.scripting.event.ScriptExecutionEvent: Returns whether additional information is available.
hasAntds() - Method in class weka.classifiers.rules.JRip.RipperRule: Whether this rule has antecedents, i.e.
hasAntds() - Method in class weka.classifiers.rules.Rule: Whether this rule has antecedents, i.e.
hasBeenLoaded(Package) - Static method in class weka.core.WekaPackageManager: Check to see if the named package has been loaded successfully
hasChild(String) - Method in class weka.core.json.JSONNode: Checks whether the node has a child with the given name.
hasClasspathProblems() - Method in class weka.core.CheckScheme: returns TRUE if the classifier returned a "not in classpath" Exception
hasClasspathProblems() - Method in class weka.estimators.CheckEstimator: returns TRUE if the estimator returned a "not in classpath" Exception
hasCustomizer() - Method in class weka.gui.PropertySheetPanel: Returns true if the object being edited has a customizer
hasDependencies() - Method in class weka.core.Capabilities: Checks whether there are any dependencies at all
hasDependency(Capabilities.Capability) - Method in class weka.core.Capabilities: returns true if the classifier handler has a dependency for the specified capability
hasEmptyRow() - Method in class weka.gui.InteractiveTableModel: Returns true if the model has an empty row
hash - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: attribute value hash code
hashCode() - Method in class weka.associations.BinaryItem
hashCode() - Method in class weka.associations.Item
hashCode() - Method in class weka.associations.ItemSet: Produces a hash code for a item set.
hashCode() - Method in class weka.classifiers.rules.DecisionTableHashKey: Calculates a hash code
hashCode() - Method in class weka.core.Attribute: Returns a hash code for this attribute based on its name.
hashCode() - Method in class weka.core.SerializedObject: Returns a hashcode for this object.
hashCode() - Method in class weka.core.Settings.SettingKey: Hashcode based on the key
hashCode() - Method in class weka.core.Trie: Returns the hash code value for this collection.
hasIncomingBatchInstances() - Method in class weka.gui.beans.Classifier: Returns true if this classifier has an incoming connection that is a batch set of instances
hasIncomingBatchInstances() - Method in class weka.gui.beans.Clusterer: Returns true if this clusterer has an incoming connection that is a batch set of instances
hasIncomingStreamInstances() - Method in class weka.gui.beans.Classifier: Returns true if this classifier has an incoming connection that is an instance stream
hasIndex() - Method in class weka.core.PropertyPath.PathElement: returns whether the property is an index-based one
hasInstanceWeights(Instances) - Static method in class weka.core.ResampleUtils: Checks whether there are any instance weights other than 1.0 set.
hasInterface(String, String) - Static method in class weka.core.InheritanceUtils: Checks whether the given class implements the given interface.
hasInterface(Class<?>, Class<?>) - Static method in class weka.core.InheritanceUtils: Checks whether the given class implements the given interface.
hasMacro(String) - Method in class weka.core.expressionlanguage.common.IfElseMacro: Whether the macro is declared
hasMacro(String) - Method in class weka.core.expressionlanguage.common.JavaMacro: Whether the macro declarations contains the macro
hasMacro(String) - Method in class weka.core.expressionlanguage.common.MacroDeclarationsCompositor: Whether the macro is contained in one of the combined declarations.
hasMacro(String) - Method in class weka.core.expressionlanguage.common.MathFunctions: Whether the macro is declared
hasMacro(String) - Method in class weka.core.expressionlanguage.common.NoMacros: Whether the macro is declared.
hasMacro(String) - Method in interface weka.core.expressionlanguage.core.MacroDeclarations: Whether the macro is declared
hasMacro(String) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Whether the given macro is declared
hasMaxRows() - Method in class weka.gui.sql.ResultSetHelper: whether a limit on the rows to retrieve was set.
hasMissingValue() - Method in class weka.core.AbstractInstance: Tests whether an instance has a missing value.
hasMissingValue() - Method in interface weka.core.Instance: Tests whether an instance has a missing value.
hasModels() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns true if the logistic regression model at this node has changed compared to the one at the parent node.
hasMoreElements(Instances) - Method in class weka.core.converters.ConverterUtils.DataSource: returns whether there are more Instance objects in the data.
hasMoreElements() - Method in class weka.core.tokenizers.AlphabeticTokenizer: returns whether there are more elements still
hasMoreElements() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: returns true if there's more elements available
hasMoreElements() - Method in class weka.core.tokenizers.NGramTokenizer: returns true if there's more elements available
hasMoreElements() - Method in class weka.core.tokenizers.Tokenizer: Tests if this enumeration contains more elements.
hasMoreElements() - Method in class weka.core.tokenizers.WordTokenizer: Tests if this enumeration contains more elements.
hasMoreElements() - Method in class weka.core.WekaEnumeration: Tests if there are any more elements to enumerate.
hasMoreIterations() - Method in class weka.experiment.Experiment: Returns true if there are more iterations to carry out in the experiment.
hasNext() - Method in class weka.core.Trie.TrieIterator: Returns true if the iteration has more elements.
hasResult() - Method in class weka.gui.sql.event.QueryExecuteEvent: whether a ResultSet was produced, e.g.
hasResultDataOfType(String) - Method in class weka.knowledgeflow.JobEnvironment: Returns true if the results contain data of a particular connection type
hasSetting(String, String) - Method in class weka.core.Settings: Returns true if a given setting has a value
hasSettings(String) - Method in class weka.core.Settings: Returns true if there are settings available for a given ID
hasTargetMetaData() - Method in class weka.core.pmml.MiningSchema: Returns true if there is Target meta data.
hasThirdPartyClass(String) - Method in class weka.core.WekaPackageLibIsolatingClassLoader: Returns true if this classloader is covering the named third-party class
hasUID(String) - Static method in class weka.core.SerializationHelper: checks whether the given class contains a serialVersionUID.
hasUID(Class<?>) - Static method in class weka.core.SerializationHelper: checks whether the given class contains a serialVersionUID.
hasVariable(String) - Method in class weka.core.expressionlanguage.common.NoVariables: Whether the variable is declared.
hasVariable(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations: Whether the variable is declared
hasVariable(String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer: Returns whether the SimpleVariableDeclarations.VariableInitializer contains the variable
hasVariable(String) - Method in class weka.core.expressionlanguage.common.VariableDeclarationsCompositor: Whether the variable is contained in one of the combined declarations.
hasVariable(String) - Method in interface weka.core.expressionlanguage.core.VariableDeclarations: Whether the variable is declared
hasVariable(String) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Returns whether the variable is declared
hasVariable(String) - Method in class weka.core.expressionlanguage.weka.StatsHelper: Returns whether the variable is declared
hasZeropoint() - Method in class weka.core.Attribute: Returns whether the attribute has a zeropoint and may be added meaningfully.
HEADER - Static variable in class weka.core.json.JSONInstances: the header section.
Header - Class in weka.core.pmml.jaxbbindings: Java class for Header element declaration.
Header() - Constructor for class weka.core.pmml.jaxbbindings.Header
HEADER - Static variable in class weka.core.RepositoryIndexGenerator
header(int) - Method in class weka.experiment.PairedTTester: Creates a "header" string describing the current resultsets.
header(int) - Method in interface weka.experiment.Tester: Creates a "header" string describing the current resultsets.
headerKeys() - Method in class weka.experiment.ResultMatrix: returns an enumeration of the header keys.
HeadlessEventCollector - Interface in weka.gui.beans: Interface for Knowledge Flow components that (typically) provide an interactive graphical visualization to implement.
HEIGHT - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: default height
HEIGHT - Static variable in class weka.gui.sql.SqlViewer: the height property in the history file.
Help - Class in weka.gui.simplecli: Outputs help for a command or for all.
Help() - Constructor for class weka.gui.simplecli.Help
heuristicStopTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
hiddenLayersTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
hidePerspectivesToolBar() - Method in class weka.gui.AbstractGUIApplication: Hide the perspectives toolbar
hidePerspectivesToolBar() - Method in interface weka.gui.GUIApplication: Hide the perspectives toolbar
HierarchicalBCEngine - Class in weka.gui.graphvisualizer: This class lays out the vertices of a graph in a hierarchy of vertical levels, with a number of nodes in each level.
HierarchicalBCEngine(ArrayList<GraphNode>, ArrayList<GraphEdge>, int, int) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: Constructor - takes in FastVectors of nodes and edges, and the initial width and height of a node
HierarchicalBCEngine(ArrayList<GraphNode>, ArrayList<GraphEdge>, int, int, boolean) - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: Constructor - takes in FastVectors of nodes and edges, the initial width and height of a node, and a boolean value to indicate if the edges should be concentrated.
HierarchicalBCEngine() - Constructor for class weka.gui.graphvisualizer.HierarchicalBCEngine: SimpleConstructor If we want to instantiate the class first, and if information for nodes and edges is not available.
HierarchicalClusterer - Class in weka.clusterers: Hierarchical clustering class.
HierarchicalClusterer() - Constructor for class weka.clusterers.HierarchicalClusterer
HierarchyPropertyParser - Class in weka.gui: This class implements a parser to read properties that have a hierarchy(i.e.
HierarchyPropertyParser() - Constructor for class weka.gui.HierarchyPropertyParser: Default constructor
HierarchyPropertyParser(String, String) - Constructor for class weka.gui.HierarchyPropertyParser: Constructor that builds a tree from the given property with the given delimitor
HierarchyVisualizer - Class in weka.gui.hierarchyvisualizer
HierarchyVisualizer(String) - Constructor for class weka.gui.hierarchyvisualizer.HierarchyVisualizer
highlightLastRow(int) - Method in class weka.gui.InteractiveTablePanel: Highlight the last row in the table
HillClimber - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.HillClimber
HillClimber - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses a hill climbing algorithm adding, deleting and reversing arcs.
HillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.HillClimber
HINGE - Static variable in class weka.classifiers.functions.SGD: the hinge loss function.
HINGE - Static variable in class weka.classifiers.functions.SGDText: the hinge loss function.
History - Class in weka.gui.simplecli: Prints all issued commands.
History() - Constructor for class weka.gui.simplecli.History
HISTORY_NAME - Static variable in class weka.gui.sql.ConnectionPanel: the name of the history.
HISTORY_NAME - Static variable in class weka.gui.sql.QueryPanel: the name of the history.
historyChanged(HistoryChangedEvent) - Method in interface weka.gui.sql.event.HistoryChangedListener: This method gets called when a history is modified.
historyChanged(HistoryChangedEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when a history is modified.
HistoryChangedEvent - Class in weka.gui.sql.event: An event that is generated when a history is modified.
HistoryChangedEvent(Object, String, DefaultListModel) - Constructor for class weka.gui.sql.event.HistoryChangedEvent: constructs the event
HistoryChangedListener - Interface in weka.gui.sql.event: A listener for changes in a history.
historySelected(GenericObjectEditorHistory.HistorySelectionEvent) - Method in interface weka.gui.GenericObjectEditorHistory.HistorySelectionListener: Gets called when a history item gets selected.
HistorySelectionEvent(Object, Object) - Constructor for class weka.gui.GenericObjectEditorHistory.HistorySelectionEvent: Initializes the event.
hit(Rectangle, Shape, boolean) - Method in class weka.gui.visualize.PostscriptGraphics
HLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
HNode - Class in weka.classifiers.trees.ht: Abstract base class for nodes in a Hoeffding tree
HNode() - Constructor for class weka.classifiers.trees.ht.HNode: Construct a new HNode
HNode(Map<String, WeightMass>) - Constructor for class weka.classifiers.trees.ht.HNode: Construct a new HNode with the supplied class distribution
hoeffdingTieThresholdTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
HoeffdingTree - Class in weka.classifiers.trees: A Hoeffding tree (VFDT) is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not change over time.
HoeffdingTree() - Constructor for class weka.classifiers.trees.HoeffdingTree
holdOutFileTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
HoldOutSubsetEvaluator - Class in weka.attributeSelection: Abstract attribute subset evaluator capable of evaluating subsets with respect to a data set that is distinct from that used to initialize/ train the subset evaluator.
HoldOutSubsetEvaluator() - Constructor for class weka.attributeSelection.HoldOutSubsetEvaluator
HostListPanel - Class in weka.gui.experiment: This panel controls setting a list of hosts for a RemoteExperiment to use.
HostListPanel(RemoteExperiment) - Constructor for class weka.gui.experiment.HostListPanel: Creates the host list panel with the given experiment.
HostListPanel() - Constructor for class weka.gui.experiment.HostListPanel: Create the host list panel initially disabled.
HTML - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions in HTML.
HTML() - Constructor for class weka.classifiers.evaluation.output.prediction.HTML
HUBER - Static variable in class weka.classifiers.functions.SGD: The Huber loss function
hypot(double, double) - Static method in class weka.core.matrix.Maths: sqrt(a^2 + b^2) without under/overflow.

I

I0 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
I0a - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
I0b - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
I1 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
I2 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
I3 - Static variable in class weka.classifiers.functions.supportVector.RegSMOImproved
IBk - Class in weka.classifiers.lazy: K-nearest neighbours classifier.
IBk(int) - Constructor for class weka.classifiers.lazy.IBk: IBk classifier.
IBk() - Constructor for class weka.classifiers.lazy.IBk: IB1 classifer.
ICON_PATH - Static variable in class weka.gui.beans.BeanVisual
ICON_PATH - Static variable in class weka.gui.knowledgeflow.MainKFPerspectiveToolBar: Path to the icons for the toolbar
iconForStep(Step) - Static method in class weka.gui.knowledgeflow.StepVisual: Gets the icon for the supplied Step.
ICSSearchAlgorithm - Class in weka.classifiers.bayes.net.search.ci: This Bayes Network learning algorithm uses conditional independence tests to find a skeleton, finds V-nodes and applies a set of rules to find the directions of the remaining arrows.
ICSSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
ID - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
ID - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
ID - Variable in class weka.gui.graphvisualizer.GraphNode: ID and label for the node
ID - Static variable in class weka.gui.knowledgeflow.AttributeSummaryPerspective.AttDefaults
ID - Static variable in class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: ID for the metastore
ID - Static variable in class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
ID - Static variable in class weka.knowledgeflow.steps.TextSaver.TextSaverDefaults
IDENTIFIER - Static variable in interface weka.core.expressionlanguage.parser.sym
identity(int, int) - Static method in class weka.core.matrix.Matrix: Generate identity matrix
IDFTransformTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
IDFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
IDIndexTipText() - Method in class weka.filters.unsupervised.attribute.AddID: Returns the tip text for this property
IDLE - Static variable in class weka.gui.beans.BeanInstance: class variable holding all the beans
IfElseMacro - Class in weka.core.expressionlanguage.common: A macro declaration exposing the ifelse function.
IfElseMacro() - Constructor for class weka.core.expressionlanguage.common.IfElseMacro
ignoreCaseForNamesTipText() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the tip text for this property
ignoreCaseTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the tip text for this property
ignoreClassTipText() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Returns the tip text for this property
ignoreClassTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
ignored() - Method in class weka.core.xml.PropertyHandler: returns an enumeration of the stored display names and classes of properties to ignore.
NOTE: String and Class Objects are mixed in this enumeration, depending whether it is a global property to ignore or just one for a certain class!
ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the tip text for this property.
ignoredAttributeIndicesTipText() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns the tip text for this property
ignoreRangeTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the tip text for this property
ImageEvent - Class in weka.gui.beans: Event that encapsulates an Image
ImageEvent(Object, BufferedImage) - Constructor for class weka.gui.beans.ImageEvent: Construct a new ImageEvent
ImageEvent(Object, BufferedImage, String) - Constructor for class weka.gui.beans.ImageEvent: Construct an ImageEvent
ImageListener - Interface in weka.gui.beans: Interface to something that can process an ImageEvent
IMAGES - Static variable in class weka.gui.ComponentHelper: the default directories for images
IMAGES_DIR - Static variable in class weka.gui.scripting.FileScriptingPanel: the directory with the scripting-specific images.
ImageSaver - Class in weka.gui.beans: Component that can accept ImageEvents and save their encapsulated images to a file.
ImageSaver() - Constructor for class weka.gui.beans.ImageSaver: Constructs a new ImageSaver
ImageSaver - Class in weka.knowledgeflow.steps: Step for saving static images as either png or gif.
ImageSaver() - Constructor for class weka.knowledgeflow.steps.ImageSaver
ImageSaver.ImageSaverDefaults - Class in weka.knowledgeflow.steps
ImageSaverBeanInfo - Class in weka.gui.beans: BeanInfo class for the ImageSaver component.
ImageSaverBeanInfo() - Constructor for class weka.gui.beans.ImageSaverBeanInfo
ImageSaverCustomizer - Class in weka.gui.beans: Customizer for the ImageSaver component.
ImageSaverCustomizer() - Constructor for class weka.gui.beans.ImageSaverCustomizer: Constructor
ImageSaverDefaults() - Constructor for class weka.knowledgeflow.steps.ImageSaver.ImageSaverDefaults
ImageViewer - Class in weka.gui.beans: A KF component that can accept imageEvent connections in order to display static images in a popup window
ImageViewer() - Constructor for class weka.gui.beans.ImageViewer: Constructs a new ImageViewer
ImageViewer - Class in weka.knowledgeflow.steps: A step for collecting and viewing image data
ImageViewer() - Constructor for class weka.knowledgeflow.steps.ImageViewer
ImageViewerBeanInfo - Class in weka.gui.beans: BeanInfo class for the ImageViewer component
ImageViewerBeanInfo() - Constructor for class weka.gui.beans.ImageViewerBeanInfo
ImageViewerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the ImageViewer step
ImageViewerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.AbstractClassifier: Return true if this classifier can generate batch predictions in an efficient manner.
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.Bagging: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.ClassificationViaRegression: Return whether this classifier configuration yields more efficient batch prediction
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.FilteredClassifier: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.LogitBoost: Performs efficient batch prediction
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.RandomCommittee: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.RandomSubSpace: Returns true if the base classifier implements BatchPredictor and is able to generate batch predictions efficiently
implementsMoreEfficientBatchPrediction() - Method in class weka.classifiers.meta.Stacking: Returns true if the meta classifier or any of the base classifiers are able to generate batch predictions efficiently and all of them implement BatchPredictor.
implementsMoreEfficientBatchPrediction() - Method in interface weka.core.BatchPredictor: Returns true if this BatchPredictor can generate batch predictions in an efficient manner.
Impurity - Class in weka.classifiers.trees.m5: Class for handling the impurity values when spliting the instances
Impurity(int, int, Instances, int) - Constructor for class weka.classifiers.trees.m5.Impurity: Constructs an Impurity object containing the impurity values of partitioning the instances using an attribute
InactiveHNode - Class in weka.classifiers.trees.ht: Class implementing an inactive node (i.e.
InactiveHNode(Map<String, WeightMass>) - Constructor for class weka.classifiers.trees.ht.InactiveHNode: Constructor
includeClassTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
incomingInstanceToVectorFieldVals(double[]) - Method in class weka.core.pmml.VectorDictionary: Convert an incoming instance to an array of values that corresponds to the fields referenced by the support vectors in the vector dictionary
incompleteBeta(double, double, double) - Static method in class weka.core.Statistics: Returns the Incomplete Beta Function evaluated from zero to xx.
incompleteBetaFraction1(double, double, double) - Static method in class weka.core.Statistics: Continued fraction expansion #1 for incomplete beta integral.
incompleteBetaFraction2(double, double, double) - Static method in class weka.core.Statistics: Continued fraction expansion #2 for incomplete beta integral.
incompleteGamma(double, double) - Static method in class weka.core.Statistics: Returns the Incomplete Gamma function.
incompleteGammaComplement(double, double) - Static method in class weka.core.Statistics: Returns the Complemented Incomplete Gamma function.
incorrect() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of incorrect classifications (that is, for which an incorrect prediction was made).
incorrect() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
incorrect() - Method in class weka.classifiers.Evaluation: Gets the number of instances incorrectly classified (that is, for which an incorrect prediction was made).
incrCoordCount() - Method in class weka.core.neighboursearch.PerformanceStats: Increments the coordinate count (number of coordinates/attributes looked at).
increaseFontSize() - Method in class weka.gui.beans.Note: Increase the font size by one
increaseFontSize() - Method in class weka.gui.knowledgeflow.NoteVisual: Increase the font size by one
increaseFrequency(int) - Method in class weka.associations.Item: Increase the frequency of this item.
increaseFrequency() - Method in class weka.associations.Item: Increment the frequency of this item.
incremental(double, int) - Method in class weka.classifiers.trees.m5.Impurity: Incrementally computes the impurirty values
INCREMENTAL - Static variable in interface weka.core.converters.Loader
INCREMENTAL - Static variable in interface weka.core.converters.Saver
IncrementalClassifierEvaluator - Class in weka.gui.beans: Bean that evaluates incremental classifiers
IncrementalClassifierEvaluator() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluator
IncrementalClassifierEvaluator - Class in weka.knowledgeflow.steps: Step that evaluates incremental classifiers and produces strip chart data
IncrementalClassifierEvaluator() - Constructor for class weka.knowledgeflow.steps.IncrementalClassifierEvaluator
IncrementalClassifierEvaluatorBeanInfo - Class in weka.gui.beans: Bean info class for the incremental classifier evaluator bean
IncrementalClassifierEvaluatorBeanInfo() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluatorBeanInfo
IncrementalClassifierEvaluatorCustomizer - Class in weka.gui.beans: GUI Customizer for the incremental classifier evaluator bean
IncrementalClassifierEvaluatorCustomizer() - Constructor for class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
IncrementalClassifierEvent - Class in weka.gui.beans: Class encapsulating an incrementally built classifier and current instance
IncrementalClassifierEvent(Object, Classifier, Instance, int) - Constructor for class weka.gui.beans.IncrementalClassifierEvent: Creates a new IncrementalClassifierEvent instance.
IncrementalClassifierEvent(Object, Classifier, Instances) - Constructor for class weka.gui.beans.IncrementalClassifierEvent: Creates a new incremental classifier event that encapsulates header information and classifier.
IncrementalClassifierEvent(Object) - Constructor for class weka.gui.beans.IncrementalClassifierEvent
IncrementalClassifierListener - Interface in weka.gui.beans: Interface to something that can process a IncrementalClassifierEvent
IncrementalConverter - Interface in weka.core.converters: Marker interface for a loader/saver that can retrieve instances incrementally
IncrementalEstimator - Interface in weka.estimators: Interface for an incremental probability estimators.
incrIntNodeCount() - Method in class weka.core.neighboursearch.TreePerformanceStats: Increments the internal node count.
incrLeafCount() - Method in class weka.core.neighboursearch.TreePerformanceStats: Increments the leaf count.
incrPointCount() - Method in class weka.core.neighboursearch.PerformanceStats: Increments the point count (number of datapoints looked at).
index() - Method in class weka.core.Attribute: Returns the index of this attribute.
index(int) - Method in class weka.core.DenseInstance: Returns the index of the attribute stored at the given position.
index(int) - Method in interface weka.core.Instance: Returns the index of the attribute stored at the given position in the sparse representation.
index(int) - Method in class weka.core.pmml.Array: Returns the index of the value stored at the given position
index(int) - Method in class weka.core.pmml.SparseArray: Returns the index of the value stored at the given position
index(int) - Method in class weka.core.SparseInstance: Returns the index of the attribute stored at the given position.
INDEX_BEANCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans: the index in the Vector, where the BeanConnections are stored (Instances and Connections are stored in a Vector and then serialized)
INDEX_BEANINSTANCES - Static variable in class weka.gui.beans.xml.XMLBeans: the index in the Vector, where the BeanInstances are stored (Instances and Connections are stored in a Vector and then serialized)
indexOf(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Searches for the first occurrence of elem.
indexOf(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Searches for the first occurrence of elem, beginning the search at index.
indexOfMax() - Method in class weka.core.matrix.DoubleVector: Returns the index of the maximum.
indexOfValue(String) - Method in class weka.core.Attribute: Returns the index of a given attribute value.
indexToOrdinal(int) - Static method in class weka.core.Utils: Turns a zero-based index into its ordinal representation, e.g., the integer 0 will be turned into the string "1st", 1 will be turned into the string "2nd", etc.
indexToString(int) - Static method in class weka.core.SingleIndex: Creates a string representation of the given index.
indicesToRangeList(int[]) - Static method in class weka.core.Range: Creates a string representation of the indices in the supplied array.
individualPredictions(Instance) - Method in class weka.classifiers.meta.MultiClassClassifier: Returns the individual predictions of the base classifiers for an instance.
INFO - Static variable in class weka.core.Debug: the log level Info
info(int[]) - Static method in class weka.core.Utils: Computes entropy for an array of integers.
INFO_GAIN_SPLIT - Static variable in class weka.classifiers.trees.HoeffdingTree
infoGain() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns (C4.5-type) information gain for the generated split.
infoGain() - Method in class weka.classifiers.trees.j48.C45Split: Returns (C4.5-type) information gain for the generated split.
InfoGainAttributeEval - Class in weka.attributeSelection: InfoGainAttributeEval :

Evaluates the worth of an attribute by measuring the information gain with respect to the class.

InfoGain(Class,Attribute) = H(Class) - H(Class | Attribute).

Valid options are:
InfoGainAttributeEval() - Constructor for class weka.attributeSelection.InfoGainAttributeEval: Constructor
InfoGainSplitCrit - Class in weka.classifiers.trees.j48: Class for computing the information gain for a given distribution.
InfoGainSplitCrit() - Constructor for class weka.classifiers.trees.j48.InfoGainSplitCrit
InfoGainSplitMetric - Class in weka.classifiers.trees.ht: Implements the info gain splitting criterion
InfoGainSplitMetric(double) - Constructor for class weka.classifiers.trees.ht.InfoGainSplitMetric
InfoPanel - Class in weka.gui.sql: A simple panel for displaying information, e.g.
InfoPanel(JFrame) - Constructor for class weka.gui.sql.InfoPanel: creates the panel
InfoPanelCellRenderer - Class in weka.gui.sql: A specialized renderer that takes care of JLabels in a JList.
InfoPanelCellRenderer() - Constructor for class weka.gui.sql.InfoPanelCellRenderer: the constructor
InformationRetrievalEvaluationMetric - Interface in weka.classifiers.evaluation: An interface for information retrieval evaluation metrics to implement.
InformationTheoreticEvaluationMetric - Interface in weka.classifiers.evaluation: Primarily a marker interface for information theoretic evaluation metrics to implement.
InfoToWiki - Class in weka.gui
InfoToWiki() - Constructor for class weka.gui.InfoToWiki
InheritanceUtils - Class in weka.core: Helper class for inheritance related operations.
InheritanceUtils() - Constructor for class weka.core.InheritanceUtils
Init(int, int) - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Init defines a minimal Bayes net with no arcs
init(Environment) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Initialize this attribute spec by resolving any environment variables and setting up the date format (if necessary)
init() - Static method in class weka.gui.beans.BeanConnection: Sets up just a single collection of bean connections in the first element of the list.
init() - Static method in class weka.gui.beans.BeanInstance: Sets up just a single collection of bean instances in the first element of the list.
init(Environment, Instances) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Initialize this match rule by substituting any environment variables in the attributes, match and label strings.
init(Environment, Instances) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Initialize this match replace rule by substituting any environment variables in the attributes, match and replace strings.
init() - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Initialize this viewer.
init() - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerInteractiveView: Initialize the viewer - layout widgets etc.
init() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Initialize/layout the viewer
init() - Method in class weka.gui.knowledgeflow.steps.CostBenefitAnalysisInteractiveView: Initialize and layout the viewer
init() - Method in class weka.gui.knowledgeflow.steps.DataVisualizerInteractiveView: Initialize and layout the viewer
init() - Method in class weka.gui.knowledgeflow.steps.GraphViewerInteractiveView: Initializes the viewer
init() - Method in class weka.gui.knowledgeflow.steps.ImageViewerInteractiveView: Initialize the viewer and the layout
init() - Method in class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView: Initialize and layout the viewer
init() - Method in class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView: Initialize the viewer
init() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Initialize the viewer
init() - Method in class weka.gui.knowledgeflow.steps.TextViewerInteractiveView: Initialize the viewer
init(Instances, Environment) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
init(Instances, Environment) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
init(Instances, Environment) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Initialize the node
init(Environment, Instances) - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Initialize the rule
initAsNaiveBayesTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
initComponent() - Method in class weka.gui.InteractiveTablePanel: Initializes the component
initCPTs() - Method in class weka.classifiers.bayes.BayesNet: initializes the conditional probabilities
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: initCPTs reserves space for CPTs and set all counts to zero
initCPTs(BayesNet) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: initCPTs reserves space for CPTs and set all counts to zero
initDefaultFilters() - Static method in class weka.gui.ConverterFileChooser: Initialize the default set of filters for loaders and savers
initFileClassIndexTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
initFileTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
initFilter(Instances) - Method in class weka.filters.unsupervised.attribute.KernelFilter: initializes the filter with the given dataset, i.e., the kernel gets built.
initFlow(FlowExecutor) - Method in class weka.knowledgeflow.Flow: Initialize the flow by setting the execution environment and calling the init() method of each step
INITIAL_DIR - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
INITIAL_DIR_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
INITIAL_STEP - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
initialAnchorRandomTipText() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns the tip text for this property.
initialCountTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
initializationMethodTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
initialize() - Method in class weka.classifiers.CostMatrix: Initializes the matrix
initialize() - Method in class weka.classifiers.trees.j48.Distribution: Sets all counts to zero.
initialize(int, int, int) - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Resets the object of split information
initialize(int, int, int) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Resets the object of split information
initialize() - Static method in class weka.core.converters.ConverterResources
initialize() - Static method in class weka.core.converters.ConverterUtils
initialize(File) - Method in class weka.experiment.DatabaseUtils: Initializes the database connection.
initialize(Properties) - Method in class weka.experiment.DatabaseUtils: Initializes the database connection.
initialize() - Method in class weka.experiment.Experiment: Prepares an experiment for running, initializing current iterator settings.
initialize() - Method in class weka.experiment.RemoteExperiment: Prepares a remote experiment for running, creates sub experiments
initialize() - Method in class weka.gui.visualize.BMPWriter: further initialization.
initialize() - Method in class weka.gui.visualize.JPEGWriter: further initialization.
initialize() - Method in class weka.gui.visualize.PNGWriter: further initialization.
initializeAndComputeMatrix(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Intializes the evaluator, filters the input data and computes the correlation/covariance matrix.
initializeClassifier(Instances) - Method in class weka.classifiers.functions.MultilayerPerceptron: Initializes an iterative classifier.
initializeClassifier(Instances) - Method in interface weka.classifiers.IterativeClassifier: Initializes an iterative classifier.
initializeClassifier(Instances) - Method in class weka.classifiers.meta.AdaBoostM1: Initialize the classifier.
initializeClassifier(Instances) - Method in class weka.classifiers.meta.AdditiveRegression: Initialize classifier.
initializeClassifier(Instances) - Method in class weka.classifiers.meta.FilteredClassifier: Initializes an iterative classifier.
initializeClassifier(Instances) - Method in class weka.classifiers.meta.LogitBoost: Builds the boosted classifier
initializeClassifier(Instances) - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Initializes an iterative classifier.
initializeDistanceFunction(Instances) - Method in class weka.clusterers.Canopy: Initialize the distance function (i.e set min/max values for numeric attributes) with the supplied instances.
initializeDown(boolean) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
initializeModel(int, double[], double[], Random) - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Initializes the model.
initializeRanges(int) - Method in class weka.core.Debug.DBO: Initialize ranges, upper limit must be set
initializeRanges() - Method in class weka.core.NormalizableDistance: Initializes the ranges using all instances of the dataset.
initializeRanges(int[]) - Method in class weka.core.NormalizableDistance: Initializes the ranges of a subset of the instances of this dataset.
initializeRanges(int[], int, int) - Method in class weka.core.NormalizableDistance: Initializes the ranges of a subset of the instances of this dataset.
initializeRangesEmpty(int, double[][]) - Method in class weka.core.NormalizableDistance: Used to initialize the ranges.
initializeStatistics() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Triggers construction of estimator based on current data and then initializes the statistics.
initializeUp() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
initInternalFields() - Method in class weka.gui.visualize.MatrixPanel: Initializes internal data fields, i.e.
initPMML() - Static method in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: Initializes a PMML object with header information.
initStructure() - Method in class weka.classifiers.bayes.BayesNet: Init structure initializes the structure to an empty graph or a Naive Bayes graph (depending on the -N flag).
INJECT_DEPENDENCY_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for dependency injection
injectStreaming(Data, Step, boolean) - Method in class weka.knowledgeflow.StepInjectorFlowRunner: Inject streaming data into the target step in the flow
injectWithExecutionFinishedCallback(Data, ExecutionFinishedCallback, Step) - Method in class weka.knowledgeflow.StepInjectorFlowRunner: Inject data into the flow
InlineTable - Class in weka.core.pmml.jaxbbindings: Java class for InlineTable element declaration.
InlineTable() - Constructor for class weka.core.pmml.jaxbbindings.InlineTable
InMemory - Class in weka.classifiers.evaluation.output.prediction: * Stores the predictions in memory for programmatic retrieval.
* Stores the instance, a prediction object and a map of attribute names with their associated values if an attribute was defined in a container per prediction.
* The list of predictions can get retrieved using the getPredictions() method.
* File output is disabled and buffer doesn't need to be supplied.
InMemory() - Constructor for class weka.classifiers.evaluation.output.prediction.InMemory
InMemory.PredictionContainer - Class in weka.classifiers.evaluation.output.prediction: Container for storing the predictions alongside the additional attributes.
innerProduct(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Returns the inner product of two DoubleVectors
INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is an input unit.
input(Instance) - Method in class weka.filters.AllFilter: Input an instance for filtering.
input(Instance) - Method in class weka.filters.Filter: Input an instance for filtering.
input(Instance) - Method in class weka.filters.RenameRelation
input(Instance) - Method in class weka.filters.SimpleBatchFilter: Input an instance for filtering.
input(Instances) - Method in class weka.filters.SimpleBatchFilter: A version of the input(Instance) method that enables input of a whole dataset represented as an Instances object into the filter.
input(Instance) - Method in class weka.filters.SimpleStreamFilter: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.AttributeSelection: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities
input(Instance) - Method in class weka.filters.supervised.attribute.ClassOrder: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.Discretize: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.NominalToBinary: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.attribute.PartitionMembership: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.Resample: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.SpreadSubsample: Input an instance for filtering.
input(Instance) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Add: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddCluster: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddExpression: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddID: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddNoise: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.AddValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Center: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Copy: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Discretize: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.FirstOrder: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MathExpression: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NominalToString: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Normalize: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Obfuscate: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Remove: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveType: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.Reorder: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
input(Instance) - Method in class weka.filters.unsupervised.attribute.Standardize: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToNominal: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.attribute.SwapValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.Randomize: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveDuplicates: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemovePercentage: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveRange: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.Resample: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.ReservoirSample: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse: Input an instance for filtering.
input(Instance) - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Input an instance for filtering.
input(Instance) - Method in class weka.gui.streams.InstanceCounter
input(Instance) - Method in class weka.gui.streams.InstanceJoiner
input(Instance) - Method in class weka.gui.streams.InstanceSavePanel
input(Instance) - Method in class weka.gui.streams.InstanceTable
input(Instance) - Method in class weka.gui.streams.InstanceViewer
inputFormat(Instances) - Method in class weka.gui.streams.InstanceCounter
inputFormat(Instances) - Method in class weka.gui.streams.InstanceJoiner: Sets the format of the input instances.
inputFormat(Instances) - Method in class weka.gui.streams.InstanceSavePanel
inputFormat(Instances) - Method in class weka.gui.streams.InstanceTable
inputFormat(Instances) - Method in class weka.gui.streams.InstanceViewer
InputMappedClassifier - Class in weka.classifiers.misc: Wrapper classifier that addresses incompatible training and test data by building a mapping between the training data that a classifier has been built with and the incoming test instances' structure.
InputMappedClassifier() - Constructor for class weka.classifiers.misc.InputMappedClassifier
InputMappedClassifierBeanInfo - Class in weka.classifiers.misc: Bean info class for the InputMappedClassifier.
InputMappedClassifierBeanInfo() - Constructor for class weka.classifiers.misc.InputMappedClassifierBeanInfo
inputOrderTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
inputs(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns a vector of BeanInstances that can be considered as inputs (or the left-hand side of a sub-flow)
inputsContains(BeanInstance) - Method in class weka.gui.beans.MetaBean
inRanges(Instance, double[][]) - Method in class weka.core.NormalizableDistance: Test if an instance is within the given ranges.
insert(int) - Method in class weka.classifiers.functions.supportVector.SMOset: Inserts an element into the set.
insert(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Inserts a new entry in the hashtable using the specified key.
insertAttributeAt(int) - Method in class weka.core.AbstractInstance: Inserts an attribute at the given position (0 to numAttributes()).
insertAttributeAt(int) - Method in interface weka.core.Instance: Inserts an attribute at the given position (0 to numAttributes()).
insertAttributeAt(Attribute, int) - Method in class weka.core.Instances: Inserts an attribute at the given position (0 to numAttributes()) and sets all values to be missing.
insertElementAt(E, int) - Method in class weka.core.FastVector: Deprecated.

Inserts an element at the given position.
insertElementAt(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Inserts the specified object as a component in this list at the specified index.
insertInstance(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: Insert a new instance (all values 0) at the given index.
insertInstance(int) - Method in class weka.gui.arffviewer.ArffTableModel
insertInstance(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
insertString(int, String, AttributeSet) - Method in class weka.gui.scripting.SyntaxDocument: Override to apply syntax highlighting after the document has been updated.
install() - Method in class weka.core.packageManagement.DefaultPackage: Install this package.
install() - Method in class weka.core.packageManagement.Package: Install this package.
installedPackageResourceExists(String, String) - Static method in class weka.core.WekaPackageManager: Check if a named resource exists in an installed package
installLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode: Traverses the tree and installs linear models at each node.
installNodeNums(int) - Method in class weka.classifiers.trees.ht.HNode
installNodeNums(int) - Method in class weka.classifiers.trees.ht.SplitNode
installPackageFromArchive(String, PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Install a package from an archive on the local file system.
installPackageFromArchive(String, PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Install a package from an archive on the local file system.
installPackageFromArchive(String, PrintStream...) - Static method in class weka.core.WekaPackageManager: Install a package from an archive (unofficial package install route)
installPackageFromRepository(String, Object, PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Install a package sourced from the repository.
installPackageFromRepository(String, Object, PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Install a package sourced from the repository.
installPackageFromRepository(String, String, PrintStream...) - Static method in class weka.core.WekaPackageManager: Install a named package by retrieving the location of the archive from the meta data stored in the repository
installPackageFromURL(URL, PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Install a package sourced from a given URL.
installPackageFromURL(URL, PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Install a package sourced from a given URL.
installPackageFromURL(URL, PrintStream...) - Static method in class weka.core.WekaPackageManager: Install a package from the supplied URL
installPackages(List<Package>, PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Installs all the packages in the supplied list.
installPackages(List<Package>, PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Installs all the packages in the supplied list.
installPackages(List<Package>, PrintStream...) - Static method in class weka.core.WekaPackageManager: Install the supplied list of packages
installSmoothedModels() - Method in class weka.classifiers.trees.m5.RuleNode
instance - Variable in class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer: the instance.
Instance - Interface in weka.core: Interface representing an instance.
instance(int) - Method in class weka.core.Instances: Returns the instance at the given position.
INSTANCE_AVAILABLE - Static variable in class weka.gui.beans.InstanceEvent
INSTANCE_AVAILABLE - Static variable in class weka.gui.streams.InstanceEvent: Specifies that an instance is available
InstanceComparator - Class in weka.core: A comparator for the Instance class.
InstanceComparator() - Constructor for class weka.core.InstanceComparator: Initializes the comparator and includes the class in the comparison and all attributes included.
InstanceComparator(boolean) - Constructor for class weka.core.InstanceComparator: Initializes the comparator with all attributes included.
InstanceComparator(boolean, String, boolean) - Constructor for class weka.core.InstanceComparator: Initializes the comparator.
InstanceCounter - Class in weka.gui.streams: A bean that counts instances streamed to it.
InstanceCounter() - Constructor for class weka.gui.streams.InstanceCounter
InstanceEvent - Class in weka.gui.beans: Event that encapsulates a single instance or header information only
InstanceEvent(Object, Instance, int) - Constructor for class weka.gui.beans.InstanceEvent: Creates a new InstanceEvent instance that encapsulates a single instance only.
InstanceEvent(Object, Instances) - Constructor for class weka.gui.beans.InstanceEvent: Creates a new InstanceEvent instance which encapsulates header information only.
InstanceEvent(Object) - Constructor for class weka.gui.beans.InstanceEvent
InstanceEvent - Class in weka.gui.streams: An event encapsulating an instance stream event.
InstanceEvent(Object, int) - Constructor for class weka.gui.streams.InstanceEvent: Constructs an InstanceEvent with the specified source object and event type
InstanceField - Class in weka.core.pmml.jaxbbindings: Java class for InstanceField element declaration.
InstanceField() - Constructor for class weka.core.pmml.jaxbbindings.InstanceField
InstanceFields - Class in weka.core.pmml.jaxbbindings: Java class for InstanceFields element declaration.
InstanceFields() - Constructor for class weka.core.pmml.jaxbbindings.InstanceFields
InstanceInfo - Interface in weka.gui.visualize: Interface for JFrames that display instance info.
InstanceInfoFrame - Class in weka.gui.visualize: Frame for displaying information on the displayed data.
InstanceInfoFrame() - Constructor for class weka.gui.visualize.InstanceInfoFrame: Initializes the frame.
InstanceJoiner - Class in weka.gui.streams: A bean that joins two streams of instances into one.
InstanceJoiner() - Constructor for class weka.gui.streams.InstanceJoiner: Setup the initial states of the member variables
InstanceListener - Interface in weka.gui.beans: Interface to something that can accept instance events
InstanceListener - Interface in weka.gui.streams: An interface for objects interested in listening to streams of instances.
InstanceLoader - Class in weka.gui.streams: A bean that produces a stream of instances from a file.
InstanceLoader() - Constructor for class weka.gui.streams.InstanceLoader
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceCounter
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner
instanceProduced(InstanceEvent) - Method in interface weka.gui.streams.InstanceListener
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceSavePanel
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceTable
instanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceViewer
InstanceProducer - Interface in weka.gui.streams: An interface for objects capable of producing streams of instances.
InstanceQuery - Class in weka.experiment: Convert the results of a database query into instances.
InstanceQuery() - Constructor for class weka.experiment.InstanceQuery: Sets up the database drivers
InstanceQueryAdapter - Interface in weka.experiment: An interface implemented by InstanceQuery and any user class that is to be passed as the first argument to InstanceQuery.retrieveInstances(InstanceQueryAdapter, ResultSet).
instanceRangeTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
Instances - Class in weka.core: Class for handling an ordered set of weighted instances.
Instances(Reader) - Constructor for class weka.core.Instances: Reads an ARFF file from a reader, and assigns a weight of one to each instance.
Instances(Reader, int) - Constructor for class weka.core.Instances: Deprecated.
instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.
Instances(Instances) - Constructor for class weka.core.Instances: Constructor copying all instances and references to the header information from the given set of instances.
Instances(Instances, int) - Constructor for class weka.core.Instances: Constructor creating an empty set of instances.
Instances(Instances, int, int) - Constructor for class weka.core.Instances: Creates a new set of instances by copying a subset of another set.
Instances(String, ArrayList<Attribute>, int) - Constructor for class weka.core.Instances: Creates an empty set of instances.
InstanceSavePanel - Class in weka.gui.streams: A bean that saves a stream of instances to a file.
InstanceSavePanel() - Constructor for class weka.gui.streams.InstanceSavePanel
InstancesHelper - Class in weka.core.expressionlanguage.weka: A helper class to expose instance values and macros for instance values to a program
InstancesHelper(Instances) - Constructor for class weka.core.expressionlanguage.weka.InstancesHelper: Constructs an InstancesHelper for the given dataset.
InstancesHelper(Instances, boolean) - Constructor for class weka.core.expressionlanguage.weka.InstancesHelper: Constructs an InstancesHelper for the given dataset.
instancesIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns the tip text for this property
InstancesResultListener - Class in weka.experiment: Outputs the received results in arff format to a Writer.
InstancesResultListener() - Constructor for class weka.experiment.InstancesResultListener: Sets temporary file.
InstancesSummaryPanel - Class in weka.gui: This panel just displays relation name, number of instances, and number of attributes.
InstancesSummaryPanel() - Constructor for class weka.gui.InstancesSummaryPanel: Creates the instances panel with no initial instances.
InstanceStreamToBatchMaker - Class in weka.gui.beans: Bean that converts an instance stream into a (batch) data set.
InstanceStreamToBatchMaker() - Constructor for class weka.gui.beans.InstanceStreamToBatchMaker
InstanceStreamToBatchMaker - Class in weka.knowledgeflow.steps: Step that converts an incoming instance stream to a batch dataset
InstanceStreamToBatchMaker() - Constructor for class weka.knowledgeflow.steps.InstanceStreamToBatchMaker
InstanceStreamToBatchMakerBeanInfo - Class in weka.gui.beans: BeanInfo class for the InstanceStreamToBatchMaker bean
InstanceStreamToBatchMakerBeanInfo() - Constructor for class weka.gui.beans.InstanceStreamToBatchMakerBeanInfo
InstanceTable - Class in weka.gui.streams: A bean that takes a stream of instances and displays in a table.
InstanceTable() - Constructor for class weka.gui.streams.InstanceTable
instanceToSchema(Instance, MiningSchema) - Method in class weka.core.pmml.MappingInfo: Convert an Instance to an array of values that matches the format of the mining schema.
InstanceViewer - Class in weka.gui.streams: This is a very simple instance viewer - just displays the dataset as text output as it would be written to a file.
InstanceViewer() - Constructor for class weka.gui.streams.InstanceViewer
instantiateStep() - Method in class weka.gui.knowledgeflow.StepTreeLeafDetails: Instantiate the step at this leaf and return it wrapped in a StepVisual
instantiationComplete() - Method in class weka.gui.AbstractPerspective: No-opp implementation.
instantiationComplete() - Method in class weka.gui.experiment.Experimenter: Gets called if we are running in a GUIApplication.
instantiationComplete() - Method in class weka.gui.explorer.PreprocessPanel: We've been instantiated and now have access to the main application and PerspectiveManager
instantiationComplete() - Method in interface weka.gui.Perspective: Gets called when startup of the application has completed.
instantiationComplete() - Method in class weka.gui.SimpleCLIPanel
intCount - Variable in class weka.core.AttributeStats: The number of int-like values
INTEGER - Static variable in interface weka.core.json.sym
INTEGER - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster subtype: integer
INTEGER - Static variable in class weka.experiment.DatabaseUtils: Type mapping for INTEGER used for reading experiment results.
InteractiveTableModel - Class in weka.gui.beans: Deprecated.
Use weka.gui.InteractiveTableModel instead. Retained for backward compatibility
InteractiveTableModel(String[]) - Constructor for class weka.gui.beans.InteractiveTableModel: Deprecated.

Constructor
InteractiveTableModel - Class in weka.gui: Table model that automatically adds a new row to the table on pressing enter in the last cell of a row.
InteractiveTableModel(String[]) - Constructor for class weka.gui.InteractiveTableModel: Constructor
InteractiveTableModelListener() - Constructor for class weka.gui.InteractiveTablePanel.InteractiveTableModelListener
InteractiveTablePanel - Class in weka.gui.beans: Deprecated.
Use weka.gui.InteractiveTablePanel instead. Retained for backward compatibility
InteractiveTablePanel(String[]) - Constructor for class weka.gui.beans.InteractiveTablePanel: Deprecated.

Constructor
InteractiveTablePanel - Class in weka.gui: Provides a panel using an interactive table model.
InteractiveTablePanel(String[]) - Constructor for class weka.gui.InteractiveTablePanel: Constructor
InteractiveTablePanel.InteractiveTableModelListener - Class in weka.gui: Listener for the InteractiveTablePanel
intercept() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Return the intercept
internalCacheSizeTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
internalDynamicToMap(String) - Static method in class weka.knowledgeflow.steps.SetVariables
internalDynamicToMap(String) - Static method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
internalToMap(String) - Static method in class weka.knowledgeflow.steps.SetVariables: Convert a string in the internal static variable representation to a map of variables + values
INTERPOLATIONMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for INTERPOLATION-METHOD.
InterquartileRange - Class in weka.filters.unsupervised.attribute: A filter for detecting outliers and extreme values based on interquartile ranges.
InterquartileRange() - Constructor for class weka.filters.unsupervised.attribute.InterquartileRange
InterquartileRange.ValueType - Enum in weka.filters.unsupervised.attribute: enum for obtaining the various determined IQR values.
interrupted() - Method in interface weka.knowledgeflow.StepManager: Step implementations processing batch data should call this as soon as they have finished processing after a stop has been requested.
interrupted() - Method in class weka.knowledgeflow.StepManagerImpl: Finished processing due to a stop being requested.
Interval - Class in weka.core.pmml.jaxbbindings: Java class for Interval element declaration.
Interval() - Constructor for class weka.core.pmml.jaxbbindings.Interval
IntervalBasedEvaluationMetric - Interface in weka.classifiers.evaluation: Primarily a marker interface for interval-based evaluation metrics to implement.
IntervalEstimator - Interface in weka.classifiers: Interface for numeric prediction schemes that can output prediction intervals.
INTSparseArray - Class in weka.core.pmml.jaxbbindings: Java class for INT-SparseArray element declaration.
INTSparseArray() - Constructor for class weka.core.pmml.jaxbbindings.INTSparseArray
IntVector - Class in weka.core.matrix: A vector specialized on integers.
IntVector() - Constructor for class weka.core.matrix.IntVector: Constructs a null vector.
IntVector(int) - Constructor for class weka.core.matrix.IntVector: Constructs an n-vector of zeros.
IntVector(int, int) - Constructor for class weka.core.matrix.IntVector: Constructs an n-vector of a constant
IntVector(int[]) - Constructor for class weka.core.matrix.IntVector: Constructs a vector given an int array
INVALIDVALUETREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for INVALID-VALUE-TREATMENT-METHOD.
INVERSE - Static variable in class weka.classifiers.lazy.LWL
inverse() - Method in class weka.core.matrix.Matrix: Matrix inverse or pseudoinverse
invertSelectionTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.core.NormalizableDistance: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Copy: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.Remove: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
invertSelectionTipText() - Method in class weka.filters.unsupervised.instance.Resample: Returns the tip text for this property
invertTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
InvisibleNode - Class in weka.gui.knowledgeflow: Subclass of DefaultMutableTreeNode that can hide itself in a JTree.
InvisibleNode() - Constructor for class weka.gui.knowledgeflow.InvisibleNode: Constructor
InvisibleNode(Object) - Constructor for class weka.gui.knowledgeflow.InvisibleNode: Constructor for a new node that allows children and is visible
InvisibleNode(Object, boolean, boolean) - Constructor for class weka.gui.knowledgeflow.InvisibleNode: Constructor
InvisibleTreeModel - Class in weka.gui.knowledgeflow: Subclass of DefaultTreeModel that contains InvisibleNodes.
InvisibleTreeModel(TreeNode) - Constructor for class weka.gui.knowledgeflow.InvisibleTreeModel: Constructor
InvisibleTreeModel(TreeNode, boolean) - Constructor for class weka.gui.knowledgeflow.InvisibleTreeModel: Constuctor
InvisibleTreeModel(TreeNode, boolean, boolean) - Constructor for class weka.gui.knowledgeflow.InvisibleTreeModel: Constructor
invoke(String, Class<?>[], Object[]) - Method in class weka.core.scripting.Groovy: executes the specified method on the current interpreter and returns the result, if any.
invoke(Object, String, Class<?>[], Object[]) - Static method in class weka.core.scripting.Groovy: executes the specified method and returns the result, if any.
invoke(String, Class<?>[], Object[]) - Method in class weka.core.scripting.Jython: executes the specified method on the current interpreter and returns the result, if any.
invoke(Object, String, Class<?>[], Object[]) - Static method in class weka.core.scripting.Jython: executes the specified method and returns the result, if any
invokeMain(String, String[]) - Static method in class weka.gui.SplashWindow: Invokes the main method of the provided class name.
invokeMethod(String, String, String[]) - Static method in class weka.gui.SplashWindow: Invokes the named method of the provided class name.
IRClassValueTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
IRClassValueTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
IRClassValueTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
is(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: 'is' is operator (to check for string equality)
IS - Static variable in interface weka.core.expressionlanguage.parser.sym
is(String) - Method in class weka.core.Stopwords: Returns true if the given string is a stop word.
isActivatedFilter() - Method in class weka.gui.knowledgeflow.InvisibleTreeModel: Return true if the visibility filter is active
isALeaf() - Method in class weka.core.neighboursearch.balltrees.BallNode: Returns true if the node is a leaf node (if both its left and right child are null).
isALeaf() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode: Returns whether if the node is a leaf or not.
isALeaf() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode: Checks if node is a leaf.
isAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: returns whether the given property (display name) is allowed for the given class.
isAllowed(Object, String) - Method in class weka.core.xml.PropertyHandler: returns whether the given property (display name) is allowed for the given object .
isAnonymous() - Method in class weka.core.json.JSONNode: Checks whether the node is anonymous.
isArff(String) - Static method in class weka.core.converters.ConverterUtils.DataSource: returns whether the extension of the location is likely to be of ARFF format, i.e., ending in ".arff" or ".arff.gz" (case-insensitive).
isArray() - Method in class weka.core.json.JSONNode: Returns wether the node is an array.
isArray(Element) - Static method in class weka.core.pmml.Array: Utility method to check if an XML element is an array.
isAttribute() - Method in enum weka.core.Capabilities.Capability: returns true if the capability is an attribute
isAttribute(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: Check if given index is in range of column indices for attributes
isAttribute(int) - Method in class weka.gui.arffviewer.ArffTableModel: Check if given index is in range of column indices for attributes
isAttributeCapability() - Method in enum weka.core.Capabilities.Capability: returns true if the capability is an attribute capability
isAveragable() - Method in class weka.core.Attribute: Returns whether the attribute can be averaged meaningfully.
isBoolean(int) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns true if attribute is boolean
isBorderOpaque() - Method in class weka.gui.beans.ShadowBorder: This implementation always returns true.
isBorderOpaque() - Method in class weka.gui.knowledgeflow.ShadowBorder: This implementation always returns true.
isBoundOR() - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Returns true if this is a bounded OR type of constraint
isBusy() - Method in class weka.gui.beans.Appender: Returns true if.
isBusy() - Method in class weka.gui.beans.Associator: Returns true if.
isBusy() - Method in interface weka.gui.beans.BeanCommon: Returns true if.
isBusy() - Method in class weka.gui.beans.ClassAssigner: Returns true if.
isBusy() - Method in class weka.gui.beans.Classifier: Returns true if.
isBusy() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Returns true if.
isBusy() - Method in class weka.gui.beans.ClassValuePicker: Returns true if.
isBusy() - Method in class weka.gui.beans.Clusterer: Returns true if.
isBusy() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Returns true if.
isBusy() - Method in class weka.gui.beans.CostBenefitAnalysis: Returns true if.
isBusy() - Method in class weka.gui.beans.CrossValidationFoldMaker: Returns true if.
isBusy() - Method in class weka.gui.beans.DataVisualizer: Returns true if.
isBusy() - Method in class weka.gui.beans.Filter: Returns true if.
isBusy() - Method in class weka.gui.beans.FlowByExpression
isBusy() - Method in class weka.gui.beans.ImageSaver
isBusy() - Method in class weka.gui.beans.ImageViewer
isBusy() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Returns true if.
isBusy() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Returns true if.
isBusy() - Method in class weka.gui.beans.Join: Returns true if we are doing something
isBusy() - Method in class weka.gui.beans.Loader: Returns true if.
isBusy() - Method in class weka.gui.beans.MetaBean: Returns true if.
isBusy() - Method in class weka.gui.beans.ModelPerformanceChart: Returns true if.
isBusy() - Method in class weka.gui.beans.PredictionAppender: Returns true if.
isBusy() - Method in class weka.gui.beans.Saver: Returns true if.
isBusy() - Method in class weka.gui.beans.SerializedModelSaver: Returns true if.
isBusy() - Method in class weka.gui.beans.Sorter: Returns true if.
isBusy() - Method in class weka.gui.beans.StripChart: Returns true if.
isBusy() - Method in class weka.gui.beans.SubstringLabeler: Returns true if.
isBusy() - Method in class weka.gui.beans.SubstringReplacer: Returns true if.
isBusy() - Method in class weka.gui.beans.TestSetMaker: Returns true if.
isBusy() - Method in class weka.gui.beans.TextSaver
isBusy() - Method in class weka.gui.beans.TextViewer: Returns true if.
isBusy() - Method in class weka.gui.beans.TrainingSetMaker: Returns true if.
isBusy() - Method in class weka.gui.beans.TrainTestSplitMaker: Returns true if.
isBusy() - Method in class weka.gui.SimpleCLIPanel: Checks whether a thread is currently running.
isCellEditable(int, int) - Method in class weka.gui.arffviewer.ArffTableModel: returns true if the cell at rowindex and columnindexis editable
isCellEditable(int, int) - Method in class weka.gui.InteractiveTableModel
isCellEditable(int, int) - Method in class weka.gui.SortedTableModel: Returns true if the cell at rowIndex and columnIndex is editable.
isCellEditable(int, int) - Method in class weka.gui.sql.ResultSetTableModel: returns true if the cell at rowindex and columnindexis editable.
isChanged() - Method in class weka.classifiers.bayes.net.EditableBayesNet: return true when current state differs from the state the network was last saved
isChanged() - Method in class weka.gui.arffviewer.ArffPanel: returns whether the content of the panel was changed
isChanged() - Method in class weka.gui.ViewerDialog: returns whether the data has been changed
isClass() - Method in enum weka.core.Capabilities.Capability: returns true if the capability is a class
isClassCapability() - Method in enum weka.core.Capabilities.Capability: returns true if the capability is a other capability
isClassname(String) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: tests whether the given partial string is the name of a class with classpath - it basically tests, whether the string consists only of alphanumeric literals, underscores and dots.
isCompatibleBaseSystem() - Method in class weka.core.packageManagement.DefaultPackage: Returns true if this package is compatible with the currently installed version of the base system.
isCompatibleBaseSystem() - Method in class weka.core.packageManagement.Package: Returns true if this package is compatible with the currently installed version of the base system.
isConnected() - Method in class weka.experiment.DatabaseUtils: Returns true if a database connection is active.
isConnected() - Method in class weka.gui.sql.event.ConnectionEvent: returns whether the connection is still open.
isContinuous() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: checks, whether cluster sub type is continuous
isCoreFileLoader(String) - Static method in class weka.core.converters.ConverterResources: checks whether the given class is one of the hardcoded core file loaders.
isCoreFileSaver(String) - Static method in class weka.core.converters.ConverterResources: checks whether the given class is one of the hardcoded core file savers.
isCpuTime() - Method in class weka.core.Debug.Clock: whether the measurement is based on the msecs returned from the System class or on the more accurate CPU time.
isCursorScrollable() - Method in class weka.experiment.DatabaseUtils: Checks whether cursors are scrollable in general, false otherwise (also if not connected).
isCursorScrollSensitive() - Method in class weka.experiment.DatabaseUtils: Returns whether the cursors only support forward movement or are scroll sensitive (with ResultSet.CONCUR_READ_ONLY concurrency).
isDataIsThresholdData() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Returns true if the plots being stored are threshold plots
isDate() - Method in class weka.core.Attribute: Tests if the attribute is a date type.
isDelimiter(String) - Method in class weka.gui.scripting.SyntaxDocument: Checks whether the character is a delimiter.
isEmpty() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Tests if this hashtable maps no keys to values.
isEmpty() - Method in class weka.core.matrix.DoubleVector: Checks if it is an empty vector
isEmpty() - Method in class weka.core.matrix.IntVector: Returns true if the vector is empty
isEmpty() - Method in class weka.core.Trie: Returns true if this collection contains no elements.
isEnabled(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: whether the given capability is enabled.
isEnabled() - Method in class weka.core.Memory: returns whether the memory management is enabled
isEnabledNot(Capabilities.Capability) - Method in class weka.core.FindWithCapabilities: whether the given "not to have" capability is enabled.
isExecuting() - Method in class weka.gui.knowledgeflow.VisibleLayout: Returns true if the flow managed by this layout is currently executing
isFinished() - Method in class weka.knowledgeflow.steps.PairedDataHelper: Return true if there is no further processing to be done
isFirstBatchDone() - Method in class weka.filters.Filter: Returns true if the first batch of instances got processed.
isFullRank() - Method in class weka.core.matrix.QRDecomposition: Is the matrix full rank?
isGaussian() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: checks, whether cluster type is gaussian
isHeadless() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Get whether this execution environment is headless
isHeadless() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Get whether this execution environment is headless
isHidden() - Method in class weka.gui.beans.BeanConnection: Returns true if this connection is invisible
isHierachic(String) - Method in class weka.gui.HierarchyPropertyParser: Whether the given string has a hierachy structure with the seperators
isIgnored(String) - Method in class weka.core.xml.PropertyHandler: checks whether the given display name is an ignored property
isIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: checks whether the given display name of a certain class is an ignored property.
isIgnored(Object, String) - Method in class weka.core.xml.PropertyHandler: checks whether the given display name of a given object is an ignored property.
isIncremental() - Method in class weka.core.converters.ConverterUtils.DataSource: returns whether the loader is an incremental one.
isIncremental() - Method in class weka.knowledgeflow.Data: Return true if the connection specified for this data object is incremental
isInDisabledList(String) - Static method in class weka.core.PluginManager: Returns true if the supplied fully qualified class name is in the disabled list
isInDisabledList(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Returns true if the supplied fully qualified class name is in the disabled list
isInitialAnchorRandom() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Gets whether if the initial anchor is chosen randomly.
isInRange(double) - Method in class weka.core.Attribute: Determines whether a value lies within the bounds of the attribute.
isInRange(int) - Method in class weka.core.Range: Gets whether the supplied cardinal number is included in the current range.
isInstalled() - Method in class weka.core.packageManagement.DefaultPackage: Returns true if this package is already installed
isInstalled() - Method in class weka.core.packageManagement.Package: Returns true if this package is already installed
isInteger() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: checks, whether cluster sub type is integer
isIsIntercept() - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Gets the value of the isIntercept property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.MiningModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TextModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Gets the value of the isScorable property.
isIsScorable() - Method in class weka.core.pmml.jaxbbindings.TreeModel: Gets the value of the isScorable property.
isIsTransformed() - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Gets the value of the isTransformed property.
isKeyword(String) - Method in class weka.experiment.DatabaseUtils: Checks whether the given string is a reserved keyword.
isKOML(String) - Static method in class weka.core.xml.SerialUIDChanger: checks whether the given filename ends with ".koml"
isLeaf() - Method in class weka.classifiers.trees.ht.HNode: Returns true if this is a leaf
isLeaf() - Method in class weka.classifiers.trees.ht.SplitNode
isLeaf() - Method in class weka.classifiers.trees.j48.ClassifierTree
isLeaf() - Method in class weka.classifiers.trees.m5.RuleNode: Return true if this node is a leaf
isLeafReached() - Method in class weka.gui.HierarchyPropertyParser: Whether the current position is a leaf
isMemoryLow() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Return true if memory is running low
isMissing(int) - Method in class weka.core.AbstractInstance: Tests if a specific value is "missing".
isMissing(Attribute) - Method in class weka.core.AbstractInstance: Tests if a specific value is "missing".
isMissing(int) - Method in interface weka.core.Instance: Tests if a specific value is "missing".
isMissing(Attribute) - Method in interface weka.core.Instance: Tests if a specific value is "missing".
isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: checks whether the value at the given position is missing
isMissingAt(int, int) - Method in class weka.gui.arffviewer.ArffTableModel: checks whether the value at the given position is missing
isMissingSparse(int) - Method in class weka.core.AbstractInstance: Tests if a specific value is "missing", given an index in the sparse representation.
isMissingSparse(int) - Method in interface weka.core.Instance: Tests if a specific value is "missing" in the sparse representation.
isMissingValue(double) - Static method in class weka.core.Utils: Tests if the given value codes "missing".
isModified() - Method in class weka.gui.scripting.Script: Returns whether the script is modified.
isMonitoring() - Method in class weka.gui.MemoryUsagePanel: Returns whether the thread is still running.
isNegated() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Get whether this node is negated.
isNewBatch() - Method in class weka.filters.Filter: Returns true if the a new batch was started, either a new instance of the filter was created or the batchFinished() method got called.
isNewer(String) - Method in class weka.core.Version: checks whether this version is newer than the one from the given version string
isNominal() - Method in class weka.core.Attribute: Test if the attribute is nominal.
isNominal(int) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns true if attribute is nominal
isNominal() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns true if selection attribute is nominal.
isNominal() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns true if selection attribute is nominal.
isNonsingular() - Method in class weka.core.matrix.LUDecomposition: Is the matrix nonsingular?
isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether the notification of changes is enabled
isNotificationEnabled() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether the notification of changes is enabled
isNullAt(int, int) - Method in class weka.gui.sql.ResultSetTableModel: checks whether the value of the cell is NULL.
isNumeric() - Method in class weka.core.Attribute: Tests if the attribute is numeric.
isNumeric() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns true if selection attribute is numeric.
isNumericAt(int) - Method in class weka.gui.sql.ResultSetTableModel: returns whether the column at the given index is numeric.
isObject() - Method in class weka.core.json.JSONNode: Returns wether the node is an object.
isOlder(String) - Method in class weka.core.Version: checks whether this version is older than the one from the given version string
isOr() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Get whether this node is to be OR'ed
isOtherCapability() - Method in enum weka.core.Capabilities.Capability: returns true if the capability is a class capability
isOutOfMemory() - Method in class weka.core.Memory: checks if there's still enough memory left by checking whether there is still a 50MB margin between getUsed() and getMax().
isOutputFormatDefined() - Method in class weka.filters.Filter: Returns whether the output format is ready to be collected
isOutputFormatDefined() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns whether the output format is ready to be collected
isPaintable() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
isPaintable() - Method in class weka.gui.ColorEditor: We paint our current color into the supplied bounding box
isPaintable() - Method in class weka.gui.CostMatrixEditor: Indicates whether the object can be represented graphically.
isPaintable() - Method in class weka.gui.EnvironmentField
isPaintable() - Method in class weka.gui.FileEditor: Returns true since this editor is paintable.
isPaintable() - Method in class weka.gui.GenericArrayEditor: Returns true to indicate that we can paint a representation of the string array.
isPaintable() - Method in class weka.gui.GenericObjectEditor: Returns true to indicate that we can paint a representation of the Object.
isPaintable() - Method in class weka.gui.PasswordField
isPaintable() - Method in class weka.gui.SimpleDateFormatEditor: Indicates whether the object can be represented graphically.
isPanelSelected() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: checks whether a panel is currently selected
isPerspectivesToolBarVisible() - Method in class weka.gui.AbstractGUIApplication: Returns true if the perspectives toolbar is visible at the current time
isPerspectivesToolBarVisible() - Method in interface weka.gui.GUIApplication: Returns true if the perspectives toolbar is visible at the current time
isPresent() - Static method in class weka.core.scripting.Groovy: returns whether the Groovy classes are present or not, i.e.
isPresent() - Static method in class weka.core.scripting.Jython: returns whether the Jython classes are present or not, i.e.
isPresent() - Static method in class weka.core.stemmers.SnowballStemmer: returns whether Snowball is present or not, i.e.
isPresent() - Static method in class weka.core.xml.KOML: returns whether KOML is present or not, i.e.
isPresent() - Static method in class weka.core.xml.XStream: returns whether XStream is present or not, i.e.
isPrimitive() - Method in class weka.core.json.JSONNode: Returns whether the node stores a primitive value or a an array/object.
isQuoteDelimiter(String) - Method in class weka.gui.scripting.SyntaxDocument: Checks whether the character is quote delimiter.
isRandom() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: checks, whether cluster type is random
isReadOnly() - Method in class weka.gui.arffviewer.ArffPanel: returns whether the model is read-only
isReadOnly() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether the model is read-only
isReadOnly() - Method in class weka.gui.arffviewer.ArffTable: returns whether the model is read-only
isReadOnly() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether the model is read-only
isRegular() - Method in class weka.core.Attribute: Returns whether the attribute values are equally spaced.
isRelationValued() - Method in class weka.core.Attribute: Tests if the attribute is relation valued.
isResourceIntensive() - Method in class weka.knowledgeflow.steps.BaseStep: Get whether this step is resource intensive (cpu/memory) or not.
isResourceIntensive() - Method in class weka.knowledgeflow.StepTask: Get whether this StepTask is resource intensive (cpu/memory) or not.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.AveragingResultProducer: Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.CSVResultListener: Always says a result is required.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultListener: Always says a result is required.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.DatabaseResultProducer: Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in class weka.experiment.LearningRateResultProducer: Determines whether the results for a specified key must be generated.
isResultRequired(ResultProducer, Object[]) - Method in interface weka.experiment.ResultListener: Determines whether the results for a specified key must be generated.
isRHSAnAttribute() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Returns true if the RHS is an attribute rather than a constant
isRootReached() - Method in class weka.gui.HierarchyPropertyParser: Whether the current position is the root
isRunning() - Method in class weka.core.Debug.Clock: whether the time is still being clocked
isRunning() - Method in class weka.gui.scripting.Script: Returns whether the script is still running.
isSaved() - Method in class weka.classifiers.bayes.net.EditableBayesNet: indicate the network state was saved
isSelectedCollectPredictionsForEvaluation() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to collect the predictions for computing evaluation statistics
isSelectedCV() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether cross-validation has been selected by the user
isSelectedEvalWithRespectToCosts() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether evaluation with respect to costs has been selected by the user
isSelectedOutputConfusion() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output the confusion matrix
isSelectedOutputEntropy() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output entropy metrics
isSelectedOutputModel() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output the model
isSelectedOutputModelsForTrainingSplits() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output the models for the training splits
isSelectedOutputPerClassStats() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output per-class stats
isSelectedOutputSourceCode() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to output source code
isSelectedPercentageSplit() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether a percentage split has been selected by the user
isSelectedPreserveOrder() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to preserve order of instances in a percentage split
isSelectedSeparateTestSet() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether a separate test set has been selected by the user
isSelectedStoreTestDataAndPredictions() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether the user has opted to store the test data and the predictions in the history
isSelectedTestOnTrain() - Method in class weka.gui.explorer.ClassifierPanel: Gets whether test on train has been selected by the user
isSerializable(String) - Static method in class weka.core.SerializationHelper: checks whether a class is serializable.
isSerializable(Class<?>) - Static method in class weka.core.SerializationHelper: checks whether a class is serializable.
isSorted() - Method in class weka.gui.SortedTableModel: returns whether the table was sorted
isSparse() - Method in class weka.core.pmml.Array: Is this array a SparseArray?
isSparse() - Method in class weka.core.pmml.SparseArray: Overrides isSparse() in Array and always returns true.
isSPD() - Method in class weka.core.matrix.CholeskyDecomposition: Is the matrix symmetric and positive definite?
isSquare() - Method in class weka.core.matrix.Matrix: returns whether the matrix is a square matrix or not.
isStepBusy() - Method in interface weka.knowledgeflow.StepManager: Returns true if, at this time, the step managed by this step manager is currently busy with processing
isStepBusy() - Method in class weka.knowledgeflow.StepManagerImpl: Returns true if, at the current time, the managed step is busy with processing
isStepFinished() - Method in interface weka.knowledgeflow.StepManager: Return true if the current step is finished.
isStepFinished() - Method in class weka.knowledgeflow.StepManagerImpl: Return true if the current step is finished.
isStopRequested() - Method in interface weka.knowledgeflow.StepManager: Return true if a stop has been requested by the runtime environment
isStopRequested() - Method in class weka.knowledgeflow.StepManagerImpl: Return true if a stop has been requested by the runtime environment
isStopRequested() - Method in class weka.knowledgeflow.steps.BaseStep: Convenience method that calls StepManager.isStopRequested()
isStopword(String) - Method in class weka.core.stopwords.AbstractStopwords: Returns true if the given string is a stop word.
isStopword(String) - Static method in class weka.core.Stopwords: Returns true if the given string is a stop word.
isStopword(String) - Method in interface weka.core.stopwords.StopwordsHandler: Returns true if the given string is a stop word.
isStreamableFilter() - Method in class weka.filters.MultiFilter: tests whether all the enclosed filters are streamable
isStreamFinished(Data) - Method in interface weka.knowledgeflow.StepManager: Returns true if this data object marks the end of an incremental stream.
isStreamFinished(Data) - Method in class weka.knowledgeflow.StepManagerImpl: Returns true if this data object marks the end of an incremental stream.
isString() - Method in class weka.core.Attribute: Tests if the attribute is a string.
isStructureOnly() - Method in class weka.gui.beans.DataSetEvent: Returns true if the encapsulated instances contain just header information
isStructureOnly() - Method in class weka.gui.beans.TestSetEvent: Returns true if the encapsulated instances contain just header information
isStructureOnly() - Method in class weka.gui.beans.TrainingSetEvent: Returns true if the encapsulated instances contain just header information
isSubclass(String, String) - Static method in class weka.core.InheritanceUtils: Checks whether the "otherclass" is a subclass of the given "superclass".
isSubclass(Class<?>, Class<?>) - Static method in class weka.core.InheritanceUtils: Checks whether the "otherclass" is a subclass of the given "superclass".
isSymmetric() - Method in class weka.core.Matrix: Deprecated.

Returns true if the matrix is symmetric.
isSymmetric() - Method in class weka.core.matrix.Matrix: Returns true if the matrix is symmetric.
isUndoEnabled() - Method in interface weka.core.Undoable: returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffPanel: returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffSortedTableModel: returns whether undo support is enabled
isUndoEnabled() - Method in class weka.gui.arffviewer.ArffTableModel: returns whether undo support is enabled
isUniform() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: checks, whether cluster type is uniform
isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Returns whether K2 prior is used
isUseK2Prior() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
isUseReasonCodes() - Method in class weka.core.pmml.jaxbbindings.Scorecard: Gets the value of the useReasonCodes property.
isUseVariant1() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Whether variant 1 is used
isVisible() - Method in class weka.gui.knowledgeflow.InvisibleNode: Returns true if this node is visible
isWrappedAlgorithm() - Method in class weka.gui.knowledgeflow.StepTreeLeafDetails: Returns true if this leaf represents a wrapped Weka algorithm (i.e.
Item - Class in weka.associations: Class that encapsulates information about an individual item.
Item(Attribute) - Constructor for class weka.associations.Item
Item - Class in weka.core.pmml.jaxbbindings: Java class for Item element declaration.
Item() - Constructor for class weka.core.pmml.jaxbbindings.Item
itemAt(int) - Method in class weka.associations.ItemSet: Gest the index of the value of the specified attribute
ItemRef - Class in weka.core.pmml.jaxbbindings: Java class for ItemRef element declaration.
ItemRef() - Constructor for class weka.core.pmml.jaxbbindings.ItemRef
items() - Method in class weka.associations.ItemSet: Gest the item set as an int array
ItemSet - Class in weka.associations: Class for storing a set of items.
ItemSet(int) - Constructor for class weka.associations.ItemSet: Constructor
ItemSet(int, int[]) - Constructor for class weka.associations.ItemSet: Constructor
ItemSet(int[]) - Constructor for class weka.associations.ItemSet: Contsructor
Itemset - Class in weka.core.pmml.jaxbbindings: Java class for Itemset element declaration.
Itemset() - Constructor for class weka.core.pmml.jaxbbindings.Itemset
itemStateChanged(ItemEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs the action associated with the ItemEvent.
IteratedLovinsStemmer - Class in weka.core.stemmers: An iterated version of the Lovins stemmer.
IteratedLovinsStemmer() - Constructor for class weka.core.stemmers.IteratedLovinsStemmer
IteratedSingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that build an ensemble from a single base learner.
IteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.IteratedSingleClassifierEnhancer
IterativeClassifier - Interface in weka.classifiers: Interface for classifiers that can induce models of growing complexity one step at a time.
IterativeClassifierOptimizer - Class in weka.classifiers.meta: Chooses the best number of iterations for an IterativeClassifier such as LogitBoost using cross-validation or a percentage split evaluation.
IterativeClassifierOptimizer() - Constructor for class weka.classifiers.meta.IterativeClassifierOptimizer
iterativeClassifierTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
iterator() - Method in class weka.core.Trie: Returns an iterator over the elements in this collection.
iterator() - Method in class weka.knowledgeflow.Flow: Get an Iterator over the Steps in this flow

J

J48 - Class in weka.classifiers.trees: Class for generating a pruned or unpruned C4.5 decision tree.
J48() - Constructor for class weka.classifiers.trees.J48
Jaccard - Class in weka.core.pmml.jaxbbindings: Java class for jaccard element declaration.
Jaccard() - Constructor for class weka.core.pmml.jaxbbindings.Jaccard
Java - Class in weka.gui.simplecli: Sets a variable.
Java() - Constructor for class weka.gui.simplecli.Java
Javadoc - Class in weka.core: Abstract superclass for classes that generate Javadoc comments and replace the content between certain comment tags.
Javadoc() - Constructor for class weka.core.Javadoc
JavaMacro - Class in weka.core.expressionlanguage.common: A macro declarations that exposes the java macro to a program.
JavaMacro() - Constructor for class weka.core.expressionlanguage.common.JavaMacro
JComponentWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a file.
JComponentWriter() - Constructor for class weka.gui.visualize.JComponentWriter: initializes the object
JComponentWriter(JComponent) - Constructor for class weka.gui.visualize.JComponentWriter: initializes the object with the given Component
JComponentWriter(JComponent, File) - Constructor for class weka.gui.visualize.JComponentWriter: initializes the object with the given Component and filename
JListHelper - Class in weka.gui: A helper class for JList GUI elements with DefaultListModel or derived models.
JListHelper() - Constructor for class weka.gui.JListHelper
Job - Class in weka.knowledgeflow.steps: Step that executes another flow as a "job".
Job() - Constructor for class weka.knowledgeflow.steps.Job
JobEnvironment - Class in weka.knowledgeflow: Extended Environment with support for storing results and property values to be set at a later date on the base schemes of WekaAlgorithmWrapper steps.
JobEnvironment() - Constructor for class weka.knowledgeflow.JobEnvironment: Constructor
JobEnvironment(Environment) - Constructor for class weka.knowledgeflow.JobEnvironment: Construct a JobEnvironment by copying the contents of a standard Environment
JobStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the Job step.
JobStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.JobStepEditorDialog
Join - Class in weka.gui.beans
Join() - Constructor for class weka.gui.beans.Join: Constructor
Join - Class in weka.knowledgeflow.steps: Step that performs an inner join on one or more key fields from two incoming batch or streaming datasets.
Join() - Constructor for class weka.knowledgeflow.steps.Join
JoinBeanInfo - Class in weka.gui.beans: BeanInfo for the Join step
JoinBeanInfo() - Constructor for class weka.gui.beans.JoinBeanInfo
JoinCustomizer - Class in weka.gui.beans: Customizer component for the Join step
JoinCustomizer() - Constructor for class weka.gui.beans.JoinCustomizer
joinOptions(String[]) - Static method in class weka.core.Utils: Joins all the options in an option array into a single string, as might be used on the command line.
JoinStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the Join step
JoinStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.JoinStepEditorDialog
JPEGWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a JPEG-file.
JPEGWriter() - Constructor for class weka.gui.visualize.JPEGWriter: initializes the object.
JPEGWriter(JComponent) - Constructor for class weka.gui.visualize.JPEGWriter: initializes the object with the given Component.
JPEGWriter(JComponent, File) - Constructor for class weka.gui.visualize.JPEGWriter: initializes the object with the given Component and filename.
JRip - Class in weka.classifiers.rules: This class implements a propositional rule learner, Repeated Incremental Pruning to Produce Error Reduction (RIPPER), which was proposed by William W.
JRip() - Constructor for class weka.classifiers.rules.JRip
JRip.Antd - Class in weka.classifiers.rules: The single antecedent in the rule, which is composed of an attribute and the corresponding value.
JRip.NominalAntd - Class in weka.classifiers.rules: The antecedent with nominal attribute
JRip.NumericAntd - Class in weka.classifiers.rules: The antecedent with numeric attribute
JRip.RipperRule - Class in weka.classifiers.rules: This class implements a single rule that predicts specified class.
JSONFlowLoader - Class in weka.knowledgeflow: Flow loader that wraps the routines in JSONFlowUtils
JSONFlowLoader() - Constructor for class weka.knowledgeflow.JSONFlowLoader
JSONFlowUtils - Class in weka.knowledgeflow: Utilities for building and saving flows from JSON data
JSONFlowUtils() - Constructor for class weka.knowledgeflow.JSONFlowUtils
JSONInstances - Class in weka.core.json: Class for transforming Instances objects into JSON objects and vice versa.
JSONInstances() - Constructor for class weka.core.json.JSONInstances
JSONLoader - Class in weka.core.converters: Reads a source that is in the JSON format.
It automatically decompresses the data if the extension is '.json.gz'.

For more information, see JSON homepage:
http://www.json.org/
JSONLoader() - Constructor for class weka.core.converters.JSONLoader
JSONNode - Class in weka.core.json: Container class for storing a JSON data structure.
JSONNode() - Constructor for class weka.core.json.JSONNode: Initializes the root container.
JSONNode(String, Boolean) - Constructor for class weka.core.json.JSONNode: Initializes the primitive container.
JSONNode(String, Integer) - Constructor for class weka.core.json.JSONNode: Initializes the primitive container.
JSONNode(String, Double) - Constructor for class weka.core.json.JSONNode: Initializes the primitive container.
JSONNode(String, String) - Constructor for class weka.core.json.JSONNode: Initializes the primitive container.
JSONNode.NodeType - Enum in weka.core.json: The type of a node.
JSONSaver - Class in weka.core.converters: Writes to a destination that is in JSON format.
The data can be compressed with gzip, in order to save space.

For more information, see JSON homepage:
http://www.json.org/
Valid options are:
JSONSaver() - Constructor for class weka.core.converters.JSONSaver: Constructor.
JSONToFlow(String) - Static method in class weka.knowledgeflow.Flow: Parse a Flow from the supplied JSON string
JSONToFlow(String, boolean) - Static method in class weka.knowledgeflow.Flow: Parse a Flow from the supplied JSON string
JSONToFlow(String, boolean) - Static method in class weka.knowledgeflow.JSONFlowUtils: Utility routine to deserialize a flow from the supplied JSON string
JTableHelper - Class in weka.gui: A helper class for JTable, e.g.
JTableHelper(JTable) - Constructor for class weka.gui.JTableHelper: initializes the object
JTreePopupMenu(JTree) - Constructor for class weka.gui.GenericObjectEditor.JTreePopupMenu: Constructs a new popup menu.
Jython - Class in weka.core.scripting: A helper class for Jython.
Jython() - Constructor for class weka.core.scripting.Jython: default constructor, tries to instantiate a Python Interpreter
JythonObject - Interface in weka.core.scripting: An indicator interface for Jython objects.
JythonPanel - Class in weka.gui.scripting: A scripting panel for Jython.
JythonPanel() - Constructor for class weka.gui.scripting.JythonPanel
JythonScript - Class in weka.gui.scripting: Represents a Jython script.
JythonScript() - Constructor for class weka.gui.scripting.JythonScript: Initializes the script.
JythonScript(Document) - Constructor for class weka.gui.scripting.JythonScript: Initializes the script.
JythonScript(Document, File) - Constructor for class weka.gui.scripting.JythonScript: Initializes the script.
JythonScript.JythonThread - Class in weka.gui.scripting: Executes a Jython script in a thread.
JythonSerializableObject - Interface in weka.core.scripting: An indicator interface for serializable Jython objects.
JythonThread(Script, String[]) - Constructor for class weka.gui.scripting.JythonScript.JythonThread: Initializes the thread.

K

K2 - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.

For more information see:

G.F.
K2() - Constructor for class weka.classifiers.bayes.net.search.global.K2
K2 - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses a hill climbing algorithm restricted by an order on the variables.

For more information see:

G.F.
K2() - Constructor for class weka.classifiers.bayes.net.search.local.K2
kappa() - Method in class weka.classifiers.evaluation.Evaluation: Returns value of kappa statistic if class is nominal.
kappa() - Method in class weka.classifiers.Evaluation: Returns value of kappa statistic if class is nominal.
KBInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the total Kononenko & Bratko Information score in bits.
KBInformation() - Method in class weka.classifiers.Evaluation: Return the total Kononenko & Bratko Information score in bits.
KBMeanInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the Kononenko & Bratko Information score in bits per instance.
KBMeanInformation() - Method in class weka.classifiers.Evaluation: Return the Kononenko & Bratko Information score in bits per instance.
KBRelativeInformation() - Method in class weka.classifiers.evaluation.Evaluation: Return the Kononenko & Bratko Relative Information score.
KBRelativeInformation() - Method in class weka.classifiers.Evaluation: Return the Kononenko & Bratko Relative Information score.
KDConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate kernel estimators for each discrete conditioning value).
KDConditionalEstimator() - Constructor for class weka.estimators.KDConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
KDConditionalEstimator(int, double) - Constructor for class weka.estimators.KDConditionalEstimator: Constructor
KDDataGenerator - Class in weka.gui.boundaryvisualizer: KDDataGenerator.
KDDataGenerator() - Constructor for class weka.gui.boundaryvisualizer.KDDataGenerator
KDTree - Class in weka.core.neighboursearch: Class implementing the KDTree search algorithm for nearest neighbour search.
The connection to dataset is only a reference.
KDTree() - Constructor for class weka.core.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTree(Instances) - Constructor for class weka.core.neighboursearch.KDTree: Creates a new instance of KDTree.
KDTreeNode - Class in weka.core.neighboursearch.kdtrees: A class representing a KDTree node.
KDTreeNode() - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][]) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode: Constructor.
KDTreeNode(int, int, int, double[][], double[][]) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNode
KDTreeNodeSplitter - Class in weka.core.neighboursearch.kdtrees: Class that splits up a KDTreeNode.
KDTreeNodeSplitter() - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: default constructor.
KDTreeNodeSplitter(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Creates a new instance of KDTreeNodeSplitter.
Kernel - Class in weka.classifiers.functions.supportVector: Abstract kernel.
Kernel() - Constructor for class weka.classifiers.functions.supportVector.Kernel
KernelEstimator - Class in weka.estimators: Simple kernel density estimator.
KernelEstimator() - Constructor for class weka.estimators.KernelEstimator: No-arg constructor needed to make WEKA's forName() work.
KernelEstimator(double) - Constructor for class weka.estimators.KernelEstimator: Constructor that takes a precision argument.
KernelEvaluation - Class in weka.classifiers.functions.supportVector: Class for evaluating Kernels.
KernelEvaluation() - Constructor for class weka.classifiers.functions.supportVector.KernelEvaluation: default constructor
kernelFactorExpressionTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
KernelFilter - Class in weka.filters.unsupervised.attribute: Converts the given set of data into a kernel matrix.
KernelFilter() - Constructor for class weka.filters.unsupervised.attribute.KernelFilter
kernelMatrixFileTipText() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.GaussianProcesses: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
kernelTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
kernelTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
key - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: attribute value
KEY_SPEC_SEPARATOR - Static variable in class weka.knowledgeflow.steps.Join: Separator used to separate first and second input key specifications
keyFieldNameTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
keys() - Method in class weka.core.xml.MethodHandler: returns an enumeration over all currently stored custom methods, i.e.
keysTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
KF_BUILTIN_TEMPLATE_KEY - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Group identifier for built-in knowledge flow templates
KF_PLUGIN_TEMPLATE_KEY - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Group identifier for plugin knowledge flow templates - packages supplying templates should use this
KFDefaults - Class in weka.knowledgeflow: Default settings for the Knowledge Flow
KFDefaults() - Constructor for class weka.knowledgeflow.KFDefaults
KFGraphicalEnvironmentCommandHandler - Class in weka.gui.knowledgeflow: Default Knowledge Flow graphical command handler
KFGraphicalEnvironmentCommandHandler(MainKFPerspective) - Constructor for class weka.gui.knowledgeflow.KFGraphicalEnvironmentCommandHandler: Constructor
KFGUIConsts - Class in weka.gui.knowledgeflow: Class that holds constants that are used within the GUI side of the Knowledge Flow.
KFGUIConsts() - Constructor for class weka.gui.knowledgeflow.KFGUIConsts
KFIgnore - Annotation Type in weka.gui.beans: Marker annotation.
kFoldCV(BayesNet, int) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: kFoldCV uses k-fold cross validation to measure the accuracy of a Bayes network classifier.
KFStep - Annotation Type in weka.gui.beans: Optional annotation for plugin beans in the Knowledge Flow.
KFStep - Annotation Type in weka.knowledgeflow.steps: KFStep class annotation
Kill - Class in weka.gui.simplecli: Kills the running process.
Kill() - Constructor for class weka.gui.simplecli.Kill
KKConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a numeric domain.
KKConditionalEstimator() - Constructor for class weka.estimators.KKConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
KKConditionalEstimator(double) - Constructor for class weka.estimators.KKConditionalEstimator: Constructor
KMEANS_PLUS_PLUS - Static variable in class weka.clusterers.SimpleKMeans
KMeansInpiredMethod - Class in weka.core.neighboursearch.kdtrees: The class that splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.

For more information see also:

Ashraf Masood Kibriya (2007).
KMeansInpiredMethod() - Constructor for class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.BallTree: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.CoverTree: Returns k-NNs of a given target instance, from among the previously supplied training instances (supplied through setInstances method) P.S.: May return more than k-NNs if more one instances have the same distance to the target as the kth NN.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the nearest neighbours for the given instance based on distance measured in the filtered space.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.KDTree: Returns the k nearest neighbours of the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.LinearNNSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
kNearestNeighbours(Instance, int) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns k nearest instances in the current neighbourhood to the supplied instance.
KNNInput - Class in weka.core.pmml.jaxbbindings: Java class for KNNInput element declaration.
KNNInput() - Constructor for class weka.core.pmml.jaxbbindings.KNNInput
KNNInputs - Class in weka.core.pmml.jaxbbindings: Java class for KNNInputs element declaration.
KNNInputs() - Constructor for class weka.core.pmml.jaxbbindings.KNNInputs
KNNTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
KNNTipText() - Method in class weka.classifiers.lazy.LWL: Returns the tip text for this property.
KnowledgeFlow - Class in weka.gui.beans: Startup class for the KnowledgeFlow.
KnowledgeFlow() - Constructor for class weka.gui.beans.KnowledgeFlow
KnowledgeFlow - Class in weka.gui.knowledgeflow: Launcher class for the Weka Knowledge Flow.
KnowledgeFlow() - Constructor for class weka.gui.knowledgeflow.KnowledgeFlow
KnowledgeFlowApp - Class in weka.gui.beans: Main GUI class for the KnowledgeFlow.
KnowledgeFlowApp(boolean) - Constructor for class weka.gui.beans.KnowledgeFlowApp: Creates a new KnowledgeFlowApp instance.
KnowledgeFlowApp - Class in weka.gui.knowledgeflow: Main Knowledge Flow application class
KnowledgeFlowApp() - Constructor for class weka.gui.knowledgeflow.KnowledgeFlowApp: Constructor
KnowledgeFlowApp(boolean) - Constructor for class weka.gui.knowledgeflow.KnowledgeFlowApp: Constructor
KnowledgeFlowApp.KFPerspective - Interface in weka.gui.beans: Interface for perspectives.
KnowledgeFlowApp.KnowledgeFlowGeneralDefaults - Class in weka.gui.knowledgeflow: General default settings for the Knowledge Flow
KnowledgeFlowApp.MainKFPerspective - Class in weka.gui.beans: Main Knowledge Flow perspective
KnowledgeFlowGeneralDefaults() - Constructor for class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults
KohonenMap - Class in weka.core.pmml.jaxbbindings: Java class for KohonenMap element declaration.
KohonenMap() - Constructor for class weka.core.pmml.jaxbbindings.KohonenMap
KOML - Class in weka.core.xml: This class is a helper class for XML serialization using KOML .
KOML() - Constructor for class weka.core.xml.KOML
komlToBinary(String, String) - Static method in class weka.core.xml.SerialUIDChanger: converts a KOML file into a binary one
KOMLV - Static variable in class weka.gui.beans.SerializedModelSaver
KStar - Class in weka.classifiers.lazy: K* is an instance-based classifier, that is the class of a test instance is based upon the class of those training instances similar to it, as determined by some similarity function.
KStar() - Constructor for class weka.classifiers.lazy.KStar
KStarCache - Class in weka.classifiers.lazy.kstar: A class representing the caching system used to keep track of each attribute value and its corresponding scale factor or stop parameter.
KStarCache() - Constructor for class weka.classifiers.lazy.kstar.KStarCache
KStarCache.CacheTable - Class in weka.classifiers.lazy.kstar: A custom hashtable class to support the caching system.
KStarCache.TableEntry - Class in weka.classifiers.lazy.kstar: Hashtable collision list.
KStarConstants - Interface in weka.classifiers.lazy.kstar
KStarNominalAttribute - Class in weka.classifiers.lazy.kstar: A custom class which provides the environment for computing the transformation probability of a specified test instance nominal attribute to a specified train instance nominal attribute.
KStarNominalAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNominalAttribute: Constructor
KStarNumericAttribute - Class in weka.classifiers.lazy.kstar: A custom class which provides the environment for computing the transformation probability of a specified test instance numeric attribute to a specified train instance numeric attribute.
KStarNumericAttribute(Instance, Instance, int, Instances, int[][], KStarCache) - Constructor for class weka.classifiers.lazy.kstar.KStarNumericAttribute: Constructor
KStarWrapper - Class in weka.classifiers.lazy.kstar
KStarWrapper() - Constructor for class weka.classifiers.lazy.kstar.KStarWrapper
kthSmallestValue(Attribute, int) - Method in class weka.core.Instances: Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int, int) - Method in class weka.core.Instances: Returns the kth-smallest attribute value of a numeric attribute.
kthSmallestValue(int[], int) - Static method in class weka.core.Utils: Returns the kth-smallest value in the array.
kthSmallestValue(double[], int) - Static method in class weka.core.Utils: Returns the kth-smallest value in the array
KValueTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property

L

LabeledItemSet - Class in weka.associations: Class for storing a set of items together with a class label.
LabeledItemSet(int, int) - Constructor for class weka.associations.LabeledItemSet: Constructor
LABELS - Static variable in class weka.core.json.JSONInstances: the labels attribute.
labelsTipText() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the tip text for this property
labelTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the tip text for this property.
LAF - Static variable in class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults
LAF - Static variable in class weka.knowledgeflow.KFDefaults
LAF_KEY - Static variable in class weka.gui.knowledgeflow.KnowledgeFlowApp.KnowledgeFlowGeneralDefaults
LAGDHillClimber - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses a Look Ahead Hill Climbing algorithm called LAGD Hill Climbing.
LAGDHillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.LAGDHillClimber
lambdaTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
lambdaTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
lambdaTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
laplaceProb(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns relative frequency of class over all bags with Laplace correction.
laplaceProb(int, int) - Method in class weka.classifiers.trees.j48.Distribution: Returns relative frequency of class for given bag.
last() - Method in class weka.core.neighboursearch.covertrees.Stack: Returns the last element in the stack.
LAST - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner: use the last attribute as class.
lastActionMsg() - Method in class weka.classifiers.bayes.net.EditableBayesNet: get message representing the last action performed on the network
lastElement() - Method in class weka.core.FastVector: Deprecated.

Returns the last element of the vector.
lastElement() - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the last component of the list.
lastIndexOf(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns the index of the last occurrence of elem.
lastIndexOf(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Searches backwards for elem, starting from the specified index, and returns an index to it.
lastInstance() - Method in class weka.core.Instances: Returns the last instance in the set.
launch() - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin: Gets called when the user clicks the button or selects this plugin's entry from the popup menu.
launch() - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin: Gets called when the user clicks the button or selects this plugin's entry from the popup menu.
launchNext(int, int) - Method in class weka.experiment.RemoteExperiment: Launch a sub experiment on a remote host
LAYOUT_COLOR - Static variable in class weka.knowledgeflow.KFDefaults
LAYOUT_COLOR_KEY - Static variable in class weka.knowledgeflow.KFDefaults
LAYOUT_HEIGHT - Static variable in class weka.knowledgeflow.KFDefaults
LAYOUT_HEIGHT_KEY - Static variable in class weka.knowledgeflow.KFDefaults
LAYOUT_WIDTH - Static variable in class weka.knowledgeflow.KFDefaults
LAYOUT_WIDTH_KEY - Static variable in class weka.knowledgeflow.KFDefaults
layoutCompleted(LayoutCompleteEvent) - Method in class weka.classifiers.bayes.net.GUI: This method is an implementation for LayoutCompleteEventListener class.
layoutCompleted(LayoutCompleteEvent) - Method in class weka.gui.graphvisualizer.GraphVisualizer: This method is an implementation for LayoutCompleteEventListener class.
layoutCompleted(LayoutCompleteEvent) - Method in interface weka.gui.graphvisualizer.LayoutCompleteEventListener
LayoutCompleteEvent - Class in weka.gui.graphvisualizer: This is an event which is fired by a LayoutEngine once a LayoutEngine finishes laying out the graph, so that the Visualizer can repaint the screen to show the changes.
LayoutCompleteEvent(Object) - Constructor for class weka.gui.graphvisualizer.LayoutCompleteEvent
LayoutCompleteEventListener - Interface in weka.gui.graphvisualizer: This interface should be implemented by any class which needs to receive LayoutCompleteEvents from the LayoutEngine.
layoutEditor() - Method in class weka.gui.knowledgeflow.steps.BlockStepEditorDialog: Layout the component
layoutEditor() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterStepEditorDialog: Layout the editor
layoutEditor() - Method in class weka.gui.knowledgeflow.steps.JobStepEditorDialog: Layout the custom part of the editor
layoutEditor() - Method in class weka.gui.knowledgeflow.steps.NoteEditorDialog: Layout the note editor
LayoutEngine - Interface in weka.gui.graphvisualizer: This interface class has been added to facilitate the addition of other layout engines to this package.
layoutGraph(ArrayList<Integer>, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: set positions of all nodes
layoutGraph() - Method in class weka.gui.graphvisualizer.GraphVisualizer: This method lays out the graph by calling the LayoutEngine's layoutGraph() method.
layoutGraph() - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: This method does a complete layout of the graph which includes removing cycles, assigning levels to nodes, reducing edge crossings and laying out the vertices horizontally for better visibility.
layoutGraph() - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method lays out the graph for better visualization
LayoutPanel - Class in weka.gui.knowledgeflow: Provides a panel just for laying out a Knowledge Flow graph.
LayoutPanel(VisibleLayout) - Constructor for class weka.gui.knowledgeflow.LayoutPanel: Constructor
lbl - Variable in class weka.gui.graphvisualizer.GraphNode: ID and label for the node
LCURLY - Static variable in interface weka.core.json.sym
LE - Static variable in interface weka.core.expressionlanguage.parser.sym
LEAF_MAJ_CLASS - Static variable in class weka.classifiers.trees.HoeffdingTree
LEAF_NB - Static variable in class weka.classifiers.trees.HoeffdingTree
LEAF_NB_ADAPTIVE - Static variable in class weka.classifiers.trees.HoeffdingTree
leafForInstance(Instance, SplitNode, String) - Method in class weka.classifiers.trees.ht.HNode: Return the leaf that the supplied instance ends up at
leafForInstance(Instance, SplitNode, String) - Method in class weka.classifiers.trees.ht.SplitNode
LeafNode - Class in weka.classifiers.trees.ht: Leaf node in a HoeffdingTree
LeafNode() - Constructor for class weka.classifiers.trees.ht.LeafNode: Construct an empty leaf node
LeafNode(HNode, SplitNode, String) - Constructor for class weka.classifiers.trees.ht.LeafNode: Construct a leaf node with the given actual node, parent and parent branch
leafPredictionStrategyTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
LearningNode - Interface in weka.classifiers.trees.ht: Marker interface for a node that can be updated with incoming instances in a HoeffdingTree.
LearningRateResultProducer - Class in weka.experiment: Tells a sub-ResultProducer to reproduce the current run for varying sized subsamples of the dataset.
LearningRateResultProducer() - Constructor for class weka.experiment.LearningRateResultProducer
learningRateTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
learningRateTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
learningRateTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
leaveOneAttributeOutTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Tip text for this property
leaveOneOutCV(BayesNet) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: LeaveOneOutCV returns the accuracy calculated using Leave One Out cross validation.
LED24 - Class in weka.datagenerators.classifiers.classification: This generator produces data for a display with 7 LEDs.
LED24() - Constructor for class weka.datagenerators.classifiers.classification.LED24: initializes the generator with default values
LEFT_PARENTHESES - Variable in class weka.experiment.ResultMatrix: the left parentheses for enumerating cols/rows.
leftNode() - Method in class weka.classifiers.trees.m5.RuleNode: Get the left child of this node
leftSide(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Prints left side of condition.
leftSide(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints left side of condition satisfied by instances.
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Does nothing because no condition has to be satisfied.
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Prints left side of condition..
leftSide(Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Does nothing because no condition has to be satisfied.
leftSide(Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Returns name of splitting attribute (left side of condition).
LegacyFlowLoader - Class in weka.knowledgeflow: Flow loader that reads legacy .kfml files and translates them to the new implementation.
LegacyFlowLoader() - Constructor for class weka.knowledgeflow.LegacyFlowLoader: Constructor
LegendPanel - Class in weka.gui.visualize: This panel displays legends for a list of plots.
LegendPanel() - Constructor for class weka.gui.visualize.LegendPanel: Constructor
length - Variable in class weka.core.neighboursearch.covertrees.Stack: The number of elements in the stack.
lessEqual(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '<=' less equal operator
lessThan(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '<' less than operator
Level - Class in weka.core.pmml.jaxbbindings: Java class for Level element declaration.
Level() - Constructor for class weka.core.pmml.jaxbbindings.Level
leverageForRule(AprioriItemSet, AprioriItemSet, int, int) - Method in class weka.associations.AprioriItemSet: Outputs the leverage for a rule.
LibSVMLoader - Class in weka.core.converters: Reads a source that is in libsvm format.

For more information about libsvm see:

http://www.csie.ntu.edu.tw/~cjlin/libsvm/
LibSVMLoader() - Constructor for class weka.core.converters.LibSVMLoader
LibSVMSaver - Class in weka.core.converters: Writes to a destination that is in libsvm format.

For more information about libsvm see:

http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Valid options are:
LibSVMSaver() - Constructor for class weka.core.converters.LibSVMSaver: Constructor
LIFT_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Lift
LiftData - Class in weka.core.pmml.jaxbbindings: Java class for LiftData element declaration.
LiftData() - Constructor for class weka.core.pmml.jaxbbindings.LiftData
liftForRule(AprioriItemSet, AprioriItemSet, int) - Method in class weka.associations.AprioriItemSet: Outputs the lift for a rule.
LiftGraph - Class in weka.core.pmml.jaxbbindings: Java class for LiftGraph element declaration.
LiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.LiftGraph
likelihoodThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
LINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
LINEAR - Static variable in class weka.classifiers.lazy.LWL: The available kernel weighting methods.
LinearKernelType - Class in weka.core.pmml.jaxbbindings: Java class for LinearKernelType element declaration.
LinearKernelType() - Constructor for class weka.core.pmml.jaxbbindings.LinearKernelType
LinearNNSearch - Class in weka.core.neighboursearch: Class implementing the brute force search algorithm for nearest neighbour search.
LinearNNSearch() - Constructor for class weka.core.neighboursearch.LinearNNSearch: Constructor.
LinearNNSearch(Instances) - Constructor for class weka.core.neighboursearch.LinearNNSearch: Constructor that uses the supplied set of instances.
LinearNorm - Class in weka.core.pmml.jaxbbindings: Java class for LinearNorm element declaration.
LinearNorm() - Constructor for class weka.core.pmml.jaxbbindings.LinearNorm
LinearRegression - Class in weka.classifiers.functions: Class for using linear regression for prediction.
LinearRegression() - Constructor for class weka.classifiers.functions.LinearRegression
LinearRegression - Class in weka.core.matrix: Class for performing (ridged) linear regression using Tikhonov regularization.
LinearRegression(Matrix, Matrix, double) - Constructor for class weka.core.matrix.LinearRegression: Performs a (ridged) linear regression.
LinearRegression(Matrix, Matrix, double[], double) - Constructor for class weka.core.matrix.LinearRegression: Performs a weighted (ridged) linear regression.
LinearUnit - Class in weka.classifiers.functions.neural: This can be used by the neuralnode to perform all it's computations (as a Linear unit).
LinearUnit() - Constructor for class weka.classifiers.functions.neural.LinearUnit
lineWrap(String, int) - Static method in class weka.core.Utils: Implements simple line breaking.
Link2(Object[], double) - Constructor for class weka.attributeSelection.BestFirst.Link2: Constructor
LinkedList2(int) - Constructor for class weka.attributeSelection.BestFirst.LinkedList2
LINKFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for LINK-FUNCTION.
linkTypeTipText() - Method in class weka.clusterers.HierarchicalClusterer
LINUX_BROWSERS - Static variable in class weka.gui.BrowserHelper: Linux/Unix binaries to look for
listCapabilities() - Method in class weka.core.Capabilities: returns a comma-separated list of all the capabilities, excluding interface-based ones.
listCapabilities(Capabilities) - Static method in class weka.core.CapabilitiesUtils: returns a comma-separated list of all the capabilities, excluding interface-based ones.
listMetaStoreEntries(String) - Method in interface weka.core.metastore.MetaStore: Get a list of all entries in a named store
listMetaStoreEntries(String, String) - Method in interface weka.core.metastore.MetaStore: Get a list of all named entries starting with the given prefix
listMetaStoreEntries(String) - Method in class weka.core.metastore.XMLFileBasedMetaStore
listMetaStoreEntries(String, String) - Method in class weka.core.metastore.XMLFileBasedMetaStore
listMetaStores() - Method in interface weka.core.metastore.MetaStore: Get a list of all named meta stores
listMetaStores() - Method in class weka.core.metastore.XMLFileBasedMetaStore
listOptions() - Method in class weka.associations.AbstractAssociator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.Apriori: Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.CheckAssociator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.FilteredAssociator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.FPGrowth: Returns an enumeration describing the available options.
listOptions() - Method in class weka.associations.SingleAssociatorEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ASEvaluation: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ASSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.BestFirst: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.CfsSubsetEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.CheckAttributeSelection: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.CorrelationAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GainRatioAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.GreedyStepwise: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.OneRAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.PrincipalComponents: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.Ranker: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.AbstractClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.BayesNet: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.NaiveBayes: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.K2: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.global.TAN: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.K2: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.local.TAN: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.BVDecompose: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.CheckClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.CheckSource: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns an enumeration of all the available options..
listOptions() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns an enumeration of all the available options..
listOptions() - Method in class weka.classifiers.functions.GaussianProcesses: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.LinearRegression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.Logistic: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.MultilayerPerceptron: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SGD: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SGDText: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SimpleLogistic: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SMO: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.SMOreg: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.CheckKernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.Puk: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.supportVector.RegSMO: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.functions.VotedPerceptron: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.IBk: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.KStar: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.lazy.LWL: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AdaBoostM1: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AdditiveRegression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Bagging: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.CVParameterSelection: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.FilteredClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.LogitBoost: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.MultiClassClassifier: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.meta.MultiScheme: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.RandomSubSpace: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Stacking: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.Vote: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.misc.SerializedClassifier: Gets an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.MultipleClassifiersCombiner: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableClassifier: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.rules.DecisionTable: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.rules.JRip: Returns an enumeration describing the available options Valid options are:
listOptions() - Method in class weka.classifiers.rules.OneR: Returns an enumeration describing the available options..
listOptions() - Method in class weka.classifiers.rules.PART: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.SingleClassifierEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.HoeffdingTree: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.J48: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.LMT: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.m5.M5Base: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.M5P: Returns an enumeration describing the available options
listOptions() - Method in class weka.classifiers.trees.RandomForest: Returns an enumeration describing the available options.
listOptions() - Method in class weka.classifiers.trees.RandomTree: Lists the command-line options for this classifier.
listOptions() - Method in class weka.classifiers.trees.REPTree: Lists the command-line options for this classifier.
listOptions() - Method in class weka.clusterers.AbstractClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.Canopy: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.CheckClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.Cobweb: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.EM: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.FarthestFirst: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.FilteredClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.HierarchicalClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.clusterers.RandomizableClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.SimpleKMeans: Returns an enumeration describing the available options.
listOptions() - Method in class weka.clusterers.SingleClustererEnhancer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.Check: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.CheckGOE: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.CheckOptionHandler: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.CheckScheme: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.AbstractFileSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.ArffSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.C45Saver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.CSVLoader
listOptions() - Method in class weka.core.converters.CSVSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.DatabaseLoader: Lists the available options
listOptions() - Method in class weka.core.converters.DatabaseSaver: Lists the available options.
listOptions() - Method in class weka.core.converters.JSONSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.LibSVMSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.MatlabSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.SVMLightSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.converters.TextDirectoryLoader: Lists the available options
listOptions() - Method in class weka.core.converters.XRFFSaver: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.DictionaryBuilder: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.FilteredDistance: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.FindWithCapabilities: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.Javadoc: Returns an enumeration describing the available options.
ListOptions - Class in weka.core: Lists the options of an OptionHandler
ListOptions() - Constructor for class weka.core.ListOptions
listOptions() - Method in class weka.core.ListOptions: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.MinkowskiDistance: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.BallTree: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.CoverTree: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.KDTree: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.LinearNNSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.NormalizableDistance: Returns an enumeration describing the available options.
listOptions() - Method in interface weka.core.OptionHandler: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.OptionHandlerJavadoc: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.stemmers.SnowballStemmer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.stopwords.AbstractFileBasedStopwords: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.stopwords.AbstractStopwords: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.stopwords.MultiStopwords: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.TechnicalInformationHandlerJavadoc: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.TestInstances: Returns an enumeration describing the available options.
listOptions() - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.tokenizers.NGramTokenizer: Returns an enumeration of all the available options..
listOptions() - Method in class weka.core.tokenizers.Tokenizer: Returns an enumeration of all the available options..
listOptions() - Method in class weka.datagenerators.ClassificationGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.LED24: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.regression.Expression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.ClusterGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.DataGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.datagenerators.RegressionGenerator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.estimators.CheckEstimator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.estimators.Estimator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns an enumeration that lists the command-line options that are available
listOptions() - Method in class weka.experiment.AveragingResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CrossValidationResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.CSVResultListener: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.DatabaseResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.experiment.Experiment: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.InstanceQuery: Returns an enumeration describing the available options
listOptions() - Method in class weka.experiment.LearningRateResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.PairedTTester: Lists options understood by this object.
listOptions() - Method in class weka.experiment.RandomSplitResultProducer: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.RegressionSplitEvaluator: Returns an enumeration describing the available options..
listOptions() - Method in class weka.experiment.ResultMatrix: Returns an enumeration of all the available options..
listOptions() - Method in class weka.filters.CheckSource: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.Filter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.MultiFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.AddClassification: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.Discretize: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.attribute.PartitionMembership: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.Resample: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Add: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddID: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns an enumeration describing the available options
listOptions() - Method in class weka.filters.unsupervised.attribute.AddUserFields: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Returns an enumeration describing the available options
listOptions() - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Copy: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Discretize: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.FirstOrder: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MathExpression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NominalToString: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericToDate: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.Remove: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveByName: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
listOptions() - Method in class weka.filters.unsupervised.attribute.Reorder: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
listOptions() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Gets an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.StringToNominal: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.attribute.SwapValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Randomize: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Gets an enumeration describing the available options..
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveRange: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.Resample: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns an enumeration describing the available options.
listOptions() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Returns an enumeration describing the available options.
listOptions() - Method in class weka.gui.explorer.AbstractPlotInstances: Returns an enumeration of all the available options.
listOptions() - Method in class weka.gui.Main: Gets an enumeration describing the available options.
listOptions() - Method in class weka.gui.scripting.Script: Returns an enumeration describing the available options.
listOptionsForClass(Class<?>) - Static method in class weka.core.Option: Gets a list of options for the supplied class.
listOptionsForClassHierarchy(Class<?>, Class<?>) - Static method in class weka.core.Option: Get a list of options for a class.
ListSelectorDialog - Class in weka.gui: A dialog to present the user with a list of items, that the user can make a selection from, or cancel the selection.
ListSelectorDialog(Window, JList) - Constructor for class weka.gui.ListSelectorDialog: Create the list selection dialog.
listStemmers() - Static method in class weka.core.stemmers.SnowballStemmer: returns an enumeration over all currently stored stemmer names.
LMT - Class in weka.classifiers.trees: Classifier for building 'logistic model trees', which are classification trees with logistic regression functions at the leaves.
LMT() - Constructor for class weka.classifiers.trees.LMT: Creates an instance of LMT with standard options
LMTNode - Class in weka.classifiers.trees.lmt: Class for logistic model tree structure.
LMTNode(ModelSelection, int, boolean, boolean, int, double, boolean, NominalToBinary, int) - Constructor for class weka.classifiers.trees.lmt.LMTNode: Constructor for logistic model tree node.
lnFactorial(double) - Static method in class weka.core.SpecialFunctions: Returns natural logarithm of factorial using gamma function.
lnFunc(double) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit: Help method for computing entropy.
lnFunc(double) - Static method in class weka.core.ContingencyTables: Help method for computing entropy.
lnGamma(double) - Static method in class weka.core.Statistics: Returns natural logarithm of gamma function.
LNormTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
LNormTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
lnsrch(double[], double[], double[], double, boolean[], double[][], Optimization.DynamicIntArray) - Method in class weka.core.Optimization: Find a new point x in the direction p from a point xold at which the value of the function has decreased sufficiently, the positive definiteness of B matrix (approximation of the inverse of the Hessian) is preserved and no bound constraints are violated.
load(InputStream) - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
load(String) - Method in class weka.gui.beans.FlowRunner: Load a serialized KnowledgeFlow (either binary or xml)
load(File) - Static method in class weka.gui.scripting.ScriptUtils: Tries to load the file and return its content.
loadBinary(String) - Method in class weka.gui.beans.FlowRunner: Load a binary serialized KnowledgeFlow
loadCheck(Package, File, PrintStream...) - Static method in class weka.core.WekaPackageManager: Check whether a package should be loaded or not.
loadDictionary(String, boolean) - Method in class weka.core.DictionaryBuilder: Load a dictionary from a file
loadDictionary(File, boolean) - Method in class weka.core.DictionaryBuilder: Load a dictionary from a file
loadDictionary(Reader) - Method in class weka.core.DictionaryBuilder: Load a textual dictionary from a reader
loadDictionary(InputStream) - Method in class weka.core.DictionaryBuilder: Load a binary dictionary from an input stream
Loader - Interface in weka.core.converters: Interface to something that can load Instances from an input source in some format.
Loader - Class in weka.gui.beans: Loads data sets using weka.core.converter classes
Loader() - Constructor for class weka.gui.beans.Loader
Loader - Class in weka.gui: This class is for loading resources from a JAR archive.
Loader(String) - Constructor for class weka.gui.Loader: initializes the object
LOADER - Static variable in class weka.knowledgeflow.JSONFlowUtils
Loader - Class in weka.knowledgeflow.steps: Knowledge Flow step that wraps weka.core.converters.Loaders.
Loader() - Constructor for class weka.knowledgeflow.steps.Loader
Loader.StructureNotReadyException - Exception in weka.core.converters: Exception that implementers can throw from getStructure() when they have not been configured sufficiently in order to read the structure (or data).
LOADER_DIALOG - Static variable in class weka.gui.ConverterFileChooser: the loader dialog.
LoaderBeanInfo - Class in weka.gui.beans: Bean info class for the loader bean
LoaderBeanInfo() - Constructor for class weka.gui.beans.LoaderBeanInfo
LoaderCustomizer - Class in weka.gui.beans: GUI Customizer for the loader bean
LoaderCustomizer() - Constructor for class weka.gui.beans.LoaderCustomizer
LoaderStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Provides a custom editor dialog for Loaders.
LoaderStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.LoaderStepEditorDialog: Constructor
loadFile(String, AbstractFileLoader...) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: loads the specified file
loadFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: loads the specified file into the table
loadFlow(File, Logger) - Static method in class weka.knowledgeflow.Flow: Utility method to load a flow from a file
loadFlow(InputStream, FlowLoader) - Static method in class weka.knowledgeflow.Flow: Utility method to load a flow from the supplied input stream using the supplied FlowLoader
loadFlow(Reader, FlowLoader) - Static method in class weka.knowledgeflow.Flow: Utility method to load a flow from the supplied reader using the supplied FlowLoader
loadFromFile(String) - Static method in class weka.core.Debug: deserializes the content of the file and returns it, null if an error occurred.
loadIcon(String) - Static method in class weka.gui.knowledgeflow.StepVisual: Load an icon from the supplied path
loadIcon(ClassLoader, String) - Static method in class weka.gui.knowledgeflow.StepVisual: Load an icon from the supplied path
loadIcons(String, String) - Method in class weka.gui.beans.BeanVisual: Loads static and animated versions of a beans icons.
loadLayout(File, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp: Load a layout from a file.
loadLayout(InputStream, boolean, String) - Method in class weka.gui.beans.KnowledgeFlowApp: Load a flow file from an input stream.
loadLayout(Reader, boolean, String) - Method in class weka.gui.beans.KnowledgeFlowApp: Load a flow file from a reader.
loadLayout() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Load a flow layout.
loadLayout(File, boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Load a flow layout.
loadModel() - Method in class weka.gui.beans.Classifier
loadModel() - Method in class weka.gui.beans.Clusterer
loadPackages(boolean) - Static method in class weka.core.WekaPackageManager: Load all packages
loadPackages(boolean, boolean, boolean) - Static method in class weka.core.WekaPackageManager: Load all packages
loadProperties() - Static method in class weka.gui.beans.BeansProperties: Loads KnowledgeFlow properties and any plugins (adds jars to the classpath)
loadProperties() - Static method in class weka.gui.beans.KnowledgeFlowApp: Loads KnowledgeFlow properties and any plugins (adds jars to the classpath)
loadSettings() - Method in class weka.core.Settings: Load the settings with ID m_ID from store m_storeName.
loadXML(String) - Method in class weka.gui.beans.FlowRunner: Load an XML serialized KnowledgeFlow
locallyPredictiveTipText() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the tip text for this property
LocalScoreSearchAlgorithm - Class in weka.classifiers.bayes.net.search.local: The ScoreBasedSearchAlgorithm class supports Bayes net structure search algorithms that are based on maximizing scores (as opposed to for example conditional independence based search algorithms).
LocalScoreSearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: default constructor
LocalScoreSearchAlgorithm(BayesNet, Instances) - Constructor for class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: constructor
LocalTransformations - Class in weka.core.pmml.jaxbbindings: Java class for LocalTransformations element declaration.
LocalTransformations() - Constructor for class weka.core.pmml.jaxbbindings.LocalTransformations
locateIndex(int) - Method in class weka.core.pmml.SparseArray: Locates the greatest index that is not greater than the given index.
locateIndex(int) - Method in class weka.core.SparseInstance: Locates the greatest index that is not greater than the given index.
log(String) - Method in class weka.core.Debug: prints the given message with level INFO
log(Level, String) - Method in class weka.core.Debug: prints the given message with the specified level and an empty sourceclass
log(Level, String, String) - Method in class weka.core.Debug: prints the given message with the specified level
log(Level, String, String, String) - Method in class weka.core.Debug: prints the given message with the specified level
Log() - Constructor for class weka.core.Debug.Log: default constructor, uses only stdout
Log(String) - Constructor for class weka.core.Debug.Log: creates a logger that logs into the specified file, if null then only stdout is used.
Log(String, int, int) - Constructor for class weka.core.Debug.Log: creates a logger that logs into the specified file, if null then only stdout is used.
log(Level, String) - Method in class weka.core.Debug.Log: logs the given message
log(Level, String, String) - Method in class weka.core.Debug.Log: prints the given message with the specified level
log(Level, String, String, String) - Method in class weka.core.Debug.Log: prints the given message with the specified level
log(String) - Method in class weka.core.Debug.SimpleLog: logs the given message to the file
log(Logger.Level, String) - Static method in class weka.core.logging.Logger: Logs the given message under the given level.
log(Logger.Level, Throwable) - Static method in class weka.core.logging.Logger: Logs the given message under the given level.
log(String, LoggingLevel) - Method in class weka.knowledgeflow.LogManager: Log a message at the supplied level
log(String, LoggingLevel) - Method in interface weka.knowledgeflow.StepManager: Write a message to the log at the given logging level
log(String, LoggingLevel) - Method in class weka.knowledgeflow.StepManagerImpl: Log a message at the supplied logging level
LOG2 - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
log2 - Static variable in class weka.core.ContingencyTables: The natural logarithm of 2
log2 - Static variable in class weka.core.Utils: The natural logarithm of 2.
log2(double) - Static method in class weka.core.Utils: Returns the logarithm of a for base 2.
log2Binomial(double, double) - Static method in class weka.core.SpecialFunctions: Returns base 2 logarithm of binomial coefficient using gamma function.
log2Multinomial(double, double[]) - Static method in class weka.core.SpecialFunctions: Returns base 2 logarithm of multinomial using gamma function.
log2MultipleHypergeometric(double[][]) - Static method in class weka.core.ContingencyTables: Returns negative base 2 logarithm of multiple hypergeometric probability for a contingency table.
Log2PI - Static variable in class weka.estimators.MultivariateGaussianEstimator: Log of twice the number pi: log(2*pi).
logBasic(String) - Method in class weka.knowledgeflow.LogManager: Log at the basic level
logBasic(String) - Method in interface weka.knowledgeflow.StepManager: Log a message at the "basic" level
logBasic(String) - Method in class weka.knowledgeflow.StepManagerImpl: Log a message at the basic logging level
logDebug(String) - Method in class weka.knowledgeflow.LogManager: Log at the debugging level
logDebug(String) - Method in interface weka.knowledgeflow.StepManager: Log a message at the "debug" level
logDebug(String) - Method in class weka.knowledgeflow.StepManagerImpl: Log a message at the debugging logging level
logDensity(Instance, double) - Method in interface weka.classifiers.ConditionalDensityEstimator: Returns natural logarithm of density estimate for given value based on given instance.
logDensity(Instance, double) - Method in class weka.classifiers.functions.GaussianProcesses: Returns natural logarithm of density estimate for given value based on given instance.
logDensity(Instance, double) - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns natural logarithm of density estimate for given value based on given instance.
logDensity(double[]) - Method in interface weka.estimators.MultivariateEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensity(double[]) - Method in class weka.estimators.MultivariateGaussianEstimator: Returns the log of the density value for the given vector.
logDensity(double) - Method in interface weka.estimators.UnivariateDensityEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensity(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensity(double) - Method in class weka.estimators.UnivariateKernelEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensity(double) - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensity(double) - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Computes log of density for given value.
logDensity(double) - Method in class weka.estimators.UnivariateNormalEstimator: Returns the natural logarithm of the density estimate at the given point.
logDensityForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer: Computes the density for a given instance.
logDensityForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer: Computes the density for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer: Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer: Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.EM: Computes the log of the conditional density (per cluster) for a given instance.
logDensityPerClusterForInstance(Instance) - Method in class weka.clusterers.MakeDensityBasedClusterer: Computes the log of the conditional density (per cluster) for a given instance.
logDetailed(String) - Method in class weka.knowledgeflow.LogManager: Log at the detailed level
logDetailed(String) - Method in interface weka.knowledgeflow.StepManager: Log a message at the "detailed" level
logDetailed(String) - Method in class weka.knowledgeflow.StepManagerImpl: Log a message at the detailed logging level
logError(String, Exception) - Method in class weka.knowledgeflow.LogManager: Log an error
logError(String, Throwable) - Method in interface weka.knowledgeflow.StepManager: Log an error message.
logError(String, Throwable) - Method in class weka.knowledgeflow.StepManagerImpl: Log an error
Logger - Class in weka.core.logging: Abstract superclass for all loggers.
Logger() - Constructor for class weka.core.logging.Logger: Initializes the logger.
Logger - Interface in weka.gui: Interface for objects that display log (permanent historical) and status (transient) messages.
Logger.Level - Enum in weka.core.logging: The logging level.
LOGGING_LEVEL - Static variable in class weka.knowledgeflow.KFDefaults
LOGGING_LEVEL_KEY - Static variable in class weka.knowledgeflow.KFDefaults
LoggingLevel - Enum in weka.knowledgeflow: Enum for different logging levels
LogHandler - Interface in weka.core: Interface to something that can output messages to a log
Logistic - Class in weka.classifiers.functions: Class for building and using a multinomial logistic regression model with a ridge estimator.

There are some modifications, however, compared to the paper of leCessie and van Houwelingen(1992):

If there are k classes for n instances with m attributes, the parameter matrix B to be calculated will be an m*(k-1) matrix.

The probability for class j with the exception of the last class is

Pj(Xi) = exp(XiBj)/((sum[j=1..(k-1)]exp(Xi*Bj))+1)

The last class has probability

1-(sum[j=1..(k-1)]Pj(Xi))
= 1/((sum[j=1..(k-1)]exp(Xi*Bj))+1)

The (negative) multinomial log-likelihood is thus:

L = -sum[i=1..n]{
sum[j=1..(k-1)](Yij * ln(Pj(Xi)))
+(1 - (sum[j=1..(k-1)]Yij))
* ln(1 - sum[j=1..(k-1)]Pj(Xi))
} + ridge * (B^2)

In order to find the matrix B for which L is minimised, a Quasi-Newton Method is used to search for the optimized values of the m*(k-1) variables.
Logistic() - Constructor for class weka.classifiers.functions.Logistic: Constructor that sets the default number of decimal places to 4.
LogisticBase - Class in weka.classifiers.trees.lmt: Base/helper class for building logistic regression models with the LogitBoost algorithm.
LogisticBase() - Constructor for class weka.classifiers.trees.lmt.LogisticBase: Constructor that creates LogisticBase object with standard options.
LogisticBase(int, boolean, boolean) - Constructor for class weka.classifiers.trees.lmt.LogisticBase: Constructor to create LogisticBase object.
LogisticProducerHelper - Class in weka.classifiers.pmml.producer: Helper class for producing PMML for a Logistic classifier.
LogisticProducerHelper() - Constructor for class weka.classifiers.pmml.producer.LogisticProducerHelper
LogitBoost - Class in weka.classifiers.meta: Class for performing additive logistic regression.
LogitBoost() - Constructor for class weka.classifiers.meta.LogitBoost: Constructor.
logJointDensitiesForInstance(Instance) - Method in class weka.clusterers.AbstractDensityBasedClusterer: Returns the logs of the joint densities for a given instance.
logJointDensitiesForInstance(Instance) - Method in interface weka.clusterers.DensityBasedClusterer: Returns the logs of the joint densities for a given instance.
loglikelihood(double[], double[]) - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Computes loglikelihood of current model.
LOGLOSS - Static variable in class weka.classifiers.functions.SGD: the log loss function.
LOGLOSS - Static variable in class weka.classifiers.functions.SGDText: the log loss function.
logLossDecodingTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
logLow(String) - Method in class weka.knowledgeflow.LogManager: Log at the low level
logLow(String) - Method in interface weka.knowledgeflow.StepManager: Log a message at the "low" level
logLow(String) - Method in class weka.knowledgeflow.StepManagerImpl: Log a message at the low logging level
LogManager - Class in weka.knowledgeflow: Class that wraps a weka.gui.Logger and filters log messages according to the set logging level.
LogManager(Step) - Constructor for class weka.knowledgeflow.LogManager: Constructor that takes a Step.
LogManager(Logger) - Constructor for class weka.knowledgeflow.LogManager: Constructor that takes a log
LogManager(Logger, boolean) - Constructor for class weka.knowledgeflow.LogManager: Constructor that takes a log
logMessage(String) - Method in class weka.gui.beans.FlowRunner.SimpleLogger
logMessage(String) - Method in class weka.gui.beans.LogPanel: Sends the supplied message to the log area.
logMessage(String) - Method in interface weka.gui.Logger: Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.LogPanel: Sends the supplied message to the log area.
logMessage(String) - Method in class weka.gui.SysErrLog: Sends the supplied message to the log area.
logMessage(String) - Method in class weka.knowledgeflow.FlowRunner.SimpleLogger
LogPanel - Class in weka.gui.beans: Class for displaying a status area (made up of a variable number of lines) and a log area.
LogPanel() - Constructor for class weka.gui.beans.LogPanel
LogPanel - Class in weka.gui: This panel allows log and status messages to be posted.
LogPanel() - Constructor for class weka.gui.LogPanel: Creates the log panel with no task monitor and the log always visible.
LogPanel(WekaTaskMonitor) - Constructor for class weka.gui.LogPanel: Creates the log panel with a task monitor, where the log is hidden.
LogPanel(WekaTaskMonitor, boolean) - Constructor for class weka.gui.LogPanel: Creates the log panel, possibly with task monitor, where the log is optionally hidden.
LogPanel(WekaTaskMonitor, boolean, boolean, boolean) - Constructor for class weka.gui.LogPanel: Creates the log panel, possibly with task monitor, where the either the log is optionally hidden or the status (having both hidden is not allowed).
logPSI - Static variable in class weka.core.matrix.Maths: The constant - log( sqrt(2 pi) )
logs2probs(double[]) - Static method in class weka.core.Utils: Converts an array containing the natural logarithms of probabilities stored in a vector back into probabilities.
logScore(int, int) - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Gets the log score contribution of this distribution
logScore(int) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: logScore returns the log of the quality of a network (e.g.
logScore(int, int) - Method in interface weka.classifiers.bayes.net.search.local.Scoreable: Returns log-score
logSystemInfo() - Method in class weka.core.Debug.Log: a convenience method for dumping the current system info in the log file
logSystemInfo() - Method in class weka.core.Debug.SimpleLog: a convenience method for dumping the current system info in the log file
logWarning(String) - Method in class weka.knowledgeflow.LogManager: Log a warning
logWarning(String) - Method in interface weka.knowledgeflow.StepManager: Log a warning message.
logWarning(String) - Method in class weka.knowledgeflow.StepManagerImpl: Log a warning message
LogWindow - Class in weka.gui: Frame that shows the output from stdout and stderr.
LogWindow() - Constructor for class weka.gui.LogWindow: creates the frame
LogWriter - Interface in weka.gui.beans: Interface to be implemented by classes that should be able to write their own output to the Weka logger.
LONG - Static variable in class weka.experiment.DatabaseUtils: Type mapping for LONG used for reading experiment results.
lookAheadIterationsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
LookAndFeel - Class in weka.gui: A little helper class for setting the Look and Feel of the user interface.
LookAndFeel() - Constructor for class weka.gui.LookAndFeel
lookupCacheSizeTipText() - Method in class weka.attributeSelection.BestFirst: Returns the tip text for this property
LOSS_STRING - Variable in class weka.experiment.ResultMatrix: loss string.
lossFunctionTipText() - Method in class weka.classifiers.functions.SGD: Returns the tip text for this property
lossFunctionTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
LovinsStemmer - Class in weka.core.stemmers: A stemmer based on the Lovins stemmer, described here:

Julie Beth Lovins (1968).
LovinsStemmer() - Constructor for class weka.core.stemmers.LovinsStemmer
LOW_MEMORY_MINIMUM - Static variable in class weka.core.Memory
lowerBoundMinSupportTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
lowerBoundMinSupportTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
lowercaseTokensTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
lowercaseTokensTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
lowerCaseTokensTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
lowerCaseTokensTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
lowerNumericBoundIsOpen() - Method in class weka.core.Attribute: Returns whether the lower numeric bound of the attribute is open.
lowerSizeTipText() - Method in class weka.experiment.LearningRateResultProducer: Returns the tip text for this property
LPAREN - Static variable in interface weka.core.expressionlanguage.parser.sym
LSQUARE - Static variable in interface weka.core.json.sym
LT - Static variable in interface weka.core.expressionlanguage.parser.sym
lu() - Method in class weka.core.matrix.Matrix: LU Decomposition
LUDecomposition - Class in weka.core.matrix: LU Decomposition.
LUDecomposition() - Method in class weka.core.Matrix: Deprecated.

Performs a LUDecomposition on the matrix.
LUDecomposition(Matrix) - Constructor for class weka.core.matrix.LUDecomposition: LU Decomposition
LWL - Class in weka.classifiers.lazy: Locally weighted learning.
LWL() - Constructor for class weka.classifiers.lazy.LWL: Constructor.

M

M5Base - Class in weka.classifiers.trees.m5: M5Base.
M5Base() - Constructor for class weka.classifiers.trees.m5.M5Base: Constructor
M5P - Class in weka.classifiers.trees: M5Base.
M5P() - Constructor for class weka.classifiers.trees.M5P: Creates a new M5P instance.
M5Rules - Class in weka.classifiers.rules: Generates a decision list for regression problems using separate-and-conquer.
M5Rules() - Constructor for class weka.classifiers.rules.M5Rules: Constructor
m_ADNodes - Variable in class weka.classifiers.bayes.net.VaryNode: list of ADNode children
m_alpha - Variable in class weka.classifiers.functions.supportVector.RegOptimizer: alpha and alpha* arrays containing weights for solving dual problem
m_alpha - Variable in class weka.classifiers.trees.lmt.LMTNode: Alpha-value (for pruning) at the node
m_alphaStar - Variable in class weka.classifiers.functions.supportVector.RegOptimizer
m_alwaysDisplayPointsOfThisSize - Variable in class weka.gui.visualize.PlotData2D: If the shape size of a point equals this size then always plot it (i.e.
M_AVERAGE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_children - Variable in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
m_classDistribution - Variable in class weka.classifiers.trees.ht.HNode: Class distribution at this node
m_col - Variable in class weka.gui.treevisualizer.NamedColor: The actual color object
m_cols - Variable in class weka.gui.treevisualizer.Colors: The array with all the colors input
m_CoordCount - Variable in class weka.core.neighboursearch.PerformanceStats: The number of coordinates looked at for the current/last query.
m_count - Variable in class weka.classifiers.functions.SGDText.Count
m_customColour - Variable in class weka.gui.visualize.PlotData2D
m_defaultExpression - Static variable in class weka.filters.unsupervised.attribute.MathExpression: The default modification expression
M_DELETE - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: Missing value handling mode
m_displayAllPoints - Variable in class weka.gui.visualize.PlotData2D: Display all points (ie.
m_Distributions - Variable in class weka.classifiers.bayes.BayesNet: The attribute estimators containing CPTs.
m_doNotLoadList - Static variable in class weka.core.WekaPackageManager: The set of packages that the user has requested not to load
m_End - Variable in class weka.core.neighboursearch.balltrees.BallNode: The end index of the portion of the master index array, which stores indices of the instances/points the node contains.
m_End - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: The end index of the portion of the master index array, which stores indices of the instances/points the node contains.
m_experimentFinished - Variable in class weka.experiment.RemoteExperimentEvent: True if a remote experiment has finished
m_hidden_index - Variable in class weka.gui.InteractiveTableModel: Index of the hidden column
m_indexVal - Variable in class weka.gui.visualize.AttributePanelEvent: The index for the new attribute
m_initialPackageLoadingInProcess - Static variable in class weka.core.WekaPackageManager: Package loading in progress?
m_iNode - Variable in class weka.classifiers.bayes.net.VaryNode: index of the node varied
m_Instances - Variable in class weka.classifiers.bayes.BayesNet: The dataset header for the purposes of printing out a semi-intelligible model
m_Instances - Variable in class weka.classifiers.bayes.net.ADNode: list of Instance children (either m_Instances or m_VaryNodes is instantiated)
m_L - Variable in class weka.classifiers.functions.GaussianProcesses: (negative) covariance matrix in symmetric matrix representation
m_Left - Variable in class weka.core.neighboursearch.balltrees.BallNode: The left child of the node.
m_Left - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: left subtree; contains instances with smaller or equal to split value.
m_logMessage - Variable in class weka.experiment.RemoteExperimentEvent: A log type message
m_MaxC - Variable in class weka.core.neighboursearch.PerformanceStats: The min and max coordinates(attributes) looked at per query.
M_MAXDIFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_MaxP - Variable in class weka.core.neighboursearch.PerformanceStats: The min and max data points looked for a query by the NNS algorithm.
m_messageString - Variable in class weka.experiment.RemoteExperimentEvent: The message
m_MinC - Variable in class weka.core.neighboursearch.PerformanceStats: The min and max coordinates(attributes) looked at per query.
m_MinP - Variable in class weka.core.neighboursearch.PerformanceStats: The min and max data points looked for a query by the NNS algorithm.
m_name - Variable in class weka.gui.treevisualizer.NamedColor: The name of the color
m_nCount - Variable in class weka.classifiers.bayes.net.ADNode: count
m_nMCV - Variable in class weka.classifiers.bayes.net.VaryNode: most common value
m_nNodes - Variable in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode: nodes of the Bayes net in this junction node
m_NodeNumber - Variable in class weka.core.neighboursearch.balltrees.BallNode: The node number/id.
m_NodeNumber - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: node number (only for debug).
m_NodeRanges - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: lowest and highest value and width (= high - low) for each dimension.
m_NodesRectBounds - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: The lo and high bounds of the hyper rectangle described by the node.
m_noPackageMetaDataAvailable - Static variable in class weka.core.WekaPackageManager
M_NORMAL - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
m_nStartNode - Variable in class weka.classifiers.bayes.net.ADNode: first node in VaryNode array
m_numIncorrectModel - Variable in class weka.classifiers.trees.lmt.LMTNode: Weighted number of training examples currently misclassified by the logistic model at the node
m_numIncorrectTree - Variable in class weka.classifiers.trees.lmt.LMTNode: Weighted number of training examples currently misclassified by the subtree rooted at the node
m_NumInstances - Variable in class weka.core.neighboursearch.balltrees.BallNode: The number of instances/points in the node.
m_numParameters - Variable in class weka.classifiers.trees.m5.RuleNode: the number of paramters in the chosen model for this node---either the subtree model or the linear model.
m_offline - Static variable in class weka.core.WekaPackageManager: Operating offline?
m_OutputFormat - Variable in class weka.core.Debug.Clock: the format of the output
m_outputTypes - Variable in class weka.core.Debug.DBO: range of outputtyp
m_parentBranch - Variable in class weka.classifiers.trees.ht.LeafNode: Parent branch leading to this node
m_parentNode - Variable in class weka.classifiers.trees.ht.LeafNode: Parent split node
m_PointCount - Variable in class weka.core.neighboursearch.PerformanceStats: The number of data points looked at for the current/last query.
m_postSplitClassDistributions - Variable in class weka.classifiers.trees.ht.SplitCandidate: list of class distributions resulting from a split - 2 entries in the outer list for numeric splits and n for nominal splits
m_Right - Variable in class weka.core.neighboursearch.balltrees.BallNode: The right child of the node.
m_Right - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: right subtree; contains instances with larger than split value.
m_root - Variable in class weka.classifiers.bayes.net.MarginCalculator
m_SplitAttrib - Variable in class weka.core.neighboursearch.balltrees.BallNode: The attribute that splits this node (not always used).
m_SplitDim - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: attribute to split on.
m_splitMerit - Variable in class weka.classifiers.trees.ht.SplitCandidate: The merit of the split
m_splitTest - Variable in class weka.classifiers.trees.ht.SplitCandidate
m_SplitVal - Variable in class weka.core.neighboursearch.balltrees.BallNode: The value of m_SpiltAttrib that splits this node (not always used).
m_SplitValue - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: value to split on.
m_Start - Variable in class weka.core.neighboursearch.balltrees.BallNode: The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.
m_Start - Variable in class weka.core.neighboursearch.kdtrees.KDTreeNode: The start index of the portion of the master index array, which stores the indices of the instances/points the node contains.
m_statusMessage - Variable in class weka.experiment.RemoteExperimentEvent: A status type message
m_SumC - Variable in class weka.core.neighboursearch.PerformanceStats: The sum of coordinates/attributes looked at for all the queries.
m_SumP - Variable in class weka.core.neighboursearch.PerformanceStats: The sum of data points looked at for all the queries.
m_SumSqC - Variable in class weka.core.neighboursearch.PerformanceStats: The squared sum of coordinates/attributes looked at for all the queries.
m_SumSqP - Variable in class weka.core.neighboursearch.PerformanceStats: The squared sum of data points looked at for all the queries.
m_theNode - Variable in class weka.classifiers.trees.ht.LeafNode: The actual node for this leaf
m_useCustomColour - Variable in class weka.gui.visualize.PlotData2D: Custom colour for this plot
m_UseWordwrap - Variable in class weka.gui.LogWindow: whether the JTextPane has wordwrap or not
m_VaryNodes - Variable in class weka.classifiers.bayes.net.ADNode: list of VaryNode children
m_verboseOn - Variable in class weka.core.Debug.DBO: enables/disables output of debug information
m_weight - Variable in class weka.classifiers.functions.SGDText.Count
m_weight - Variable in class weka.classifiers.trees.ht.WeightMass
m_weightSeenAtLastSplitEval - Variable in class weka.classifiers.trees.ht.ActiveHNode: The weight of instances seen at the last split evaluation
m_xChange - Variable in class weka.gui.visualize.AttributePanelEvent: True if the x selection changed
m_yChange - Variable in class weka.gui.visualize.AttributePanelEvent: True if the y selection changed
Macro - Interface in weka.core.expressionlanguage.core: Interface for compile time macros to enable meta programming
MacroDeclarations - Interface in weka.core.expressionlanguage.core: Interface to expose macros to a program.
MacroDeclarationsCompositor - Class in weka.core.expressionlanguage.common: A helper class that allows to combine several macro declarations together.
MacroDeclarationsCompositor(MacroDeclarations...) - Constructor for class weka.core.expressionlanguage.common.MacroDeclarationsCompositor: Constructs a MacroDeclarationsCompositor containing the provided declarations
MahalanobisEstimator - Class in weka.estimators: Simple probability estimator that places a single normal distribution over the observed values.
MahalanobisEstimator(Matrix, double, double) - Constructor for class weka.estimators.MahalanobisEstimator: Constructor
main(String[]) - Static method in class weka.associations.Apriori: Main method.
main(String[]) - Static method in class weka.associations.AssociatorEvaluation: A test method for this class.
main(String[]) - Static method in class weka.associations.CheckAssociator: Test method for this class
main(String[]) - Static method in class weka.associations.FilteredAssociator: Main method for running this class.
main(String[]) - Static method in class weka.associations.FPGrowth: Main method.
main(String[]) - Static method in class weka.attributeSelection.AttributeSelection: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.CfsSubsetEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.CheckAttributeSelection: Test method for this class
main(String[]) - Static method in class weka.attributeSelection.ClassifierAttributeEval: Main method for executing this class.
main(String[]) - Static method in class weka.attributeSelection.ClassifierSubsetEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.CorrelationAttributeEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.GainRatioAttributeEval: Main method.
main(String[]) - Static method in class weka.attributeSelection.InfoGainAttributeEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.OneRAttributeEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.PrincipalComponents: Main method for testing this class
main(String[]) - Static method in class weka.attributeSelection.ReliefFAttributeEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Main method for testing this class.
main(String[]) - Static method in class weka.attributeSelection.WrapperSubsetEval: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.BayesNet: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayes: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomial: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.NaiveBayesUpdateable: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.ADNode: for testing only
main(String[]) - Static method in class weka.classifiers.bayes.net.BayesNetGenerator: Main method
main(String[]) - Static method in class weka.classifiers.bayes.net.BIFReader: Loads the file specified as first parameter and prints it to stdout.
main(String[]) - Static method in class weka.classifiers.bayes.net.EditableBayesNet
main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorFullBayes: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.bayes.net.GUI: Main method.
main(String[]) - Static method in class weka.classifiers.bayes.net.MarginCalculator
main(String[]) - Static method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: for testing the class
main(String[]) - Static method in class weka.classifiers.BVDecompose: Test method for this class
main(String[]) - Static method in class weka.classifiers.BVDecomposeSegCVSub: Test method for this class
main(String[]) - Static method in class weka.classifiers.CheckClassifier: Test method for this class
main(String[]) - Static method in class weka.classifiers.CheckSource: Executes the tests, use "-h" to list the commandline options.
main(String[]) - Static method in class weka.classifiers.evaluation.Evaluation: A test method for this class.
main(String[]) - Static method in class weka.classifiers.Evaluation: A test method for this class.
main(String[]) - Static method in class weka.classifiers.functions.GaussianProcesses: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.LinearRegression: Generates a linear regression function predictor.
main(String[]) - Static method in class weka.classifiers.functions.Logistic: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.MultilayerPerceptron: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SGD: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SGDText: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SimpleLinearRegression: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.functions.SimpleLogistic: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.functions.SMO: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.functions.SMOreg: Main method for running this classifier.
main(String[]) - Static method in class weka.classifiers.functions.supportVector.CheckKernel: Test method for this class
main(String[]) - Static method in class weka.classifiers.functions.supportVector.KernelEvaluation: A test method for this class.
main(String[]) - Static method in class weka.classifiers.functions.VotedPerceptron: Main method.
main(String[]) - Static method in class weka.classifiers.lazy.IBk: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.KStar: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.lazy.LWL: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AdaBoostM1: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AdditiveRegression: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.AttributeSelectedClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Bagging: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.ClassificationViaRegression: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.CostSensitiveClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.CVParameterSelection: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.FilteredClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.IterativeClassifierOptimizer: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.LogitBoost: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiClassClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.MultiScheme: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RandomCommittee: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RandomizableFilteredClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RandomSubSpace: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.RegressionByDiscretization: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Stacking: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.Vote: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.misc.InputMappedClassifier: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.misc.SerializedClassifier: Runs the classifier with the given options
main(String[]) - Static method in class weka.classifiers.rules.DecisionTable: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.JRip: Main method.
main(String[]) - Static method in class weka.classifiers.rules.M5Rules: Main method by which this class can be tested
main(String[]) - Static method in class weka.classifiers.rules.OneR: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.rules.PART: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.rules.ZeroR: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.DecisionStump: Main method for testing this class.
main(String[]) - Static method in class weka.classifiers.trees.HoeffdingTree
main(String[]) - Static method in class weka.classifiers.trees.J48: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.trees.LMT: Main method for testing this class
main(String[]) - Static method in class weka.classifiers.trees.M5P: Main method by which this class can be tested
main(String[]) - Static method in class weka.classifiers.trees.RandomForest: Main method for this class.
main(String[]) - Static method in class weka.classifiers.trees.RandomTree: Main method for this class.
main(String[]) - Static method in class weka.classifiers.trees.REPTree: Main method for this class.
main(String[]) - Static method in class weka.clusterers.Canopy
main(String[]) - Static method in class weka.clusterers.CheckClusterer: Test method for this class
main(String[]) - Static method in class weka.clusterers.ClusterEvaluation: Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.Cobweb: Main method.
main(String[]) - Static method in class weka.clusterers.EM: Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.FarthestFirst: Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.FilteredClusterer: Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.HierarchicalClusterer
main(String[]) - Static method in class weka.clusterers.MakeDensityBasedClusterer: Main method for testing this class.
main(String[]) - Static method in class weka.clusterers.SimpleKMeans: Main method for executing this class.
main(String[]) - Static method in class weka.core.AlgVector: Main method for testing this class, can take an ARFF file as first argument.
main(String[]) - Static method in class weka.core.AllJavadoc: Parses the given commandline parameters and generates the Javadoc.
main(String[]) - Static method in class weka.core.Attribute: Simple main method for testing this class.
main(String[]) - Static method in class weka.core.BinarySparseInstance: Main method for testing this class.
main(String[]) - Static method in class weka.core.Capabilities: loads the given dataset and prints the Capabilities necessary to process it.
main(String[]) - Static method in class weka.core.CheckGOE: Main method for using the CheckGOE.
main(String[]) - Static method in class weka.core.CheckOptionHandler: Main method for using the CheckOptionHandler.
main(String[]) - Static method in class weka.core.ClassCache: For testing only.
main(String[]) - Static method in class weka.core.ClassDiscovery: Possible calls: weka.core.ClassDiscovery <packages>
Prints all the packages in the current classpath weka.core.ClassDiscovery <classname> <packagename(s)>
Prints the classes it found.
main(String[]) - Static method in class weka.core.ContingencyTables: Main method for testing this class.
main(String[]) - Static method in class weka.core.converters.ArffLoader: Main method.
main(String[]) - Static method in class weka.core.converters.ArffSaver: Main method.
main(String[]) - Static method in class weka.core.converters.C45Loader: Main method for testing this class.
main(String[]) - Static method in class weka.core.converters.C45Saver: Main method.
main(String[]) - Static method in class weka.core.converters.ConverterUtils.DataSink: for testing only - takes a data file as input and a data file for the output.
main(String[]) - Static method in class weka.core.converters.ConverterUtils.DataSource: for testing only - takes a data file as input.
main(String[]) - Static method in class weka.core.converters.CSVLoader: Main method.
main(String[]) - Static method in class weka.core.converters.CSVSaver: Main method.
main(String[]) - Static method in class weka.core.converters.DatabaseLoader: Main method.
main(String[]) - Static method in class weka.core.converters.DatabaseSaver: Main method.
main(String[]) - Static method in class weka.core.converters.DictionarySaver
main(String[]) - Static method in class weka.core.converters.JSONLoader: Main method.
main(String[]) - Static method in class weka.core.converters.JSONSaver: Main method.
main(String[]) - Static method in class weka.core.converters.LibSVMLoader: Main method.
main(String[]) - Static method in class weka.core.converters.LibSVMSaver: Main method.
main(String[]) - Static method in class weka.core.converters.MatlabLoader: Main method.
main(String[]) - Static method in class weka.core.converters.MatlabSaver: Main method.
main(String[]) - Static method in class weka.core.converters.SerializedInstancesLoader: Main method.
main(String[]) - Static method in class weka.core.converters.SerializedInstancesSaver: Main method.
main(String[]) - Static method in class weka.core.converters.SVMLightLoader: Main method.
main(String[]) - Static method in class weka.core.converters.SVMLightSaver: Main method.
main(String[]) - Static method in class weka.core.converters.TextDirectoryLoader: Main method.
main(String[]) - Static method in class weka.core.converters.XRFFLoader: Main method.
main(String[]) - Static method in class weka.core.converters.XRFFSaver: Main method.
main(String[]) - Static method in class weka.core.Copyright: Only for testing
main(String[]) - Static method in class weka.core.DenseInstance: Main method for testing this class.
main(String[]) - Static method in class weka.core.EnumHelper: Main method for testing this class
main(String[]) - Static method in class weka.core.Environment: Main method for testing this class.
main(String[]) - Static method in class weka.core.FindWithCapabilities: Executes the location of classes with parameters from the commandline.
main(String[]) - Static method in class weka.core.GlobalInfoJavadoc: Parses the given commandline parameters and generates the Javadoc.
main(String[]) - Static method in class weka.core.InstanceComparator: for testing only.
main(String[]) - Static method in class weka.core.Instances: Main method for this class.
main(String[]) - Static method in class weka.core.json.JSONInstances: For testing only.
main(String[]) - Static method in class weka.core.json.JSONNode: Only for testing.
main(String[]) - Static method in class weka.core.json.Parser: Runs the parser from commandline.
main(String[]) - Static method in class weka.core.ListOptions: runs the javadoc producer with the given commandline options
main(String[]) - Static method in class weka.core.matrix.DoubleVector
main(String[]) - Static method in class weka.core.matrix.IntVector: Tests the IntVector class
main(String[]) - Static method in class weka.core.Matrix: Deprecated.

Main method for testing this class.
main(String[]) - Static method in class weka.core.matrix.Matrix: Main method for testing this class.
main(String[]) - Static method in class weka.core.Memory: prints only some statistics
main(String[]) - Static method in class weka.core.neighboursearch.CoverTree: Method for testing the class from command line.
main(String[]) - Static method in class weka.core.OptionHandlerJavadoc: Parses the given commandline parameters and generates the Javadoc.
main(String[]) - Static method in class weka.core.packageManagement.DefaultPackage
main(String[]) - Static method in class weka.core.packageManagement.DefaultPackageManager
main(String[]) - Static method in class weka.core.pmml.Constant
main(String[]) - Static method in class weka.core.pmml.PMMLFactory
main(String[]) - Static method in class weka.core.PropertyPath: for testing only
main(String[]) - Static method in class weka.core.Queue: Main method for testing this class.
main(String[]) - Static method in class weka.core.RandomVariates: Main method for testing this class.
main(String[]) - Static method in class weka.core.Range: Main method for testing this class.
main(String[]) - Static method in class weka.core.RepositoryIndexGenerator: Main method for running the RepositoryIndexGenerator
main(String[]) - Static method in class weka.core.RevisionUtils: For testing only.
main(String[]) - Static method in class weka.core.scripting.Groovy: If no arguments are given, it just prints the presence of the Groovy classes, otherwise it expects a Groovy filename to execute.
main(String[]) - Static method in class weka.core.scripting.Jython: If no arguments are given, it just prints the presence of the Jython classes, otherwise it expects a Jython filename to execute.
main(String[]) - Static method in class weka.core.SerializationHelper: Outputs information about a class on the commandline, takes class name as arguments.
main(String[]) - Static method in class weka.core.SingleIndex: Main method for testing this class.
main(String[]) - Static method in class weka.core.SparseInstance: Main method for testing this class.
main(String[]) - Static method in class weka.core.SpecialFunctions: Main method for testing this class.
main(String[]) - Static method in class weka.core.Statistics: Main method for testing this class.
main(String[]) - Static method in class weka.core.stemmers.IteratedLovinsStemmer: Runs the stemmer with the given options
main(String[]) - Static method in class weka.core.stemmers.LovinsStemmer: Runs the stemmer with the given options
main(String[]) - Static method in class weka.core.stemmers.NullStemmer: Runs the stemmer with the given options
main(String[]) - Static method in class weka.core.stemmers.SnowballStemmer: Runs the stemmer with the given options.
main(String[]) - Static method in class weka.core.Stopwords: Accepts the following parameter:
-i file
loads the stopwords from the given file
-o file
saves the stopwords to the given file
-p
outputs the current stopwords on stdout
Any additional parameters are interpreted as words to test as stopwords.
main(String[]) - Static method in class weka.core.SystemInfo: for printing the system info to stdout.
main(String[]) - Static method in class weka.core.TechnicalInformation: Prints some examples of technical informations if there are no commandline options given.
main(String[]) - Static method in class weka.core.TechnicalInformationHandlerJavadoc: Parses the given commandline parameters and generates the Javadoc.
main(String[]) - Static method in class weka.core.TestInstances: for running the class from commandline, prints the generated data to stdout
main(String[]) - Static method in class weka.core.tokenizers.AlphabeticTokenizer: Runs the tokenizer with the given options and strings to tokenize.
main(String[]) - Static method in class weka.core.tokenizers.CharacterNGramTokenizer: Runs the tokenizer with the given options and strings to tokenize.
main(String[]) - Static method in class weka.core.tokenizers.NGramTokenizer: Runs the tokenizer with the given options and strings to tokenize.
main(String[]) - Static method in class weka.core.tokenizers.WordTokenizer: Runs the tokenizer with the given options and strings to tokenize.
main(String[]) - Static method in class weka.core.Trie: Only for testing (prints the built Trie).
main(String[]) - Static method in class weka.core.Utils: Main method for testing this class.
main(String[]) - Static method in class weka.core.Version: only for testing
main(String[]) - Static method in class weka.core.WekaPackageManager: Main method for using the package manager from the command line
main(String[]) - Static method in class weka.core.xml.SerialUIDChanger: exchanges an old UID for a new one.
main(String[]) - Static method in class weka.core.xml.XMLDocument: for testing only.
main(String[]) - Static method in class weka.core.xml.XMLInstances: takes an XML document as first argument and then outputs the Instances statistics
main(String[]) - Static method in class weka.core.xml.XMLOptions: for testing only.
main(String[]) - Static method in class weka.core.xml.XMLSerialization: for testing only.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.Agrawal: Main method for executing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.BayesNet: Main method for executing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.LED24: Main method for executing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.RandomRBF: Main method for executing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.classification.RDG1: Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.regression.Expression: Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.classifiers.regression.MexicanHat: Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.clusterers.BIRCHCluster: Main method for testing this class.
main(String[]) - Static method in class weka.datagenerators.clusterers.SubspaceCluster: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.CheckEstimator: Test method for this class
main(String[]) - Static method in class weka.estimators.DDConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DiscreteEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DKConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.DNConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KDConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KernelEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.KKConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.MahalanobisEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.MultivariateGaussianEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NDConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NNConditionalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.NormalEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.PoissonEstimator: Main method for testing this class.
main(String[]) - Static method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Main method, used for testing this class.
main(String[]) - Static method in class weka.estimators.UnivariateKernelEstimator: Main method, used for testing this class.
main(String[]) - Static method in class weka.estimators.UnivariateMixtureEstimator: Main method, used for testing this class.
main(String[]) - Static method in class weka.estimators.UnivariateNormalEstimator: Main method, used for testing this class.
main(String[]) - Static method in class weka.experiment.CrossValidationResultProducer: Quick test of timestamp
main(String[]) - Static method in class weka.experiment.Experiment: Configures/Runs the Experiment from the command line.
main(String[]) - Static method in class weka.experiment.InstanceQuery: Test the class from the command line.
main(String[]) - Static method in class weka.experiment.OutputZipper: Main method for testing this class
main(String[]) - Static method in class weka.experiment.PairedCorrectedTTester: Test the class from the command line.
main(String[]) - Static method in class weka.experiment.PairedStats: Tests the paired stats object from the command line.
main(String[]) - Static method in class weka.experiment.PairedStatsCorrected: Tests the paired stats object from the command line.
main(String[]) - Static method in class weka.experiment.PairedTTester: Test the class from the command line.
main(String[]) - Static method in class weka.experiment.RemoteEngine: Main method.
main(String[]) - Static method in class weka.experiment.RemoteExperiment: Configures/Runs the Experiment from the command line.
main(String[]) - Static method in class weka.experiment.ResultMatrixCSV: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixGnuPlot: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixHTML: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixLatex: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixPlainText: for testing only.
main(String[]) - Static method in class weka.experiment.ResultMatrixSignificance: for testing only.
main(String[]) - Static method in class weka.experiment.Stats: Tests the paired stats object from the command line.
main(String[]) - Static method in class weka.experiment.xml.XMLExperiment: for testing only.
main(String[]) - Static method in class weka.filters.AllFilter: Main method for testing this class.
main(String[]) - Static method in class weka.filters.CheckSource: Executes the tests, use "-h" to list the commandline options.
main(String[]) - Static method in class weka.filters.Filter: Main method for testing this class.
main(String[]) - Static method in class weka.filters.MultiFilter: Main method for executing this class.
main(String[]) - Static method in class weka.filters.RenameRelation: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.AddClassification: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.supervised.attribute.AttributeSelection: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Main method for testing this class
main(String[]) - Static method in class weka.filters.supervised.attribute.ClassOrder: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.Discretize: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.MergeNominalValues: runs the filter with the given arguments
main(String[]) - Static method in class weka.filters.supervised.attribute.NominalToBinary: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.attribute.PartitionMembership: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.ClassBalancer: runs the filter with the given arguments
main(String[]) - Static method in class weka.filters.supervised.instance.Resample: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.SpreadSubsample: Main method for testing this class.
main(String[]) - Static method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Add: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddCluster: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddExpression: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddID: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddNoise: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddUserFields: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.AddValues: Main method for testing and running this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.CartesianProduct: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Center: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ClassAssigner: Main method for executing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ClusterMembership: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Copy: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.DateToNumeric: Runs the filter with the given parameters.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Discretize: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.FirstOrder: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector
main(String[]) - Static method in class weka.filters.unsupervised.attribute.InterquartileRange: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.KernelFilter: runs the filter with the given arguments
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MakeIndicator: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MathExpression: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: runs the filter with the given arguments
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeManyValues: Main method for executing this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.MergeTwoValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToBinary: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NominalToString: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Normalize: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericCleaner: Runs the filter from commandline, use "-h" to see all options.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToBinary: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToDate: Runs the filter with the given parameters.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericToNominal: Runs the filter with the given parameters.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.NumericTransform: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Obfuscate: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Main method for executing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PKIDiscretize: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.PrincipalComponents: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RandomProjection: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RandomSubset: Runs the filter with the given parameters.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Remove: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveByName: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveType: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RemoveUseless: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RenameAttribute: Main method for executing this filter.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.RenameNominalValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Reorder: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SortLabels: runs the filter with the given arguments.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Standardize: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToNominal: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.StringToWordVector: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.SwapValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesDelta: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.attribute.Transpose: runs the filter with the given arguments
main(String[]) - Static method in class weka.filters.unsupervised.instance.NonSparseToSparse: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Randomize: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveDuplicates: Main method for running this filter.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveFolds: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveMisclassified: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemovePercentage: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveRange: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.RemoveWithValues: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.Resample: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.ReservoirSample: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.SparseToNonSparse: Main method for testing this class.
main(String[]) - Static method in class weka.filters.unsupervised.instance.SubsetByExpression: Main method for running this filter.
main(String[]) - Static method in class weka.gui.arffviewer.ArffViewer: shows the frame and it tries to load all the arff files that were provided as arguments.
main(String[]) - Static method in class weka.gui.AttributeListPanel: Tests the attribute list panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeSelectionPanel: Tests the attribute selection panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeSummaryPanel: Tests out the attribute summary panel from the command line.
main(String[]) - Static method in class weka.gui.AttributeVisualizationPanel: Main method to test this class from command line
main(String[]) - Static method in class weka.gui.beans.AttributeSummarizer
main(String[]) - Static method in class weka.gui.beans.CostBenefitAnalysis
main(String[]) - Static method in class weka.gui.beans.DataVisualizer
main(String[]) - Static method in class weka.gui.beans.EnvironmentField: Deprecated.

Main method for testing this class
main(String[]) - Static method in class weka.gui.beans.FlowRunner: Main method for testing this class.
main(String[]) - Static method in class weka.gui.beans.KnowledgeFlow: Shows the splash screen, launches the application and then disposes the splash screen.
main(String[]) - Static method in class weka.gui.beans.KnowledgeFlowApp: Main method.
main(String[]) - Static method in class weka.gui.beans.Loader
main(String[]) - Static method in class weka.gui.beans.LogPanel: Main method to test this class.
main(String[]) - Static method in class weka.gui.beans.ModelPerformanceChart
main(String[]) - Static method in class weka.gui.beans.Saver: The main method for testing
main(String[]) - Static method in class weka.gui.beans.ScatterPlotMatrix
main(String[]) - Static method in class weka.gui.beans.SQLViewerPerspective: Main method for testing this class
main(String[]) - Static method in class weka.gui.beans.StripChart: Tests out the StripChart from the command line
main(String[]) - Static method in class weka.gui.beans.TextViewer
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanel: Main method for testing this class
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Main method for testing this class
main(String[]) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Main method for testing this class
main(String[]) - Static method in class weka.gui.ConverterFileChooser: For testing the file chooser.
main(String[]) - Static method in class weka.gui.DatabaseConnectionDialog: for testing only
main(String[]) - Static method in class weka.gui.EnvironmentField: Main method for testing this class
main(String[]) - Static method in class weka.gui.experiment.AlgorithmListPanel: Tests out the algorithm list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.DatasetListPanel: Tests out the dataset list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.DistributeExperimentPanel: Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.Experimenter: Tests out the experiment environment.
main(String[]) - Static method in class weka.gui.experiment.ExperimenterDefaults: only for testing - prints the content of the props file.
main(String[]) - Static method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.HostListPanel: Tests out the host list panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.OutputFormatDialog: for testing only.
main(String[]) - Static method in class weka.gui.experiment.ResultsPanel: Tests out the results panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.RunNumberPanel: Tests out the panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.RunPanel: Tests out the run panel from the command line.
main(String[]) - Static method in class weka.gui.experiment.SetupPanel: Tests out the experiment setup from the command line.
main(String[]) - Static method in class weka.gui.explorer.AssociationsPanel: Tests out the Associator panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.AttributeSelectionPanel: Tests out the attribute selection panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.ClassifierPanel: Tests out the classifier panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.ClustererPanel: Tests out the clusterer panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.Explorer: Tests out the explorer environment.
main(String[]) - Static method in class weka.gui.explorer.ExplorerDefaults: only for testing - prints the content of the props file.
main(String[]) - Static method in class weka.gui.explorer.PreprocessPanel: Tests out the instance-preprocessing panel from the command line.
main(String[]) - Static method in class weka.gui.explorer.VisualizePanel: Tests out the visualize panel from the command line.
main(String[]) - Static method in class weka.gui.GenericArrayEditor: Tests out the array editor from the command line.
main(String[]) - Static method in class weka.gui.GenericObjectEditor: Tests out the Object editor from the command line.
main(String[]) - Static method in class weka.gui.GenericPropertiesCreator: for generating props file: no parameter: see default constructor 1 parameter (i.e., filename): see default constructor + setOutputFilename(String) 2 parameters (i.e, filenames): see constructor with String argument + setOutputFilename(String)
main(String[]) - Static method in class weka.gui.graphvisualizer.GraphVisualizer: Main method to load a text file with the description of a graph from the command line
main(String[]) - Static method in class weka.gui.GUIChooser
main(String[]) - Static method in class weka.gui.GUIChooserApp: Tests out the GUIChooser environment.
main(String[]) - Static method in class weka.gui.HierarchyPropertyParser: Tests out the parser.
main(String[]) - Static method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer: Main method for testing this class.
main(String[]) - Static method in class weka.gui.InfoToWiki
main(String[]) - Static method in class weka.gui.InstancesSummaryPanel: Tests out the instance summary panel from the command line.
main(String[]) - Static method in class weka.gui.knowledgeflow.KnowledgeFlow
main(String[]) - Static method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Main method for launching this application
main(String[]) - Static method in class weka.gui.ListSelectorDialog: Tests out the list selector from the command line.
main(String[]) - Static method in class weka.gui.LogPanel: Tests out the log panel from the command line.
main(String[]) - Static method in class weka.gui.LogWindow: for testing only
main(String[]) - Static method in class weka.gui.LookAndFeel: prints all the available LnFs to stdout
Main - Class in weka.gui: Menu-based GUI for Weka, replacement for the GUIChooser.
Main() - Constructor for class weka.gui.Main: default constructor.
main(String[]) - Static method in class weka.gui.Main: starts the application.
main(String[]) - Static method in class weka.gui.PackageManager
main(String[]) - Static method in class weka.gui.PropertySelectorDialog: Tests out the property selector from the command line.
main(String[]) - Static method in class weka.gui.ResultHistoryPanel: Tests out the result history from the command line.
main(String[]) - Static method in class weka.gui.SaveBuffer: Main method for testing this class
main(String[]) - Static method in class weka.gui.scripting.GroovyPanel: Displays the panel in a frame.
main(String[]) - Static method in class weka.gui.scripting.GroovyScript: Runs the script from commandline.
main(String[]) - Static method in class weka.gui.scripting.JythonPanel: Displays the panel in a frame.
main(String[]) - Static method in class weka.gui.scripting.JythonScript: Runs the script from commandline.
main(String[]) - Static method in class weka.gui.SelectedTagEditor: Tests out the selectedtag editor from the command line.
main(String[]) - Static method in class weka.gui.SimpleCLI: Method to start up the simple cli.
main(String[]) - Static method in class weka.gui.SimpleCLIPanel: Displays the panel in a frame.
main(String[]) - Static method in class weka.gui.sql.SqlViewer: starts the SQL-Viewer interface.
main(String[]) - Static method in class weka.gui.sql.SqlViewerDialog: for testing only.
main(String[]) - Static method in class weka.gui.treevisualizer.TreeVisualizer: Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.AttributePanel: Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.BMPWriter: for testing only.
main(String[]) - Static method in class weka.gui.visualize.ClassPanel: Main method for testing this class.
main(String[]) - Static method in class weka.gui.visualize.JPEGWriter: for testing only.
main(String[]) - Static method in class weka.gui.visualize.LegendPanel: Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.MatrixPanel: Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.Plot2D: Main method for testing this class
main(String[]) - Static method in class weka.gui.visualize.PNGWriter: for testing only.
main(String[]) - Static method in class weka.gui.visualize.PostscriptWriter: for testing only
main(String[]) - Static method in class weka.gui.visualize.ThresholdVisualizePanel: Starts the ThresholdVisualizationPanel with parameters from the command line.
main(String[]) - Static method in class weka.gui.visualize.VisualizePanel: Main method for testing this class
main(String[]) - Static method in class weka.gui.WekaTaskMonitor: Main method for testing this class
main(String[]) - Static method in class weka.gui.Workbench
main(String[]) - Static method in class weka.gui.WorkbenchApp: Main method.
main(String[]) - Static method in class weka.knowledgeflow.FlowRunner: Main method for executing the FlowRunner
main(String[]) - Static method in class weka.knowledgeflow.JSONFlowUtils: Main method for testing this class
main(String[]) - Static method in class weka.Run: Main method for this class.
Main.BackgroundDesktopPane - Class in weka.gui: DesktopPane with background image.
Main.ChildFrameMDI - Class in weka.gui: Specialized JInternalFrame class.
Main.ChildFrameSDI - Class in weka.gui: Specialized JFrame class.
MAIN_PERSPECTIVE_ID - Static variable in class weka.knowledgeflow.KFDefaults
MainKFPerspective() - Constructor for class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
MainKFPerspective - Class in weka.gui.knowledgeflow: Main perspective for the Knowledge flow application
MainKFPerspective() - Constructor for class weka.gui.knowledgeflow.MainKFPerspective: Construct a new MainKFPerspective
MainKFPerspectiveToolBar - Class in weka.gui.knowledgeflow: Class that provides the main editing widget toolbar and menu items
MainKFPerspectiveToolBar(MainKFPerspective) - Constructor for class weka.gui.knowledgeflow.MainKFPerspectiveToolBar: Constructor
MainKFPerspectiveToolBar.Widgets - Enum in weka.gui.knowledgeflow: Enum containing all the widgets provided by the toolbar.
MainMenuExtension - Interface in weka.gui: Classes implementing this interface will be displayed in the "Extensions" menu in the main GUI of Weka.
MAJOR - Static variable in class weka.core.Version: the major version
MAJORITY_VOTING_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Majority Voting (only nominal classes)
makeADTree(int, ArrayList<Integer>, Instances) - Static method in class weka.classifiers.bayes.net.ADNode: create sub tree
makeADTree(Instances) - Static method in class weka.classifiers.bayes.net.ADNode: create AD tree from set of instances
makeBinaryTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
makeBinaryTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
makeCopies(Associator, int) - Static method in class weka.associations.AbstractAssociator: Creates copies of the current associator.
makeCopies(ASEvaluation, int) - Static method in class weka.attributeSelection.ASEvaluation: Creates copies of the current evaluator.
makeCopies(ASSearch, int) - Static method in class weka.attributeSelection.ASSearch: Creates copies of the current search scheme.
makeCopies(Classifier, int) - Static method in class weka.classifiers.AbstractClassifier: Creates a given number of deep copies of the given classifier using serialization.
makeCopies(Kernel, int) - Static method in class weka.classifiers.functions.supportVector.Kernel: Creates a given number of deep or shallow (if the kernel implements Copyable) copies of the given kernel using serialization.
makeCopies(Clusterer, int) - Static method in class weka.clusterers.AbstractClusterer: Creates copies of the current clusterer.
makeCopies(DensityBasedClusterer, int) - Static method in class weka.clusterers.AbstractDensityBasedClusterer: Creates copies of the current clusterer.
makeCopies(Estimator, int) - Static method in class weka.estimators.Estimator: Creates a given number of deep copies of the given estimator using serialization.
makeCopies(Filter, int) - Static method in class weka.filters.Filter: Creates a given number of deep copies of the given filter using serialization.
makeCopy(Associator) - Static method in class weka.associations.AbstractAssociator: Creates a deep copy of the given associator using serialization.
makeCopy(Classifier) - Static method in class weka.classifiers.AbstractClassifier: Creates a deep copy of the given classifier using serialization.
makeCopy(Kernel) - Static method in class weka.classifiers.functions.supportVector.Kernel: Creates a shallow copy of the kernel (if it implements Copyable) otherwise a deep copy using serialization.
makeCopy(Clusterer) - Static method in class weka.clusterers.AbstractClusterer: Creates a deep copy of the given clusterer using serialization.
makeCopy(OptionHandler) - Static method in interface weka.core.OptionHandler: Creates an instance of the class that the given option handler belongs to and sets the options for this new instance by taking the option settings from the given option handler.
makeCopy(Estimator) - Static method in class weka.estimators.Estimator: Creates a deep copy of the given estimator using serialization.
makeCopy(Filter) - Static method in class weka.filters.Filter: Creates a deep copy of the given filter using serialization.
makeCopy(Object) - Static method in class weka.gui.GenericArrayEditor: Makes a copy of an object using serialization.
makeCopy(Object) - Static method in class weka.gui.GenericObjectEditor: Makes a copy of an object using serialization if the given object is not an option handler.
makeData(DataGenerator, String[]) - Static method in class weka.datagenerators.DataGenerator: Calls the data generator.
MakeDecList - Class in weka.classifiers.rules.part: Class for handling a decision list.
MakeDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.MakeDecList: Constructor for unpruned dec list.
MakeDecList(ModelSelection, double, int) - Constructor for class weka.classifiers.rules.part.MakeDecList: Constructor for dec list pruned using C4.5 pruning.
MakeDecList(ModelSelection, int, int, int) - Constructor for class weka.classifiers.rules.part.MakeDecList: Constructor for dec list pruned using hold-out pruning.
MakeDensityBasedClusterer - Class in weka.clusterers: Class for wrapping a Clusterer to make it return a distribution and density.
MakeDensityBasedClusterer() - Constructor for class weka.clusterers.MakeDensityBasedClusterer: Default constructor.
MakeDensityBasedClusterer(Clusterer) - Constructor for class weka.clusterers.MakeDensityBasedClusterer: Contructs a MakeDensityBasedClusterer wrapping a given Clusterer.
makeDistribution(double, int) - Static method in class weka.classifiers.evaluation.NominalPrediction: Convert a single prediction into a probability distribution with all zero probabilities except the predicted value which has probability 1.0.
MakeIndicator - Class in weka.filters.unsupervised.attribute: A filter that creates a new dataset with a Boolean attribute replacing a nominal attribute.
MakeIndicator() - Constructor for class weka.filters.unsupervised.attribute.MakeIndicator: Constructor
makeOutputInstance(Instance, boolean) - Method in class weka.gui.beans.SubstringLabelerRules: Process and input instance and return an output instance
makeOutputInstance(Instance) - Method in class weka.gui.beans.SubstringReplacerRules: Make an output instance given an input one
MakeResourceIntensive - Class in weka.knowledgeflow.steps: A Step that makes downstream steps that are directly connected to this step resource intensive (or not).
MakeResourceIntensive() - Constructor for class weka.knowledgeflow.steps.MakeResourceIntensive
makeUniformDistribution(int) - Static method in class weka.classifiers.evaluation.NominalPrediction: Creates a uniform probability distribution -- where each of the possible classes is assigned equal probability.
makeVaryNode(int, ArrayList<Integer>, Instances) - Static method in class weka.classifiers.bayes.net.ADNode: create sub tree
makeWeighted(CostMatrix) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Makes a copy of this ConfusionMatrix after applying the supplied CostMatrix to the cells.
ManhattanDistance - Class in weka.core: Implements the Manhattan distance (or Taxicab geometry).
ManhattanDistance() - Constructor for class weka.core.ManhattanDistance: Constructs an Manhattan Distance object, Instances must be still set.
ManhattanDistance(Instances) - Constructor for class weka.core.ManhattanDistance: Constructs an Manhattan Distance object and automatically initializes the ranges.
map(String, String) - Method in class weka.core.matrix.DoubleVector: Applies a method to the vector
mapClasses(int, int, int[][], int[], double[], double[], int) - Static method in class weka.clusterers.ClusterEvaluation: Finds the minimum error mapping of classes to clusters.
MappingInfo - Class in weka.core.pmml: Class that maintains the mapping between incoming data set structure and that of the mining schema.
MappingInfo(Instances, MiningSchema, Logger) - Constructor for class weka.core.pmml.MappingInfo
mapToMiningSchema(Instances) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Map mining schema to incoming instances.
MapValues - Class in weka.core.pmml.jaxbbindings: Java class for MapValues element declaration.
MapValues() - Constructor for class weka.core.pmml.jaxbbindings.MapValues
margin() - Method in class weka.classifiers.evaluation.NominalPrediction: Calculates the prediction margin.
MarginCalculator - Class in weka.classifiers.bayes.net
MarginCalculator() - Constructor for class weka.classifiers.bayes.net.MarginCalculator
MarginCalculator.JunctionTreeNode - Class in weka.classifiers.bayes.net
MarginCalculator.JunctionTreeSeparator - Class in weka.classifiers.bayes.net
MarginCurve - Class in weka.classifiers.evaluation: Generates points illustrating the prediction margin.
MarginCurve() - Constructor for class weka.classifiers.evaluation.MarginCurve
markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
markovBlanketClassifierTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
maskKeyword(String) - Method in class weka.experiment.DatabaseUtils: If the given string is a keyword, then the mask character will be appended and returned.
MatCell - Class in weka.core.pmml.jaxbbindings: Java class for MatCell element declaration.
MatCell() - Constructor for class weka.core.pmml.jaxbbindings.MatCell
MATCH_PART_SEPARATOR - Static variable in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Separator for parts of the match specification
MATCH_RULE_SEPARATOR - Static variable in class weka.gui.beans.SubstringLabelerRules: Separator for match rules in the internal representation
Matchable - Interface in weka.core: Interface to something that can be matched with tree matching algorithms.
matchMissingValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
matchRulesFromInternal(String, Instances, String, Logger, Environment) - Static method in class weka.gui.beans.SubstringLabelerRules: Get a list of match rules from an internally encoded match specification
matchRulesFromInternal(String, Instances, String, Logger, Environment) - Static method in class weka.gui.beans.SubstringReplacerRules: Get a list of match rules from an internally encoded match specification
MathExpression - Class in weka.filters.unsupervised.attribute: Modify numeric attributes according to a given mathematical expression.
MathExpression() - Constructor for class weka.filters.unsupervised.attribute.MathExpression: Constructor
MathFunctions - Class in weka.core.expressionlanguage.common: Macro declarations for common mathematical functions.
MathFunctions() - Constructor for class weka.core.expressionlanguage.common.MathFunctions
Maths - Class in weka.core.matrix: Utility class.
Maths() - Constructor for class weka.core.matrix.Maths
MatlabLoader - Class in weka.core.converters: Reads a Matlab file containing a single matrix in ASCII format.
MatlabLoader() - Constructor for class weka.core.converters.MatlabLoader
MatlabSaver - Class in weka.core.converters: Writes Matlab ASCII files, in single or double precision format.
MatlabSaver() - Constructor for class weka.core.converters.MatlabSaver: Constructor.
matrix() - Method in class weka.classifiers.trees.j48.Distribution: Returns matrix with distribution of class values.
Matrix - Class in weka.core: Deprecated.
Use weka.core.matrix.Matrix instead - only for backwards compatibility.
Matrix(int, int) - Constructor for class weka.core.Matrix: Deprecated.

Constructs a matrix and initializes it with default values.
Matrix(double[][]) - Constructor for class weka.core.Matrix: Deprecated.

Constructs a matrix using a given array.
Matrix(Reader) - Constructor for class weka.core.Matrix: Deprecated.

Reads a matrix from a reader.
Matrix - Class in weka.core.matrix: Jama = Java Matrix class.
Matrix(int, int) - Constructor for class weka.core.matrix.Matrix: Construct an m-by-n matrix of zeros.
Matrix(int, int, double) - Constructor for class weka.core.matrix.Matrix: Construct an m-by-n constant matrix.
Matrix(double[][]) - Constructor for class weka.core.matrix.Matrix: Construct a matrix from a 2-D array.
Matrix(double[][], int, int) - Constructor for class weka.core.matrix.Matrix: Construct a matrix quickly without checking arguments.
Matrix(double[], int) - Constructor for class weka.core.matrix.Matrix: Construct a matrix from a one-dimensional packed array
Matrix(Reader) - Constructor for class weka.core.matrix.Matrix: Reads a matrix from a reader.
Matrix - Class in weka.core.pmml.jaxbbindings: Java class for Matrix element declaration.
Matrix() - Constructor for class weka.core.pmml.jaxbbindings.Matrix
MATRIX_ON_DEMAND - Static variable in class weka.classifiers.meta.CostSensitiveClassifier: load cost matrix on demand
MATRIX_SUPPLIED - Static variable in class weka.classifiers.meta.CostSensitiveClassifier: use explicit cost matrix
MatrixPanel - Class in weka.gui.visualize: This panel displays a plot matrix of the user selected attributes of a given data set.
MatrixPanel() - Constructor for class weka.gui.visualize.MatrixPanel: Constructor
matrixToString(double[][]) - Static method in class weka.attributeSelection.PrincipalComponents: Return a matrix as a String
matthewsCorrelationCoefficient(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class.
matthewsCorrelationCoefficient(int, double, double, double, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class.
matthewsCorrelationCoefficient(int) - Method in class weka.classifiers.Evaluation: Calculates the matthews correlation coefficient (sometimes called phi coefficient) for the supplied class
max() - Method in class weka.core.matrix.DoubleVector: Returns the maximum value of all elements
MAX - Static variable in class weka.core.neighboursearch.KDTree: The index of MAX value in attributes' range array.
MAX - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of max value in an array of attributes' range.
max - Variable in class weka.experiment.Stats: The maximum value seen, or Double.NaN if no values seen
MAX_DIGITS - Static variable in class weka.core.converters.SVMLightSaver: the number of digits after the decimal point.
MAX_HISTORY_COUNT - Static variable in class weka.gui.GenericObjectEditorHistory: the maximum entries in the history.
MAX_HISTORY_LENGTH - Static variable in class weka.gui.GenericObjectEditorHistory: the maximum length of a caption in the history.
MAX_LINE_LENGTH - Static variable in class weka.gui.GenericObjectEditorHistory: the menu max line length.
MAX_PRECISION - Static variable in class weka.gui.visualize.VisualizeUtils: Default maximum precision for the display of numeric values
MAX_ROWS - Static variable in class weka.gui.sql.QueryPanel: the name for the max rows in the history.
MAX_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Maximum Probability
MAX_SHAPES - Static variable in class weka.gui.visualize.Plot2D
MAX_SLEEP_TIME - Static variable in class weka.core.Memory
MAX_TABS - Static variable in class weka.gui.scripting.SyntaxDocument: the maximum number of tabs.
MAX_UNDO_POINTS - Static variable in class weka.knowledgeflow.KFDefaults
MAX_UNDO_POINTS_KEY - Static variable in class weka.knowledgeflow.KFDefaults
maxBag() - Method in class weka.classifiers.trees.j48.Distribution: Returns index of bag containing maximum number of instances.
maxBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
maxCardinalityTipText() - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm
maxClass() - Method in class weka.classifiers.trees.j48.Distribution: Returns class with highest frequency over all bags.
maxClass(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns class with highest frequency for given bag.
maxCountTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
maxDecimalPlacesTipText() - Method in class weka.core.converters.ArffSaver: Returns the tip text for this property.
maxDecimalPlacesTipText() - Method in class weka.core.converters.CSVSaver: Returns the tip text for this property.
maxDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
maxDepthTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
maxDepthTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
maxDepthTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
maxImpurity() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Returns the impurity of this split
maxImpurity() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Returns the impurity of this split
maxImpurity() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Returns the impurity of this split
maximumAttributeNamesTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
maximumAttributeNamesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property.
maximumAttributesTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property.
maximumNumberOfClustersTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
maximumVariancePercentageAllowedTipText() - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Returns the tip text for this property
maxIndex(double[]) - Static method in class weka.core.Utils: Returns index of maximum element in a given array of doubles.
maxIndex(int[]) - Static method in class weka.core.Utils: Returns index of maximum element in a given array of integers.
maxInstancesInLeafTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the tip text for this property.
maxInstInLeafTipText() - Method in class weka.core.neighboursearch.KDTree: Tip text for this property.
maxInstNumTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
maxInstNumTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
maxIterationsTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
maxIterationsTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
maxIterationsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
maxItsTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
maxKTipText() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the tip text for this property
maxNrOfParentsTipText() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm
maxNumberOfItemsTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
maxNumCandidateCanopiesToHoldInMemory() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
maxNumComponentsToolTipText() - Method in class weka.estimators.UnivariateMixtureEstimator: The tool tip for this property.
maxParentSetSize(int) - Method in class weka.classifiers.bayes.net.ParentSet: reserve memory for parent set
maxRadiusTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
maxRangeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
maxRelativeLeafRadiusTipText() - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Returns the tip text for this property.
maxRuleSizeTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
maxSubsequenceLengthTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
maxThresholdTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
MAYBE_SUPPORT - Static variable in class weka.gui.GenericObjectEditor.GOETreeNode: color for "maybe support".
mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.Filter: Default implementation returns false.
mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.MultiFilter: RemoveWithValues may return false from input() (thus not making an instance available immediately) even after the first batch has been completed due to matching a value that the user wants to remove.
mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: RemoveWithValues may return false from input() (thus not making an instance available immediately) even after the first batch has been completed due to matching a value that the user wants to remove.
mayRemoveInstanceAfterFirstBatchDone() - Method in class weka.filters.unsupervised.instance.SubsetByExpression: SubsetByExpression may return false from input() (thus not making an instance available immediately) even after the first batch has been completed if the user has opted to apply the filter to instances after the first batch (rather than just passing them through).
MDL - Static variable in interface weka.classifiers.bayes.net.search.local.Scoreable
mean(double[]) - Static method in class weka.core.Utils: Computes the mean for an array of doubles.
mean - Variable in class weka.experiment.Stats: The mean of values, or Double.NaN if no values seen
meanAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean absolute error.
meanAbsoluteError() - Method in class weka.classifiers.Evaluation: Returns the mean absolute error.
meanOrMode(int) - Method in class weka.core.Instances: Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanOrMode(Attribute) - Method in class weka.core.Instances: Returns the mean (mode) for a numeric (nominal) attribute as a floating-point value.
meanPrecTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
meanPriorAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean absolute error of the prior.
meanPriorAbsoluteError() - Method in class weka.classifiers.Evaluation: Returns the mean absolute error of the prior.
meanSquaredTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
meanWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
measureAICScore() - Method in class weka.classifiers.bayes.BayesNet
measureAttributesUsed() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
measureBayesScore() - Method in class weka.classifiers.bayes.BayesNet
measureBDeuScore() - Method in class weka.classifiers.bayes.BayesNet
measureBestNumIts() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the best number of iterations
measureBestVal() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the measure for the best model
measureDivergence() - Method in class weka.classifiers.bayes.BayesNet
measureEntropyScore() - Method in class weka.classifiers.bayes.BayesNet
measureExtraArcs() - Method in class weka.classifiers.bayes.BayesNet
measureMaxDepth() - Method in class weka.core.neighboursearch.BallTree: Returns the depth of the tree.
measureMaxDepth() - Method in class weka.core.neighboursearch.CoverTree: Returns the depth of the tree.
measureMaxDepth() - Method in class weka.core.neighboursearch.KDTree: Returns the depth of the tree.
measureMDLScore() - Method in class weka.classifiers.bayes.BayesNet
measureMissingArcs() - Method in class weka.classifiers.bayes.BayesNet
measureNumAttributesSelected() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Additional measure --- number of attributes selected
measureNumIterations() - Method in class weka.classifiers.meta.AdditiveRegression: return the number of iterations (base classifiers) completed
measureNumLeaves() - Method in class weka.classifiers.trees.J48: Returns the number of leaves
measureNumLeaves() - Method in class weka.classifiers.trees.LMT: Returns the number of leaves in the tree
measureNumLeaves() - Method in class weka.core.neighboursearch.BallTree: Returns the number of leaves.
measureNumLeaves() - Method in class weka.core.neighboursearch.CoverTree: Returns the number of leaves.
measureNumLeaves() - Method in class weka.core.neighboursearch.KDTree: Returns the number of leaves.
measureNumRules() - Method in class weka.classifiers.rules.DecisionTable: Returns the number of rules
measureNumRules() - Method in class weka.classifiers.rules.PART: Return the number of rules.
measureNumRules() - Method in class weka.classifiers.trees.J48: Returns the number of rules (same as number of leaves)
measureNumRules() - Method in class weka.classifiers.trees.m5.M5Base: return the number of rules
measureOutOfBagError() - Method in class weka.classifiers.meta.Bagging: Gets the out of bag error that was calculated as the classifier was built.
measurePerformanceTipText() - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the tip text for this property.
measureReversedArcs() - Method in class weka.classifiers.bayes.BayesNet
measureSelectionTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Additional measure --- time taken (milliseconds) to select the attributes
measureTime() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Additional measure --- time taken (milliseconds) to select attributes and build the classifier
measureTreeSize() - Method in class weka.classifiers.trees.J48: Returns the size of the tree
measureTreeSize() - Method in class weka.classifiers.trees.LMT: Returns the size of the tree
measureTreeSize() - Method in class weka.core.neighboursearch.BallTree: Returns the size of the tree.
measureTreeSize() - Method in class weka.core.neighboursearch.CoverTree: Returns the size of the tree.
measureTreeSize() - Method in class weka.core.neighboursearch.KDTree: Returns the size of the tree.
MEDIAN_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Median Probability (only numeric class)
MedianDistanceFromArbitraryPoint - Class in weka.core.neighboursearch.balltrees: Class that splits a BallNode of a ball tree using Uhlmann's described method.

For information see:

Jeffrey K.
MedianDistanceFromArbitraryPoint() - Constructor for class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Constructor.
MedianDistanceFromArbitraryPoint(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Constructor.
MedianOfWidestDimension - Class in weka.core.neighboursearch.balltrees: Class that splits a BallNode of a ball tree based on the median value of the widest dimension of the points in the ball.
MedianOfWidestDimension() - Constructor for class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Constructor.
MedianOfWidestDimension(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Constructor.
MedianOfWidestDimension - Class in weka.core.neighboursearch.kdtrees: The class that splits a KDTree node based on the median value of a dimension in which the node's points have the widest spread.

For more information see also:

Jerome H.
MedianOfWidestDimension() - Constructor for class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension
Memory - Class in weka.core: A little helper class for Memory management.
Memory() - Constructor for class weka.core.Memory: initializes the memory management without GUI support
Memory(boolean) - Constructor for class weka.core.Memory: initializes the memory management
MemoryBasedDataSource - Class in weka.knowledgeflow.steps: Simple start step that stores a set of instances and outputs it in a dataSet connection.
MemoryBasedDataSource() - Constructor for class weka.knowledgeflow.steps.MemoryBasedDataSource
memoryIsLow() - Method in class weka.core.Memory: Checks to see if memory is running low.
MemoryUsagePanel - Class in weka.gui: A panel for displaying the memory usage.
MemoryUsagePanel() - Constructor for class weka.gui.MemoryUsagePanel: default constructor.
mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.AprioriItemSet: Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.ItemSet: Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
mergeAllItemSets(ArrayList<Object>, int, int) - Static method in class weka.associations.LabeledItemSet: Merges all item sets in the set of (k-1)-item sets to create the (k)-item sets and updates the counters.
MergeInfrequentNominalValues - Class in weka.filters.unsupervised.attribute: Merges all values of the specified nominal attributes that are insufficiently frequent.
MergeInfrequentNominalValues() - Constructor for class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues
mergeInstance(Instance) - Method in class weka.core.BinarySparseInstance: Merges this instance with the given instance and returns the result.
mergeInstance(Instance) - Method in class weka.core.DenseInstance: Merges this instance with the given instance and returns the result.
mergeInstance(Instance) - Method in interface weka.core.Instance: Merges this instance with the given instance and returns the result.
mergeInstance(Instance) - Method in class weka.core.SparseInstance: Merges this instance with the given instance and returns the result.
mergeInstances(Instances, Instances) - Static method in class weka.core.Instances: Merges two sets of Instances together.
MergeManyValues - Class in weka.filters.unsupervised.attribute: Merges many values of a nominal attribute into one value.
MergeManyValues() - Constructor for class weka.filters.unsupervised.attribute.MergeManyValues
MergeNominalValues - Class in weka.filters.supervised.attribute: Merges values of all nominal attributes among the specified attributes, excluding the class attribute, using the CHAID method, but without considering re-splitting of merged subsets.
MergeNominalValues() - Constructor for class weka.filters.supervised.attribute.MergeNominalValues
MergeTwoValues - Class in weka.filters.unsupervised.attribute: Merges two values of a nominal attribute into one value.
MergeTwoValues() - Constructor for class weka.filters.unsupervised.attribute.MergeTwoValues
mergeValueRangeTipText() - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Returns the tip text for this property.
MESSAGE_TO_DISPLAY_ON_INSTALLATION_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for a message to display on installation
MetaBean - Class in weka.gui.beans: A meta bean that encapsulates several other regular beans, useful for grouping large KnowledgeFlows.
MetaBean() - Constructor for class weka.gui.beans.MetaBean
metaClassifierTipText() - Method in class weka.classifiers.meta.Stacking: Returns the tip text for this property
MetaStore - Interface in weka.core.metastore: Interface for metastore implementations.
METHOD_1_AGAINST_1 - Static variable in class weka.classifiers.meta.MultiClassClassifier: 1-against-1
METHOD_1_AGAINST_ALL - Static variable in class weka.classifiers.meta.MultiClassClassifier: 1-against-all
METHOD_ERROR_EXHAUSTIVE - Static variable in class weka.classifiers.meta.MultiClassClassifier: exhaustive correction code
METHOD_ERROR_RANDOM - Static variable in class weka.classifiers.meta.MultiClassClassifier: random correction code
MethodHandler - Class in weka.core.xml: This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
MethodHandler() - Constructor for class weka.core.xml.MethodHandler: initializes the handler
methodNameTipText() - Method in class weka.filters.unsupervised.attribute.NumericTransform: Returns the tip text for this property
methodTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
metricIsMaximisable(String) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper: Returns true if the named metric is maximisable
metricString() - Method in class weka.associations.Apriori: Returns the metric string for the chosen metric type
metricString() - Method in interface weka.associations.CARuleMiner: Gets name of the scoring metric used for car mining
metricTypeTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
metricTypeTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
MexicanHat - Class in weka.datagenerators.classifiers.regression: A data generator for the simple 'Mexian Hat' function:
y = sin|x| / |x|
In addition to this simple function, the amplitude can be changed and gaussian noise can be added.
MexicanHat() - Constructor for class weka.datagenerators.classifiers.regression.MexicanHat: initializes the generator
MiddleOutConstructor - Class in weka.core.neighboursearch.balltrees: The class that builds a BallTree middle out.

For more information see also:

Andrew W.
MiddleOutConstructor() - Constructor for class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Creates a new instance of MiddleOutConstructor.
MidPointOfWidestDimension - Class in weka.core.neighboursearch.kdtrees: The class that splits a KDTree node based on the midpoint value of a dimension in which the node's points have the widest spread.

For more information see also:

Andrew Moore (1991).
MidPointOfWidestDimension() - Constructor for class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension
millisToDate(double, String) - Static method in class weka.core.Utils: The inverse of dateToMillis(String, String).
MIN - Static variable in class weka.core.neighboursearch.KDTree: The index of MIN value in attributes' range array.
MIN - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of min value in an array of attributes' range.
min - Variable in class weka.experiment.Stats: The minimum value seen, or Double.NaN if no values seen
MIN_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Minimum Probability
minAbsoluteCoefficientValueTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
minBoxRelWidthTipText() - Method in class weka.core.neighboursearch.KDTree: Tip text for this property.
minBucketSizeTipText() - Method in class weka.classifiers.rules.OneR: Returns the tip text for this property
minDataDLIfDeleted(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats: Compute the minimal data description length of the ruleset if the rule in the given position is deleted.
The min_data_DL_if_deleted = data_DL_if_deleted - potential
minDataDLIfExists(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats: Compute the minimal data description length of the ruleset if the rule in the given position is NOT deleted.
The min_data_DL_if_n_deleted = data_DL_if_n_deleted - potential
minDefaultTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
mineCARs(Instances) - Method in class weka.associations.Apriori: Method that mines all class association rules with minimum support and with a minimum confidence.
mineCARs(Instances) - Method in interface weka.associations.CARuleMiner: Method for mining class association rules.
minimalTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property.
minimizeAbsoluteErrorTipText() - Method in class weka.classifiers.meta.AdditiveRegression: Returns the tip text for this property
minimizeAbsoluteErrorTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
minimizeExpectedCostTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
minimizeWindows() - Method in class weka.gui.Main: minimizes all windows.
minimumBucketSizeTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
minimumCanopyDensityTipText() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
minimumFractionOfWeightInfoGainTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
minimumFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
minimumLayoutSize(Container) - Method in class weka.gui.WrapLayout: Returns the minimum dimensions needed to layout the visible components contained in the specified target container.
minIndex(int[]) - Static method in class weka.core.Utils: Returns index of minimum element in a given array of integers.
minIndex(double[]) - Static method in class weka.core.Utils: Returns index of minimum element in a given array of doubles.
MiningBuildTask - Class in weka.core.pmml.jaxbbindings: Java class for MiningBuildTask element declaration.
MiningBuildTask() - Constructor for class weka.core.pmml.jaxbbindings.MiningBuildTask
MiningField - Class in weka.core.pmml.jaxbbindings: Java class for MiningField element declaration.
MiningField() - Constructor for class weka.core.pmml.jaxbbindings.MiningField
MiningField(String, FIELDUSAGETYPE) - Constructor for class weka.core.pmml.jaxbbindings.MiningField
MiningField(String, FIELDUSAGETYPE, MISSINGVALUETREATMENTMETHOD, String) - Constructor for class weka.core.pmml.jaxbbindings.MiningField
MiningFieldMetaInfo - Class in weka.core.pmml: Class encapsulating information about a MiningField.
MiningFieldMetaInfo(Element) - Constructor for class weka.core.pmml.MiningFieldMetaInfo: Constructs a new MiningFieldMetaInfo object.
MININGFUNCTION - Enum in weka.core.pmml.jaxbbindings: Java class for MINING-FUNCTION.
MiningModel - Class in weka.core.pmml.jaxbbindings: Java class for MiningModel element declaration.
MiningModel() - Constructor for class weka.core.pmml.jaxbbindings.MiningModel
MiningSchema - Class in weka.core.pmml.jaxbbindings: Java class for MiningSchema element declaration.
MiningSchema() - Constructor for class weka.core.pmml.jaxbbindings.MiningSchema
MiningSchema - Class in weka.core.pmml: This class encapsulates the mining schema from a PMML xml file.
MiningSchema(Element, Instances, TransformationDictionary) - Constructor for class weka.core.pmml.MiningSchema: Constructor for MiningSchema.
minInstNumTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
minInstNumTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
Minkowski - Class in weka.core.pmml.jaxbbindings: Java class for minkowski element declaration.
Minkowski() - Constructor for class weka.core.pmml.jaxbbindings.Minkowski
MinkowskiDistance - Class in weka.core: Implementing Minkowski distance (or similarity) function.

One object defines not one distance but the data model in which the distances between objects of that data model can be computed.

Attention: For efficiency reasons the use of consistency checks (like are the data models of the two instances exactly the same), is low.

For more information, see:

Wikipedia.
MinkowskiDistance() - Constructor for class weka.core.MinkowskiDistance: Constructs an Minkowski Distance object, Instances must be still set.
MinkowskiDistance(Instances) - Constructor for class weka.core.MinkowskiDistance: Constructs an Minkowski Distance object and automatically initializes the ranges.
minLogLikelihoodImprovementCVTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
minLogLikelihoodImprovementIteratingTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
minMetricTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
minMetricTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
minNoTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
minNumInstancesTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
minNumInstancesTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
minNumObjTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
minNumObjTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
minNumTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
minNumTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
MINOR - Static variable in class weka.core.Version: the minor version
minProb - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the smallest transformation probability
minRadiusTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
minRangeTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
minRuleSizeTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
minsAndMaxs(Instances, double[][], int) - Method in class weka.classifiers.trees.j48.C45Split: Returns the minsAndMaxs of the index.th subset.
minStdDevTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
minStdDevTipText() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the tip text for this property
minTermFreqTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
minTermFreqTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
minThresholdTipText() - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Returns the tip text for this property
minus(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '-' minus operator
MINUS - Static variable in interface weka.core.expressionlanguage.parser.sym
minus(double) - Method in class weka.core.matrix.DoubleVector: Subtracts a value
minus(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Subtracts another DoubleVector element by element
minus(Matrix) - Method in class weka.core.matrix.Matrix: C = A - B
minusEquals(double) - Method in class weka.core.matrix.DoubleVector: Subtracts a value in place
minusEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Subtracts another DoubleVector element by element in place
minusEquals(Matrix) - Method in class weka.core.matrix.Matrix: A = A - B
minVariancePropTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
minVariancePropTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
minWordFrequencyTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
minWordFrequencyTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
MISSING_SHAPE - Static variable in class weka.gui.visualize.Plot2D
MISSING_VALUE - Static variable in interface weka.classifiers.evaluation.Prediction: Constant representing a missing value.
MISSING_VALUE - Static variable in class weka.core.json.JSONInstances: the missing value indicator.
missingAccessed() - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Whether a missing value has been evaluated during computation.
missingArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: Count nr of arcs missing from other network compared to current network Note that an arc is not 'missing' if it is reversed.
missingClass() - Method in class weka.classifiers.evaluation.Evaluation: Gets the weight of the instances that had missing class values
missingCount - Variable in class weka.core.AttributeStats: The number of missing values
missingMergeTipText() - Method in class weka.attributeSelection.GainRatioAttributeEval: Returns the tip text for this property
missingMergeTipText() - Method in class weka.attributeSelection.InfoGainAttributeEval: Returns the tip text for this property
missingMergeTipText() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Returns the tip text for this property
missingModeTipText() - Method in class weka.classifiers.lazy.KStar: Returns the tip text for this property
missingSeparateTipText() - Method in class weka.attributeSelection.CfsSubsetEval: Returns the tip text for this property
missingValue() - Static method in class weka.core.Utils: Returns the value used to code a missing value.
MISSINGVALUESTRATEGY - Enum in weka.core.pmml.jaxbbindings: Java class for MISSING-VALUE-STRATEGY.
missingValueTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
missingValueTipText() - Method in class weka.core.converters.CSVSaver: Returns the tip text for this property.
MISSINGVALUETREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for MISSING-VALUE-TREATMENT-METHOD.
MissingValueWeights - Class in weka.core.pmml.jaxbbindings: Java class for MissingValueWeights element declaration.
MissingValueWeights() - Constructor for class weka.core.pmml.jaxbbindings.MissingValueWeights
MM() - Constructor for class weka.estimators.UnivariateMixtureEstimator.MM
MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClassifierPanel: The filename extension that should be used for model files.
MODEL_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClustererPanel: The filename extension that should be used for model files
modelBuilt() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: flag to indicate whether the model was built yet
modelDistributionForInstance(Instance) - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the class probabilities for an instance according to the logistic model at the node.
ModelExplanation - Class in weka.core.pmml.jaxbbindings: Java class for ModelExplanation element declaration.
ModelExplanation() - Constructor for class weka.core.pmml.jaxbbindings.ModelExplanation
modelFileTipText() - Method in class weka.classifiers.misc.SerializedClassifier: Returns the tip text for this property
ModelLiftGraph - Class in weka.core.pmml.jaxbbindings: Java class for ModelLiftGraph element declaration.
ModelLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.ModelLiftGraph
modelPathTipText() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the tip text for this property
ModelPerformanceChart - Class in weka.gui.beans: Bean that can be used for displaying threshold curves (e.g.
ModelPerformanceChart() - Constructor for class weka.gui.beans.ModelPerformanceChart
ModelPerformanceChart - Class in weka.knowledgeflow.steps: A Step that collects and displays either classifier error plots or threshold curves
ModelPerformanceChart() - Constructor for class weka.knowledgeflow.steps.ModelPerformanceChart
ModelPerformanceChartBeanInfo - Class in weka.gui.beans: Bean info class for the model performance chart
ModelPerformanceChartBeanInfo() - Constructor for class weka.gui.beans.ModelPerformanceChartBeanInfo
ModelPerformanceChartCustomizer - Class in weka.gui.beans: GUI customizer for model performance chart.
ModelPerformanceChartCustomizer() - Constructor for class weka.gui.beans.ModelPerformanceChartCustomizer: Constructor
ModelPerformanceChartInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the ModelPerformanceChart step
ModelPerformanceChartInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.ModelPerformanceChartInteractiveView
ModelPerformanceChartStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the ModelPerformanceChart step
ModelPerformanceChartStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.ModelPerformanceChartStepEditorDialog
ModelSelection - Class in weka.classifiers.trees.j48: Abstract class for model selection criteria.
ModelSelection() - Constructor for class weka.classifiers.trees.j48.ModelSelection
ModelStats - Class in weka.core.pmml.jaxbbindings: Java class for ModelStats element declaration.
ModelStats() - Constructor for class weka.core.pmml.jaxbbindings.ModelStats
modelsToString() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns a string describing the logistic regression function at the node.
ModelVerification - Class in weka.core.pmml.jaxbbindings: Java class for ModelVerification element declaration.
ModelVerification() - Constructor for class weka.core.pmml.jaxbbindings.ModelVerification
modifyHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
modifyHeaderTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
momentumTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
moralize(BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator: moralize DAG and calculate adjacency matrix representation for a Bayes Network, effecively converting the directed acyclic graph to an undirected graph.
mostRecentVersionWithRespectToConstraint(PackageConstraint) - Static method in class weka.core.WekaPackageManager: Find the most recent version of the package encapsulated in the supplied PackageConstraint argument that satisfies the constraint
mouseClicked(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when a mouse button has been pressed and released on a component
mouseClicked(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Does nothing.
mouseDragged(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs intermediate updates to what the user wishes to do.
mouseEntered(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when the mouse enters a component.
mouseEntered(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Does nothing.
mouseExited(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when the mouse exits a component
mouseExited(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Does nothing.
mouseMoved(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Does nothing.
mousePressed(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when a mouse button has been pressed on a component
mousePressed(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Determines what action the user wants to perform.
mouseReleased(MouseEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when a mouse button has been released on a component.
mouseReleased(MouseEvent) - Method in class weka.gui.treevisualizer.TreeVisualizer: Performs the final stages of what the user wants to perform.
move(File, File) - Static method in class weka.gui.scripting.ScriptUtils: Moves the file/directory (recursively).
MOVE_DOWN - Static variable in class weka.gui.JListHelper: moves items down
MOVE_UP - Static variable in class weka.gui.JListHelper: moves items up
moveBottom(JList) - Static method in class weka.gui.JListHelper: moves the selected items to the end
moveDown(JList) - Static method in class weka.gui.JListHelper: moves the selected item down by 1
moveTop(JList) - Static method in class weka.gui.JListHelper: moves the selected items to the top
moveUp(JList) - Static method in class weka.gui.JListHelper: moves the selected items up by 1
MSE() - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Returns average of squared errors for current model.
MultiClassClassifier - Class in weka.classifiers.meta: A metaclassifier for handling multi-class datasets with 2-class classifiers.
MultiClassClassifier() - Constructor for class weka.classifiers.meta.MultiClassClassifier: Constructor.
MultiClassClassifierUpdateable - Class in weka.classifiers.meta: A metaclassifier for handling multi-class datasets with 2-class classifiers.
MultiClassClassifierUpdateable() - Constructor for class weka.classifiers.meta.MultiClassClassifierUpdateable: Constructor
MultiFilter - Class in weka.filters: Applies several filters successively.
MultiFilter() - Constructor for class weka.filters.MultiFilter
MultiInstanceCapabilitiesHandler - Interface in weka.core: Multi-Instance classifiers can specify an additional Capabilities object for the data in the relational attribute, since the format of multi-instance data is fixed to "bag/NOMINAL,data/RELATIONAL,class".
MultilayerPerceptron - Class in weka.classifiers.functions: A classifier that uses backpropagation to learn a multi-layer perceptron to classify instances.
MultilayerPerceptron() - Constructor for class weka.classifiers.functions.MultilayerPerceptron: The constructor.
MultiNomialBMAEstimator - Class in weka.classifiers.bayes.net.estimate: Multinomial BMA Estimator.
MultiNomialBMAEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator
MultipleClassifiersCombiner - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that build an ensemble from multiple classifiers.
MultipleClassifiersCombiner() - Constructor for class weka.classifiers.MultipleClassifiersCombiner
MULTIPLEMODELMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for MULTIPLE-MODEL-METHOD.
multiply(Matrix) - Method in class weka.core.Matrix: Deprecated.

Returns the multiplication of two matrices
multiResultsetFull(int, int) - Method in class weka.experiment.PairedTTester: Creates a comparison table where a base resultset is compared to the other resultsets.
multiResultsetFull(int, int) - Method in interface weka.experiment.Tester: Creates a comparison table where a base resultset is compared to the other resultsets.
multiResultsetRanking(int) - Method in class weka.experiment.PairedTTester: returns a ranking of the resultsets
multiResultsetRanking(int) - Method in interface weka.experiment.Tester
multiResultsetSummary(int) - Method in class weka.experiment.PairedTTester: Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
multiResultsetSummary(int) - Method in interface weka.experiment.Tester: Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
multiResultsetWins(int, int[][]) - Method in class weka.experiment.PairedTTester: Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
multiResultsetWins(int, int[][]) - Method in interface weka.experiment.Tester: Carries out a comparison between all resultsets, counting the number of datsets where one resultset outperforms the other.
MultiScheme - Class in weka.classifiers.meta: Class for selecting a classifier from among several using cross validation on the training data or the performance on the training data.
MultiScheme() - Constructor for class weka.classifiers.meta.MultiScheme
MultiStopwords - Class in weka.core.stopwords: Applies the specified stopwords algorithms one after other.
As soon as a word has been identified as stopword, the loop is exited.
MultiStopwords() - Constructor for class weka.core.stopwords.MultiStopwords
MultivariateEstimator - Interface in weka.estimators: Interface to Multivariate Distribution Estimation
MultivariateGaussianEstimator - Class in weka.estimators: Implementation of maximum likelihood Multivariate Distribution Estimation using Normal Distribution.
MultivariateGaussianEstimator() - Constructor for class weka.estimators.MultivariateGaussianEstimator
MultivariateStat - Class in weka.core.pmml.jaxbbindings: Java class for MultivariateStat element declaration.
MultivariateStat() - Constructor for class weka.core.pmml.jaxbbindings.MultivariateStat
MultivariateStats - Class in weka.core.pmml.jaxbbindings: Java class for MultivariateStats element declaration.
MultivariateStats() - Constructor for class weka.core.pmml.jaxbbindings.MultivariateStats

N

NaiveBayes - Class in weka.classifiers.bayes: Class for a Naive Bayes classifier using estimator classes.
NaiveBayes() - Constructor for class weka.classifiers.bayes.NaiveBayes
NaiveBayes - Class in weka.classifiers.bayes.net.search.fixed: The NaiveBayes class generates a fixed Bayes network structure with arrows from the class variable to each of the attribute variables.
NaiveBayes() - Constructor for class weka.classifiers.bayes.net.search.fixed.NaiveBayes
NaiveBayesModel - Class in weka.core.pmml.jaxbbindings: Java class for NaiveBayesModel element declaration.
NaiveBayesModel() - Constructor for class weka.core.pmml.jaxbbindings.NaiveBayesModel
NaiveBayesMultinomial - Class in weka.classifiers.bayes: Class for building and using a multinomial Naive Bayes classifier.
NaiveBayesMultinomial() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomial
NaiveBayesMultinomialText - Class in weka.classifiers.bayes: Multinomial naive bayes for text data.
NaiveBayesMultinomialText() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomialText
NaiveBayesMultinomialUpdateable - Class in weka.classifiers.bayes: Class for building and using an updateable multinomial Naive Bayes classifier.
NaiveBayesMultinomialUpdateable() - Constructor for class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable
naiveBayesPredictionThresholdTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
NaiveBayesUpdateable - Class in weka.classifiers.bayes: Class for a Naive Bayes classifier using estimator classes.
NaiveBayesUpdateable() - Constructor for class weka.classifiers.bayes.NaiveBayesUpdateable
name() - Method in class weka.core.Attribute: Returns the attribute's name.
NAME - Static variable in class weka.core.json.JSONInstances: the name attribute.
name() - Method in class weka.core.Option: Returns the option's name.
NAME_CLASSFIRST - Static variable in class weka.experiment.xml.XMLExperiment: the name of the classFirst property
NAME_PROPERTYNODE_PARENTCLASS - Static variable in class weka.experiment.xml.XMLExperiment: PropertyNode member
NAME_PROPERTYNODE_PROPERTY - Static variable in class weka.experiment.xml.XMLExperiment: PropertyNode member
NAME_PROPERTYNODE_VALUE - Static variable in class weka.experiment.xml.XMLExperiment: PropertyNode member
NamedColor - Class in weka.gui.treevisualizer: This class contains a color name and the rgb values of that color
NamedColor(String, int, int, int) - Constructor for class weka.gui.treevisualizer.NamedColor
nameTipText() - Method in class weka.filters.unsupervised.attribute.AddExpression: Returns the tip text for this property
NATIVE_LIBS_DIR - Static variable in class weka.core.WekaPackageManager: The default native libraries directory
NATIVE_LIBS_DIR_NAME - Static variable in class weka.core.WekaPackageManager
NBNode - Class in weka.classifiers.trees.ht: Implements a LearningNode that uses a naive Bayes model
NBNode(Instances, double) - Constructor for class weka.classifiers.trees.ht.NBNode: Construct a new NBNode
NBNodeAdaptive - Class in weka.classifiers.trees.ht: Implements a LearningNode that chooses between using majority class or naive Bayes for prediction
NBNodeAdaptive(Instances, double) - Constructor for class weka.classifiers.trees.ht.NBNodeAdaptive: Constructor
NBTreeClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a naive bayes tree structure used for classification.
NBTreeClassifierTree(ModelSelection) - Constructor for class weka.classifiers.trees.j48.NBTreeClassifierTree
NBTreeModelSelection - Class in weka.classifiers.trees.j48: Class for selecting a NB tree split.
NBTreeModelSelection(int, Instances) - Constructor for class weka.classifiers.trees.j48.NBTreeModelSelection: Initializes the split selection method with the given parameters.
NBTreeNoSplit - Class in weka.classifiers.trees.j48: Class implementing a "no-split"-split (leaf node) for naive bayes trees.
NBTreeNoSplit() - Constructor for class weka.classifiers.trees.j48.NBTreeNoSplit
NBTreeSplit - Class in weka.classifiers.trees.j48: Class implementing a NBTree split on an attribute.
NBTreeSplit(int, int, double) - Constructor for class weka.classifiers.trees.j48.NBTreeSplit: Initializes the split model.
NDConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a discrete domain (utilises separate normal estimators for each discrete conditioning value).
NDConditionalEstimator() - Constructor for class weka.estimators.NDConditionalEstimator: No-arg constructor needed to make WEKA's forName() work.
NDConditionalEstimator(int, double) - Constructor for class weka.estimators.NDConditionalEstimator: Constructor
NearestNeighborModel - Class in weka.core.pmml.jaxbbindings: Java class for NearestNeighborModel element declaration.
NearestNeighborModel() - Constructor for class weka.core.pmml.jaxbbindings.NearestNeighborModel
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.BallTree: Returns the nearest instance in the current neighbourhood to the supplied instance.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.CoverTree: Returns the NN instance of a given target instance, from among the previously supplied training instances.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the nearest neighbour for the given instance based on distance measured in the filtered space.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.KDTree: Returns the nearest neighbour of the supplied target instance.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Returns the nearest instance in the current neighbourhood to the supplied instance.
nearestNeighbour(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Returns the nearest instance in the current neighbourhood to the supplied instance.
NearestNeighbourSearch - Class in weka.core.neighboursearch: Abstract class for nearest neighbour search.
NearestNeighbourSearch() - Constructor for class weka.core.neighboursearch.NearestNeighbourSearch: Constructor.
NearestNeighbourSearch(Instances) - Constructor for class weka.core.neighboursearch.NearestNeighbourSearch: Constructor.
nearestNeighbourSearchAlgorithmTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
nearestNeighbourSearchAlgorithmTipText() - Method in class weka.classifiers.lazy.LWL: Returns the tip text for this property.
needExponentialFormat(double) - Method in class weka.core.matrix.FlexibleDecimalFormat
needsUID(String) - Static method in class weka.core.SerializationHelper: checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.
needsUID(Class<?>) - Static method in class weka.core.SerializationHelper: checks whether a class needs to declare a serialVersionUID, i.e., it implements the java.io.Serializable interface but doesn't declare a serialVersionUID.
NeuralConnection - Class in weka.classifiers.functions.neural: Abstract unit in a NeuralNetwork.
NeuralConnection(String) - Constructor for class weka.classifiers.functions.neural.NeuralConnection: Constructs The unit with the basic connection information prepared for use.
NeuralInput - Class in weka.core.pmml.jaxbbindings: Java class for NeuralInput element declaration.
NeuralInput() - Constructor for class weka.core.pmml.jaxbbindings.NeuralInput
NeuralInputs - Class in weka.core.pmml.jaxbbindings: Java class for NeuralInputs element declaration.
NeuralInputs() - Constructor for class weka.core.pmml.jaxbbindings.NeuralInputs
NeuralLayer - Class in weka.core.pmml.jaxbbindings: Java class for NeuralLayer element declaration.
NeuralLayer() - Constructor for class weka.core.pmml.jaxbbindings.NeuralLayer
NeuralMethod - Interface in weka.classifiers.functions.neural: This is an interface used to create classes that can be used by the neuralnode to perform all it's computations.
NeuralNetwork - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML Neural Network model.
NeuralNetwork(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.NeuralNetwork
NeuralNetwork - Class in weka.core.pmml.jaxbbindings: Java class for NeuralNetwork element declaration.
NeuralNetwork() - Constructor for class weka.core.pmml.jaxbbindings.NeuralNetwork
NeuralNode - Class in weka.classifiers.functions.neural: This class is used to represent a node in the neuralnet.
NeuralNode(String, Random, NeuralMethod) - Constructor for class weka.classifiers.functions.neural.NeuralNode
NeuralOutput - Class in weka.core.pmml.jaxbbindings: Java class for NeuralOutput element declaration.
NeuralOutput() - Constructor for class weka.core.pmml.jaxbbindings.NeuralOutput
NeuralOutputs - Class in weka.core.pmml.jaxbbindings: Java class for NeuralOutputs element declaration.
NeuralOutputs() - Constructor for class weka.core.pmml.jaxbbindings.NeuralOutputs
Neuron - Class in weka.core.pmml.jaxbbindings: Java class for Neuron element declaration.
Neuron() - Constructor for class weka.core.pmml.jaxbbindings.Neuron
NEW_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent
newClassLoader() - Static method in class weka.core.scripting.Groovy: initializes and returns a Groovy Interpreter.
newClock() - Static method in class weka.core.Debug: returns a new instance of a clock
newDataFormat(DataSetEvent) - Method in class weka.gui.beans.ClassAssignerCustomizer
newDataFormat(DataSetEvent) - Method in interface weka.gui.beans.DataFormatListener: Recieve a DataSetEvent that encapsulates a new data format.
newDocument(String, String) - Method in class weka.core.xml.XMLDocument: creates a new Document with the given information.
newEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit: Computes entropy of distribution after splitting.
Newick - Static variable in interface weka.core.Drawable
newInstance(File, Class<?>) - Static method in class weka.core.scripting.Groovy: loads the module and returns a new instance of it as instance of the provided Java class template.
newInstance(File, Class<?>) - Static method in class weka.core.scripting.Jython: loads the module and returns a new instance of it as instance of the provided Java class template.
newInstance(File, Class<?>, File[]) - Static method in class weka.core.scripting.Jython: loads the module and returns a new instance of it as instance of the provided Java class template.
newInstance() - Method in class weka.gui.ExtensionFileFilterWithClass: Creates a new instance of the underlying class.
newInterpreter() - Static method in class weka.core.scripting.Jython: initializes and returns a Python Interpreter
newLog(String, int, int) - Static method in class weka.core.Debug: returns a new Log instance
newNominalRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR: Create a rule branching on this nominal attribute.
newNumericRule(Attribute, Instances, int[]) - Method in class weka.classifiers.rules.OneR: Create a rule branching on this numeric attribute
newPlotStarted(String) - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView
newPlotStarted(String) - Method in interface weka.knowledgeflow.steps.BoundaryPlotter.RenderingUpdateListener: Called when a new plot is started
newPropertiesHandler() - Method in class weka.gui.WekaFileChooser.Factory
newRandom() - Static method in class weka.core.Debug: returns a default debug random object, with no particular seed and debugging enabled.
newRandom(int) - Static method in class weka.core.Debug: returns a debug random object with the specified seed and debugging enabled.
newRule(Attribute, Instances) - Method in class weka.classifiers.rules.OneR: Create a rule branching on this attribute.
newThread(String[]) - Method in class weka.gui.scripting.GroovyScript: Returns a new thread to execute.
newThread(String[]) - Method in class weka.gui.scripting.JythonScript: Returns a new thread to execute.
newThread(String[]) - Method in class weka.gui.scripting.Script: Returns a new thread to execute.
newTimestamp() - Static method in class weka.core.Debug: returns a default timestamp for the current date/time
next() - Method in class weka.classifiers.functions.MultilayerPerceptron: Performs one iteration.
next() - Method in interface weka.classifiers.IterativeClassifier: Performs one iteration.
next - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: next table entry (separate chaining)
next() - Method in class weka.classifiers.meta.AdaBoostM1: Perform the next boosting iteration.
next() - Method in class weka.classifiers.meta.AdditiveRegression: Perform another iteration.
next() - Method in class weka.classifiers.meta.FilteredClassifier: Performs one iteration.
next() - Method in class weka.classifiers.meta.LogitBoost: Perform another iteration of boosting.
next() - Method in class weka.core.Trie.TrieIterator: Returns the next element in the iteration.
next_token() - Method in class weka.core.expressionlanguage.parser.Scanner: Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.
next_token() - Method in class weka.core.json.Scanner: Resumes scanning until the next regular expression is matched, the end of input is encountered or an I/O-Error occurs.
nextBoolean() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, uniformly distributed boolean value from this random number generator's sequence.
nextBytes(byte[]) - Method in class weka.core.Debug.Random: Generates random bytes and places them into a user-supplied byte array.
nextDouble() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.
nextElement(Instances) - Method in class weka.core.converters.ConverterUtils.DataSource: returns the next element and sets the specified dataset, null if none available.
nextElement() - Method in class weka.core.tokenizers.AlphabeticTokenizer: returns the next element
nextElement() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns N-grams and also (N-1)-grams and ....
nextElement() - Method in class weka.core.tokenizers.NGramTokenizer: Returns N-grams and also (N-1)-grams and ....
nextElement() - Method in class weka.core.tokenizers.Tokenizer: Returns the next element of this enumeration if this enumeration object has at least one more element to provide.
nextElement() - Method in class weka.core.tokenizers.WordTokenizer: Returns the next element of this enumeration if this enumeration object has at least one more element to provide.
nextElement() - Method in class weka.core.WekaEnumeration: Returns the next element.
nextErlang(int) - Method in class weka.core.RandomVariates: Generate a value of a variate following standard Erlang distribution.
nextExponential() - Method in class weka.core.RandomVariates: Generate a value of a variate following standard exponential distribution using simple inverse method.
nextFloat() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, uniformly distributed float value between 0.0 and 1.0 from this random number generator's sequence.
nextGamma(double) - Method in class weka.core.RandomVariates: Generate a value of a variate following standard Gamma distribution with shape parameter a.
nextGaussian() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, Gaussian ("normally") distributed double value with mean 0.0 and standard deviation 1.0 from this random number generator's sequence.
nextInt() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.
nextInt(int) - Method in class weka.core.Debug.Random: Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextIteration() - Method in class weka.experiment.Experiment: Carries out the next iteration of the experiment.
nextIteration() - Method in class weka.experiment.RemoteExperiment: Overides the one in Experiment
nextLong() - Method in class weka.core.Debug.Random: Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
NGramMaxSizeTipText() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns the tip text for this property.
NGramMaxSizeTipText() - Method in class weka.core.tokenizers.NGramTokenizer: Returns the tip text for this property.
NGramMinSizeTipText() - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Returns the tip text for this property.
NGramMinSizeTipText() - Method in class weka.core.tokenizers.NGramTokenizer: Returns the tip text for this property.
NGramTokenizer - Class in weka.core.tokenizers: Splits a string into an n-gram with min and max grams.
NGramTokenizer() - Constructor for class weka.core.tokenizers.NGramTokenizer
NNConditionalEstimator - Class in weka.estimators: Conditional probability estimator for a numeric domain conditional upon a numeric domain (using Mahalanobis distance).
NNConditionalEstimator() - Constructor for class weka.estimators.NNConditionalEstimator
NNNORMALIZATIONMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for NN-NORMALIZATION-METHOD.
NO_CLASS - Static variable in class weka.associations.CheckAssociator: a "dummy" class type
NO_CLASS - Static variable in class weka.core.TestInstances: can be used to avoid generating a class attribute
NO_CLASS - Static variable in class weka.gui.SetInstancesPanel: the text denoting "no class" in the class combobox.
NO_COMMAND - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
NO_SUPPORT - Static variable in class weka.gui.GenericObjectEditor.GOETreeNode: color for "no support".
Node - Interface in weka.core.expressionlanguage.core: A node of the AST (abstract syntax tree) for a program
Node - Class in weka.core.pmml.jaxbbindings: Java class for Node element declaration.
Node() - Constructor for class weka.core.pmml.jaxbbindings.Node
Node - Class in weka.gui.treevisualizer: This class records all the data about a particular node for displaying.
Node(String, String, int, int, Color, String) - Constructor for class weka.gui.treevisualizer.Node: This will setup all the values of the node except for its top and center.
NodePlace - Interface in weka.gui.treevisualizer: This is an interface for classes that wish to take a node structure and arrange them
nodeSplitterTipText() - Method in class weka.core.neighboursearch.KDTree: Returns the tip text for this property.
nodeToString() - Method in class weka.classifiers.trees.m5.RuleNode: Returns a description of this node (debugging purposes)
nodeType - Variable in class weka.gui.graphvisualizer.GraphNode: Type of node.
noHeaderRowPresentTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
noHeaderRowTipText() - Method in class weka.core.converters.CSVSaver: Returns the tip text for this property.
noisePercentTipText() - Method in class weka.datagenerators.classifiers.classification.LED24: Returns the tip text for this property
noiseRateTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
noiseTipText() - Method in class weka.classifiers.functions.GaussianProcesses: Returns the tip text for this property
noiseVarianceTipText() - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Returns the tip text for this property
NoMacros - Class in weka.core.expressionlanguage.common: A macro declarations that contains no macros at all
NoMacros() - Constructor for class weka.core.expressionlanguage.common.NoMacros
NOMINAL - Static variable in class weka.core.Attribute: Constant set for nominal attributes.
NominalAntd(Attribute) - Constructor for class weka.classifiers.rules.JRip.NominalAntd: Constructor
NominalAttributeInfo - Class in weka.core: Stores information for nominal and string attributes.
NominalAttributeInfo(List<String>, String) - Constructor for class weka.core.NominalAttributeInfo: Constructs the info based on argument.
nominalAttributesTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
nominalColsTipText() - Method in class weka.datagenerators.clusterers.SubspaceCluster: Returns the tip text for this property
NominalConditionalSufficientStats - Class in weka.classifiers.trees.ht: Maintains sufficient stats for the distribution of a nominal attribute
NominalConditionalSufficientStats() - Constructor for class weka.classifiers.trees.ht.NominalConditionalSufficientStats
nominalCounts - Variable in class weka.core.AttributeStats: Counts of each nominal value
nominalIndicesTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
NominalItem - Class in weka.associations: Class that encapsulates a nominal item.
NominalItem(Attribute, int) - Constructor for class weka.associations.NominalItem: Constructs a new NominalItem.
nominalLabelSpecsTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
nominalLabelsTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
NominalPrediction - Class in weka.classifiers.evaluation: Encapsulates an evaluatable nominal prediction: the predicted probability distribution plus the actual class value.
NominalPrediction(double, double[]) - Constructor for class weka.classifiers.evaluation.NominalPrediction: Creates the NominalPrediction object with a default weight of 1.0.
NominalPrediction(double, double[], double) - Constructor for class weka.classifiers.evaluation.NominalPrediction: Creates the NominalPrediction object.
nominalStringReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
NominalToBinary - Class in weka.filters.supervised.attribute: Converts all nominal attributes into binary numeric attributes.
NominalToBinary() - Constructor for class weka.filters.supervised.attribute.NominalToBinary
NominalToBinary - Class in weka.filters.unsupervised.attribute: Converts all nominal attributes into binary numeric attributes.
NominalToBinary() - Constructor for class weka.filters.unsupervised.attribute.NominalToBinary: Constructor - initialises the filter
nominalToBinaryFilterTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
NominalToString - Class in weka.filters.unsupervised.attribute: Converts a nominal attribute (i.e.
NominalToString() - Constructor for class weka.filters.unsupervised.attribute.NominalToString
nominalWeights - Variable in class weka.core.AttributeStats: Weight mass for each nominal value
NON_NUMERIC - Static variable in class weka.filters.unsupervised.attribute.InterquartileRange: indicator for non-numeric attributes
NONE - Static variable in interface weka.core.converters.Loader: The retrieval modes
NONE - Static variable in interface weka.core.converters.Saver: The retrieval modes
NONE - Static variable in class weka.gui.visualize.VisualizePanelEvent: No longer used
nonEmptyCanopySetIntersection(long[], long[]) - Static method in class weka.clusterers.Canopy: Tests if two sets of canopies have a non-empty intersection
NonSparseToSparse - Class in weka.filters.unsupervised.instance: An instance filter that converts all incoming instances into sparse format.
NonSparseToSparse() - Constructor for class weka.filters.unsupervised.instance.NonSparseToSparse
noPruningTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
noReplacementTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
noReplacementTipText() - Method in class weka.filters.unsupervised.instance.Resample: Returns the tip text for this property
norm() - Method in class weka.core.AlgVector: Returns the norm of the vector
norm1() - Method in class weka.core.matrix.DoubleVector: Returns the L1-norm of the vector
norm1() - Method in class weka.core.matrix.Matrix: One norm
norm2() - Method in class weka.core.matrix.DoubleVector: Returns the L2-norm of the vector
norm2() - Method in class weka.core.matrix.Matrix: Two norm
norm2() - Method in class weka.core.matrix.SingularValueDecomposition: Two norm
NORM_EXPECTED_COST_NAME - Static variable in class weka.classifiers.evaluation.CostCurve: attribute name: Normalized Expected Cost
NORMAL - Static variable in interface weka.gui.graphvisualizer.GraphConstants: NORMAL node - node actually contained in graphs description
normalDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: noraml
NormalEstimator - Class in weka.estimators: Simple probability estimator that places a single normal distribution over the observed values.
NormalEstimator() - Constructor for class weka.estimators.NormalEstimator: No-arg constructor needed to make WEKA's forName() work.
NormalEstimator(double) - Constructor for class weka.estimators.NormalEstimator: Constructor that takes a precision argument.
normalInverse(double) - Static method in class weka.core.Statistics: Returns the value, x, for which the area under the Normal (Gaussian) probability density function (integrated from minus infinity to x) is equal to the argument y (assumes mean is zero, variance is one).
NormalizableDistance - Class in weka.core: Represents the abstract ancestor for normalizable distance functions, like Euclidean or Manhattan distance.
NormalizableDistance() - Constructor for class weka.core.NormalizableDistance: Invalidates the distance function, Instances must be still set.
NormalizableDistance(Instances) - Constructor for class weka.core.NormalizableDistance: Initializes the distance function and automatically initializes the ranges.
normalize() - Method in class weka.classifiers.CostMatrix: Normalizes the matrix so that the diagonal contains zeros.
normalize(double[]) - Static method in class weka.core.Utils: Normalizes the doubles in the array by their sum.
normalize(double[], double) - Static method in class weka.core.Utils: Normalizes the doubles in the array using the given value.
Normalize - Class in weka.filters.unsupervised.attribute: Normalizes all numeric values in the given dataset (apart from the class attribute, if set).
Normalize() - Constructor for class weka.filters.unsupervised.attribute.Normalize
normalizeAttributesTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
normalizeDimWidthsTipText() - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Returns the tip text for this property.
normalizedKernel(char[], char[]) - Method in class weka.classifiers.functions.supportVector.StringKernel: evaluates the normalized kernel between s and t.
normalizeDocLengthTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
normalizeDocLengthTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
normalizeDocLengthTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
normalizeDocLengthTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
NormalizedPolyKernel - Class in weka.classifiers.functions.supportVector: The normalized polynomial kernel.
K(x,y) = <x,y>/sqrt(<x,x><y,y>) where <x,y> = PolyKernel(x,y)
Valid options are:
NormalizedPolyKernel() - Constructor for class weka.classifiers.functions.supportVector.NormalizedPolyKernel: default constructor - does nothing
NormalizedPolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.NormalizedPolyKernel: Creates a new NormalizedPolyKernel instance.
normalizeNodeWidthTipText() - Method in class weka.core.neighboursearch.KDTree: Tip text for this property.
normalizeNumericClassTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
normalizeTipText() - Method in class weka.core.DictionaryBuilder: Tip text for this property
normalProbability(double) - Static method in class weka.core.Statistics: Returns the area under the Normal (Gaussian) probability density function, integrated from minus infinity to x (assumes mean is zero, variance is one).
NormContinuous - Class in weka.core.pmml.jaxbbindings: Java class for NormContinuous element declaration.
NormContinuous() - Constructor for class weka.core.pmml.jaxbbindings.NormContinuous
NormContinuous - Class in weka.core.pmml: Class encapsulating a NormContinuous Expression.
NormContinuous(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.NormContinuous
NormDiscrete - Class in weka.core.pmml.jaxbbindings: Java class for NormDiscrete element declaration.
NormDiscrete() - Constructor for class weka.core.pmml.jaxbbindings.NormDiscrete
NormDiscrete(String, String) - Constructor for class weka.core.pmml.jaxbbindings.NormDiscrete
NormDiscrete - Class in weka.core.pmml: Class encapsulating a NormDiscrete Expression.
NormDiscrete(Element, FieldMetaInfo.Optype, ArrayList<Attribute>) - Constructor for class weka.core.pmml.NormDiscrete: Constructor.
normF() - Method in class weka.core.matrix.Matrix: Frobenius norm
normInf() - Method in class weka.core.matrix.Matrix: Infinity norm
normTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
normTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
normVector() - Method in class weka.core.AlgVector: Norms this vector to length 1.0
NORTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
noSizeDeterminationTipText() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns the tip text for this property
noSizeDeterminationTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the tip text for this property
noSizeDeterminationTipText() - Method in class weka.experiment.RegressionSplitEvaluator: Returns the tip text for this property
NoSplit - Class in weka.classifiers.trees.j48: Class implementing a "no-split"-split.
NoSplit(Distribution) - Constructor for class weka.classifiers.trees.j48.NoSplit: Creates "no-split"-split for given distribution.
NoSupportForMissingValuesException - Exception in weka.core: Exception that is raised by an object that is unable to process data with missing values.
NoSupportForMissingValuesException() - Constructor for exception weka.core.NoSupportForMissingValuesException: Creates a new NoSupportForMissingValuesException with no message.
NoSupportForMissingValuesException(String) - Constructor for exception weka.core.NoSupportForMissingValuesException: Creates a new NoSupportForMissingValuesException.
not(Node) - Static method in class weka.core.expressionlanguage.common.Operators: '!' or 'not' logical not operator
NOT - Static variable in interface weka.core.expressionlanguage.parser.sym
NOT_DRAWABLE - Static variable in interface weka.core.Drawable
notCoveredInstances() - Method in class weka.classifiers.trees.m5.Rule: Get the instances not covered by this rule
Note - Class in weka.gui.beans: Simple bean for displaying a textual note on the layout.
Note() - Constructor for class weka.gui.beans.Note: Constructor
Note - Class in weka.knowledgeflow.steps: A Knowledge Flow "step" that implements a note on the GUI layout
Note() - Constructor for class weka.knowledgeflow.steps.Note
NoteBeanInfo - Class in weka.gui.beans: Bean info class for the Note bean.
NoteBeanInfo() - Constructor for class weka.gui.beans.NoteBeanInfo
NoteCustomizer - Class in weka.gui.beans: Customizer for the note component.
NoteCustomizer() - Constructor for class weka.gui.beans.NoteCustomizer: Constructs a new note customizer
NoteEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for Notes
NoteEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.NoteEditorDialog
NoteVisual - Class in weka.gui.knowledgeflow: Visual representation for the Note "step".
NoteVisual() - Constructor for class weka.gui.knowledgeflow.NoteVisual
notifyCallback(StepTaskCallback, StepTask, ExecutionResult) - Method in interface weka.knowledgeflow.CallbackNotifierDelegate: Notify the supplied callback
notifyCallback(StepTaskCallback, StepTask, ExecutionResult) - Method in class weka.knowledgeflow.DefaultCallbackNotifierDelegate: Notifies the callback immediately
notifyCallback(StepTaskCallback, StepTask, ExecutionResult) - Method in class weka.knowledgeflow.DelayedCallbackNotifierDelegate: Notify the callback.
notifyCapabilitiesFilterListener(Capabilities) - Method in class weka.gui.explorer.Explorer: notifies all the listeners of a change
notifyCapabilitiesFilterListeners(Capabilities) - Method in class weka.gui.WorkbenchApp: Notify filter capabilities listeners of changes
notifyIsDirty() - Method in class weka.gui.knowledgeflow.MainKFPerspective
notifyListener() - Method in class weka.gui.arffviewer.ArffPanel: notfies all listener of the change
notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffSortedTableModel: notfies all listener of the change of the model
notifyListener(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTableModel: notfies all listener of the change of the model
notifyNow() - Method in class weka.knowledgeflow.DelayedCallbackNotifierDelegate: Do the notification now
NotPersistable - Annotation Type in weka.knowledgeflow.steps: Annotation for properties that should not be persisted
NOTRUECHILDSTRATEGY - Enum in weka.core.pmml.jaxbbindings: Java class for NO-TRUE-CHILD-STRATEGY.
NoVariables - Class in weka.core.expressionlanguage.common: A variable declarations that contains no variables
NoVariables() - Constructor for class weka.core.expressionlanguage.common.NoVariables
nowVisible() - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Called by the KnowledgeFlow application once the enclosing JFrame is visible
nowVisible() - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Called by the KnowledgeFlow application once the enclosing JFrame is visible
nowVisible() - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Called by the KnowledgeFlow application once the enclosing JFrame is visible
nrOfGoodOperationsTipText() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber
nrOfLookAheadStepsTipText() - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber
Null - Class in weka.classifiers.evaluation.output.prediction: Suppresses all output.
Null() - Constructor for class weka.classifiers.evaluation.output.prediction.Null
NULL - Static variable in interface weka.core.json.sym
Null - Class in weka.core.stopwords: Dummy stopwords scheme, always returns false.
Null() - Constructor for class weka.core.stopwords.Null
NullStemmer - Class in weka.core.stemmers: A dummy stemmer that performs no stemming at all.
NullStemmer() - Constructor for class weka.core.stemmers.NullStemmer
NUM_DECIMAL_PLACES_DEFAULT - Static variable in class weka.classifiers.AbstractClassifier: The number of decimal places used when printing numbers in the model.
NUM_RAND_COLS - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
numAllConditions(Instances) - Static method in class weka.classifiers.rules.RuleStats: Compute the number of all possible conditions that could appear in a rule of a given data.
numArcsTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the tip text for this property
numArguments() - Method in class weka.core.Option: Returns the option's number of arguments.
numAttributes() - Method in class weka.core.DenseInstance: Returns the number of attributes.
numAttributes() - Method in interface weka.core.Instance: Returns the number of attributes.
numAttributes() - Method in class weka.core.Instances: Returns the number of attributes.
numAttributes() - Method in class weka.core.SparseInstance: Returns the number of attributes.
numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.BayesNet: Returns the tip text for this property
numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns the tip text for this property
numAttributesTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
numAttributesTipText() - Method in class weka.datagenerators.ClusterGenerator: Returns the tip text for this property
numAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns the tip text for this property.
numBags() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of bags.
numberAttributesSelected() - Method in class weka.attributeSelection.AttributeSelection: Return the number of attributes selected from the most recent run of attribute selection
numberOfAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
numberOfClusters() - Method in class weka.clusterers.AbstractClusterer: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.Canopy
numberOfClusters() - Method in interface weka.clusterers.Clusterer: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.Cobweb: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.EM: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.FarthestFirst: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.HierarchicalClusterer
numberOfClusters() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.SimpleKMeans: Returns the number of clusters.
numberOfClusters() - Method in class weka.clusterers.SingleClustererEnhancer: Returns the number of clusters.
NumberOfClustersRequestable - Interface in weka.clusterers: Interface to a clusterer that can generate a requested number of clusters
numberOfLinearModels() - Method in class weka.classifiers.trees.m5.RuleNode: Get the number of linear models in the tree
numBinsTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
numBoostingIterationsTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
numBoostingIterationsTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
numBootstrapRunsToolTipText() - Method in class weka.estimators.UnivariateMixtureEstimator: The tool tip for this property.
numBuiltinTemplates() - Method in class weka.gui.knowledgeflow.TemplateManager: Get the number of builtin KF templates available
numCacheHits() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns the number of cache hits on dot products.
numCacheHits() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the number of dot product cache hits.
numCacheHits() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the number of dot product cache hits.
numCacheHits() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the number of dot product cache hits.
numCentroidsTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns the tip text for this property
numChildred() - Method in class weka.classifiers.trees.ht.SplitNode: Number of child nodes
numChildren() - Method in class weka.gui.HierarchyPropertyParser: The number of the children nodes.
numClassAttributeValues() - Method in class weka.classifiers.functions.SMO
numClasses() - Method in class weka.classifiers.trees.j48.Distribution: Returns number of classes.
numClasses() - Method in class weka.core.AbstractInstance: Returns the number of class labels.
numClasses() - Method in interface weka.core.Instance: Returns the number of class labels.
numClasses() - Method in class weka.core.Instances: Returns the number of class labels.
numClassesTipText() - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Returns the tip text for this property
numClassesTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
numClassified() - Method in class weka.classifiers.evaluation.Evaluation: Returns the number (really, weight) of instances that have been classified.
numClustersTipText() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
numClustersTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
numClustersTipText() - Method in class weka.clusterers.FarthestFirst: Returns the tip text for this property
numClustersTipText() - Method in class weka.clusterers.HierarchicalClusterer
numClustersTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
numClustersTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
numColumns() - Method in class weka.classifiers.CostMatrix: Same as size
numColumns() - Method in class weka.core.Matrix: Deprecated.

Returns the number of columns in the matrix.
numComponentsToolTipText() - Method in class weka.estimators.UnivariateMixtureEstimator: The tool tip for this property.
numCorrect() - Method in class weka.classifiers.trees.j48.Distribution: Returns perClass(maxClass()).
numCorrect(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns perClassPerBag(index,maxClass(index)).
numCyclesTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
numDecimalPlacesTipText() - Method in class weka.classifiers.AbstractClassifier: Returns the tip text for this property
numDecimalPlacesTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
numDecimalPlacesTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
numDecimalsTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
numDistinctValues(int) - Method in class weka.core.Instances: Returns the number of distinct values of a given attribute.
numDistinctValues(Attribute) - Method in class weka.core.Instances: Returns the number of distinct values of a given attribute.
numElements() - Method in class weka.classifiers.functions.supportVector.SMOset: Returns the number of elements in the set.
numElements() - Method in class weka.classifiers.meta.Bagging: Returns the number of elements in the partition.
numElements() - Method in class weka.classifiers.meta.FilteredClassifier: Returns the number of elements in the partition.
numElements() - Method in class weka.classifiers.meta.RandomCommittee: Returns the number of elements in the partition.
numElements() - Method in class weka.classifiers.trees.J48: Returns the number of elements in the partition.
numElements() - Method in class weka.classifiers.trees.RandomTree: Returns the number of elements in the partition.
numElements() - Method in class weka.classifiers.trees.REPTree: Returns the number of elements in the partition.
numElements() - Method in class weka.core.AlgVector: Returns the number of elements in the vector.
numElements() - Method in interface weka.core.PartitionGenerator: Returns the number of elements in the partition.
numEntriesInClassDistribution() - Method in class weka.classifiers.trees.ht.HNode: The size of the class distribution
NUMERIC - Static variable in class weka.core.Attribute: Constant set for numeric attributes.
NumericAntd(Attribute) - Constructor for class weka.classifiers.rules.JRip.NumericAntd: Constructor
numericAttributesTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
NumericCleaner - Class in weka.filters.unsupervised.attribute: A filter that 'cleanses' the numeric data from values that are too small, too big or very close to a certain value, and sets these values to a pre-defined default.
NumericCleaner() - Constructor for class weka.filters.unsupervised.attribute.NumericCleaner
NumericInfo - Class in weka.core.pmml.jaxbbindings: Java class for NumericInfo element declaration.
NumericInfo() - Constructor for class weka.core.pmml.jaxbbindings.NumericInfo
NumericItem - Class in weka.associations: Class that encapsulates a numeric item.
NumericItem(Attribute, double, NumericItem.Comparison) - Constructor for class weka.associations.NumericItem: Constructs a new NumericItem
NumericItem.Comparison - Enum in weka.associations
NumericPrediction - Class in weka.classifiers.evaluation: Encapsulates an evaluatable numeric prediction: the predicted class value plus the actual class value.
NumericPrediction(double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction: Creates the NumericPrediction object with a default weight of 1.0.
NumericPrediction(double, double, double) - Constructor for class weka.classifiers.evaluation.NumericPrediction: Creates the NumericPrediction object.
NumericPrediction(double, double, double, double[][]) - Constructor for class weka.classifiers.evaluation.NumericPrediction: Creates the NumericPrediction object.
NumericPredictor - Class in weka.core.pmml.jaxbbindings: Java class for NumericPredictor element declaration.
NumericPredictor() - Constructor for class weka.core.pmml.jaxbbindings.NumericPredictor
NumericPredictor(String, BigInteger, double) - Constructor for class weka.core.pmml.jaxbbindings.NumericPredictor
numericReplacementValueTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Tip text for this property suitable for displaying in the GUI.
numericStats - Variable in class weka.core.AttributeStats: Stats on numeric value distributions
numericTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
NumericToBinary - Class in weka.filters.unsupervised.attribute: Converts all numeric attributes into binary attributes (apart from the class attribute, if set): if the value of the numeric attribute is exactly zero, the value of the new attribute will be zero.
NumericToBinary() - Constructor for class weka.filters.unsupervised.attribute.NumericToBinary
NumericToDate - Class in weka.filters.unsupervised.attribute: A filter for turning numeric attributes into date attributes.
NumericToDate() - Constructor for class weka.filters.unsupervised.attribute.NumericToDate
NumericToNominal - Class in weka.filters.unsupervised.attribute: A filter for turning numeric attributes into nominal ones.
NumericToNominal() - Constructor for class weka.filters.unsupervised.attribute.NumericToNominal
NumericTransform - Class in weka.filters.unsupervised.attribute: Transforms numeric attributes using a given transformation method.
NumericTransform() - Constructor for class weka.filters.unsupervised.attribute.NumericTransform: Default constructor -- sets the default transform method to java.lang.Math.abs().
numEvals() - Method in class weka.classifiers.functions.supportVector.CachedKernel: Returns the number of time Eval has been called.
numEvals() - Method in class weka.classifiers.functions.supportVector.Kernel: Returns the number of kernel evaluation performed.
numEvals() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Returns the number of kernel evaluation performed.
numEvals() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the number of kernel evaluation performed.
numExamplesTipText() - Method in class weka.datagenerators.ClassificationGenerator: Returns the tip text for this property
numExamplesTipText() - Method in class weka.datagenerators.RegressionGenerator: Returns the tip text for this property
numExecutionSlotsTipText() - Method in class weka.attributeSelection.GreedyStepwise
numExecutionSlotsTipText() - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Returns the tip text for this property
numExecutionSlotsTipText() - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Returns the tip text for this property
numExecutionSlotsTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
numExecutionSlotsTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property
numFalseNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate number (really, weight) of false negatives with respect to a particular class.
numFalseNegatives(int) - Method in class weka.classifiers.Evaluation: Calculate number of false negatives with respect to a particular class.
numFalsePositives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of false positives with respect to a particular class.
numFalsePositives(int) - Method in class weka.classifiers.Evaluation: Calculate number of false positives with respect to a particular class.
numFeaturesTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.CVParameterSelection: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.meta.Stacking: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
numFoldsTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
numFoldsTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
numFoldsTipText() - Method in class weka.experiment.CrossValidationResultProducer: Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the tip text for this property
numFoldsTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
numIncomingConnections() - Method in interface weka.knowledgeflow.StepManager: Get the number of steps that are connected with incoming connections
numIncomingConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Get the number of incoming connections to the managed step
numIncomingConnectionsOfType(String) - Method in interface weka.knowledgeflow.StepManager: Get the number of steps that are connected with the given incoming connection type
numIncomingConnectionsOfType(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get the number of incoming connections to the managed step of a given type
numIncorrect() - Method in class weka.classifiers.trees.j48.Distribution: Returns total-numCorrect().
numIncorrect(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns perBag(index)-numCorrect(index).
numInstances() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).
numInstances() - Method in class weka.classifiers.Evaluation: Gets the number of test instances that had a known class value (actually the sum of the weights of test instances with known class value).
numInstances() - Method in class weka.core.Instances: Returns the number of instances in the dataset.
numInstances() - Method in class weka.core.neighboursearch.balltrees.BallNode: Returns the number of instances in the hyper-spherical region of this node.
numInstances() - Method in class weka.core.neighboursearch.kdtrees.KDTreeNode: Returns the number of Instances in the rectangular region defined by this node.
numIrrelevantTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Returns the tip text for this property
numIterationsTipText() - Method in class weka.classifiers.trees.RandomForest: Returns the tip text for the number of iterations.
numKMeansRunsTipText() - Method in class weka.clusterers.EM: Returns the tip text for this property
numLeaves() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns number of leaves in tree structure.
numLeaves() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the number of leaves (normal count).
numLeaves(int) - Method in class weka.classifiers.trees.m5.RuleNode: Sets the leaves' numbers
numNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of instances not in the given class.
numNeighboursTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
numNodes() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns number of nodes in tree structure.
numNodes() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns the number of nodes.
numNodes() - Method in class weka.classifiers.trees.REPTree: Computes size of the tree.
numNonZero() - Method in class weka.core.pmml.SparseArray: Get the number of non-zero values in this sparse array
numNumericTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property
numOutgoingConnections() - Method in interface weka.knowledgeflow.StepManager: Get the number of steps that are connected with outgoing connections
numOutgoingConnections() - Method in class weka.knowledgeflow.StepManagerImpl: Get the number of outgoing connections from the managed step
numOutgoingConnectionsOfType(String) - Method in interface weka.knowledgeflow.StepManager: Get the number of steps that are connected with the given outgoing connection type
numOutgoingConnectionsOfType(String) - Method in class weka.knowledgeflow.StepManagerImpl: Get the number of outgoing connections from the managed step of a given type
numParameters() - Method in class weka.classifiers.functions.LinearRegression: Get the number of coefficients used in the model
numParameters() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Return the number of parameters (coefficients) in the linear model
numPendingOutput() - Method in class weka.filters.Filter: Returns the number of instances pending output
numPendingOutput() - Method in class weka.filters.unsupervised.attribute.RemoveType: Returns the number of instances pending output
numPluginTemplates() - Method in class weka.gui.knowledgeflow.TemplateManager: Get the number of plugin KF templates available
numPositives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of instances of the given class.
numPredictedNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of instances predicted not to be of the given class.
numPredictedPositives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of instances predicted to be of the given class.
numRepositoryPackages() - Static method in class weka.core.WekaPackageManager: Get the number of packages that are available at the repository.
numResourcesForWithGroupID(String) - Static method in class weka.core.PluginManager: Get the number of resources available under a given resource group ID.
numResourcesForWithGroupID(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Get the number of resources available under a given resource group ID.
numRows() - Method in class weka.classifiers.CostMatrix: Same as size
numRows() - Method in class weka.core.Matrix: Deprecated.

Returns the number of rows in the matrix.
numRules() - Method in class weka.classifiers.rules.part.MakeDecList: Outputs the number of rules in the classifier.
numRulesTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
numRulesToFindTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
numRunsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
numSplits() - Method in class weka.classifiers.trees.ht.SplitCandidate: Number of branches resulting from the split
numSubsets() - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns the number of created subsets for the split.
numTemplates() - Method in class weka.gui.knowledgeflow.TemplateManager: Get the total number of KF templates available
numThreadsTipText() - Method in class weka.attributeSelection.CfsSubsetEval
numThreadsTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer
numThreadsTipText() - Method in class weka.classifiers.meta.LogitBoost
numToEvaluateInParallelTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Tip text for this property.
numToSelectTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
numToSelectTipText() - Method in class weka.attributeSelection.Ranker: Returns the tip text for this property
numTrueNegatives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of true negatives with respect to a particular class.
numTrueNegatives(int) - Method in class weka.classifiers.Evaluation: Calculate the number of true negatives with respect to a particular class.
numTruePositives(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the number (really, weight) of true positives with respect to a particular class.
numTruePositives(int) - Method in class weka.classifiers.Evaluation: Calculate the number of true positives with respect to a particular class.
numValues() - Method in class weka.core.Attribute: Returns the number of attribute values.
numValues() - Method in class weka.core.DenseInstance: Returns the number of values present.
numValues() - Method in interface weka.core.Instance: Returns the number of values present in a sparse representation.
numValues() - Method in class weka.core.pmml.Array: Get the number of values in this array.
numValues() - Method in class weka.core.pmml.SparseArray: Get the number of values in this array.
numValues() - Method in class weka.core.SparseInstance: Returns the number of values in the sparse vector.
numValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property

O

Obfuscate - Class in weka.filters.unsupervised.attribute: A simple instance filter that renames the relation, all attribute names and all nominal attribute values.
Obfuscate() - Constructor for class weka.filters.unsupervised.attribute.Obfuscate
ObjectCellRenderer() - Constructor for class weka.gui.experiment.AlgorithmListPanel.ObjectCellRenderer
ObjectFactory - Class in weka.core.pmml.jaxbbindings: This object contains factory methods for each Java content interface and Java element interface generated in the weka.core.pmml.jaxbbindings package.
ObjectFactory() - Constructor for class weka.core.pmml.jaxbbindings.ObjectFactory: Create a new ObjectFactory that can be used to create new instances of schema derived classes for package: weka.core.pmml.jaxbbindings
objectForName(String) - Static method in class weka.core.WekaPackageClassLoaderManager: Return an instantiated instance of the supplied class name.
obtainVotes(Instance) - Method in class weka.classifiers.functions.SMO: Returns an array of votes for the given instance.
OFF - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
OFF - Static variable in class weka.core.Debug: the log level Off - i.e., no logging
OffscreenChartRenderer - Interface in weka.gui.beans: Interface to something that can render certain types of charts in headless mode.
okPressed() - Method in class weka.gui.knowledgeflow.steps.AttributeSummarizerStepEditorDialog: Called when OK is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.BlockStepEditorDialog: Called when OK is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.ClassAssignerStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.ClassValuePickerStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.DataGridStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.DataVisualizerStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.JoinStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.NoteEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.SendToPerspectiveStepEditorDialog: Handle the OK button
okPressed() - Method in class weka.gui.knowledgeflow.steps.SorterStepEditorDialog: Called when the OK button is pressed
okPressed() - Method in class weka.gui.knowledgeflow.steps.StorePropertiesInEnvironmentStepEditorDialog
okToBeActive() - Method in class weka.gui.AbstractPerspective: Returns true if the perspective is usable at this time.
okToBeActive() - Method in class weka.gui.explorer.AssociationsPanel
okToBeActive() - Method in class weka.gui.explorer.AttributeSelectionPanel
okToBeActive() - Method in class weka.gui.explorer.ClassifierPanel
okToBeActive() - Method in class weka.gui.explorer.ClustererPanel
okToBeActive() - Method in class weka.gui.explorer.VisualizePanel
okToBeActive() - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Returns true if this perspective is OK with being an active perspective - i.e.
okToBeActive() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Returns true if this perspective is OK with being an active perspective - i.e.
okToBeActive() - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Can we be active (i.e.
okToBeActive() - Method in interface weka.gui.Perspective: Returns true if this perspective is OK with being an active perspective - i.e.
okToBeActive() - Method in class weka.gui.SimpleCLIPanel
oldEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit: Computes entropy of distribution before splitting.
omegaTipText() - Method in class weka.classifiers.functions.supportVector.Puk: Returns the tip text for this property
ON - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: Some usefull constants
onDemandDirectoryTipText() - Method in class weka.classifiers.meta.CostSensitiveClassifier
onDemandDirectoryTipText() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns the tip text for this property
OneR - Class in weka.classifiers.rules: Class for building and using a 1R classifier; in other words, uses the minimum-error attribute for prediction, discretizing numeric attributes.
OneR() - Constructor for class weka.classifiers.rules.OneR
OneRAttributeEval - Class in weka.attributeSelection: OneRAttributeEval :

Evaluates the worth of an attribute by using the OneR classifier.

Valid options are:
OneRAttributeEval() - Constructor for class weka.attributeSelection.OneRAttributeEval: Constructor
onUnit(Graphics, int, int, int, int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to determine if the point at x,y is on the unit.
open(File) - Method in class weka.gui.scripting.FileScriptingPanel: Opens the specified file.
open(File) - Method in class weka.gui.scripting.Script: Tries to open the file.
OPEN_DIALOG - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Constant for an open dialog (same as JFileChooser.OPEN_DIALOG)
openFrame(String) - Method in class weka.gui.ResultHistoryPanel: Opens the named result in a separate frame.
openURL(String) - Static method in class weka.gui.BrowserHelper: opens the URL in a browser.
openURL(Component, String) - Static method in class weka.gui.BrowserHelper: opens the URL in a browser.
openURL(Component, String, boolean) - Static method in class weka.gui.BrowserHelper: opens the URL in a browser.
Operators - Class in weka.core.expressionlanguage.common: A class to specify the semantics of operators in the expressionlanguage
Operators() - Constructor for class weka.core.expressionlanguage.common.Operators
Optimization - Class in weka.core: Implementation of Active-sets method with BFGS update to solve optimization problem with only bounds constraints in multi-dimensions.
Optimization() - Constructor for class weka.core.Optimization
optimizationsTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
optimize() - Method in class weka.classifiers.functions.supportVector.RegSMO: finds alpha and alpha* parameters that optimize the SVM target function
OptimumLiftGraph - Class in weka.core.pmml.jaxbbindings: Java class for OptimumLiftGraph element declaration.
OptimumLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.OptimumLiftGraph
Option - Class in weka.core: Class to store information about an option.
Option(String, String, int, String) - Constructor for class weka.core.Option: Creates new option with the given parameters.
OptionHandler - Interface in weka.core: Interface to something that understands options.
OPTIONHANDLER - Static variable in class weka.knowledgeflow.JSONFlowUtils
OptionHandlerJavadoc - Class in weka.core: Generates Javadoc comments from the OptionHandler's options.
OptionHandlerJavadoc() - Constructor for class weka.core.OptionHandlerJavadoc: default constructor
OptionMetadata - Annotation Type in weka.core: Method annotation that can be used with scheme parameters to provide a nice display-ready name for the parameter, help information and command-line option details.
OPTIONS - Static variable in class weka.knowledgeflow.JSONFlowUtils
OPTIONS_ENDTAG - Static variable in class weka.core.OptionHandlerJavadoc: the end comment tag for inserting the generated Javadoc
OPTIONS_STARTTAG - Static variable in class weka.core.OptionHandlerJavadoc: the start comment tag for inserting the generated Javadoc
optionsTipTextHTML() - Method in class weka.gui.beans.AbstractOffscreenChartRenderer: Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form.
optionsTipTextHTML() - Method in interface weka.gui.beans.OffscreenChartRenderer: Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form
optionsTipTextHTML() - Method in class weka.gui.beans.WekaOffscreenChartRenderer: Gets a short list of additional options (if any), suitable for displaying in a tip text, in HTML form
OPTYPE - Enum in weka.core.pmml.jaxbbindings: Java class for OPTYPE.
or(Capabilities) - Method in class weka.core.Capabilities: performs an OR conjunction with the capabilities of the given Capabilities object and updates itself
or(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '|' or 'or' logical or operator
OR - Static variable in interface weka.core.expressionlanguage.parser.sym
ORDERED - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: Constant set for input order (option O)
ordering() - Method in class weka.core.Attribute: Returns the ordering of the attribute.
ORDERING_MODULO - Static variable in class weka.core.Attribute: Constant set for modulo-ordered attributes.
ORDERING_ORDERED - Static variable in class weka.core.Attribute: Constant set for ordered attributes.
ORDERING_SYMBOLIC - Static variable in class weka.core.Attribute: Constant set for symbolic attributes.
orderTipText() - Method in class weka.core.MinkowskiDistance: Returns the tip text for this property.
ORDINAL_SUFFIXES - Static variable in class weka.core.Utils: Suffixes for ordinal representation of indices.
OrdinalToNumeric - Class in weka.filters.unsupervised.attribute: An attribute filter that converts ordinal nominal attributes into numeric ones

Valid options are:
OrdinalToNumeric() - Constructor for class weka.filters.unsupervised.attribute.OrdinalToNumeric
originalValue(double) - Method in class weka.filters.supervised.attribute.ClassOrder: Return the original internal class value given the randomized class value, i.e.
OS_ARCH_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for OS architecture.
OS_NAME_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for OS name.
osAndArchCheck(Package, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks the supplied package against the current OS and architecture.
OUT_OF_MEMORY_THRESHOLD - Static variable in class weka.core.Memory
outcomes - Variable in class weka.gui.graphvisualizer.GraphNode: The outcomes for the given node
outlierFactorTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
OUTLIERTREATMENTMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for OUTLIER-TREATMENT-METHOD.
OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is an output unit.
Output - Class in weka.core.pmml.jaxbbindings: Java class for Output element declaration.
Output() - Constructor for class weka.core.pmml.jaxbbindings.Output
output() - Method in class weka.filters.Filter: Output an instance after filtering and remove from the output queue.
output() - Method in class weka.filters.unsupervised.attribute.RemoveType: Output an instance after filtering and remove from the output queue.
outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property.
outputAdditionalStatsTipText() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns the tip text for this property.
outputClassificationTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
outputData(String, Data) - Method in interface weka.knowledgeflow.StepManager: Output data to all steps connected with the supplied outgoing connection type.
outputData(Data...) - Method in interface weka.knowledgeflow.StepManager: Output one or more Data objects to all relevant steps.
outputData(String, String, Data) - Method in interface weka.knowledgeflow.StepManager: Output a single Data object to the named step with the supplied outgoing connection type
outputData(String, Data) - Method in class weka.knowledgeflow.StepManagerImpl: Output a Data object to all downstream connected Steps that are connected with the supplied connection name.
outputData(Data...) - Method in class weka.knowledgeflow.StepManagerImpl: Output one or more Data objects to all relevant steps.
outputData(String, String, Data) - Method in class weka.knowledgeflow.StepManagerImpl: Outputs the supplied Data object to the named Step.
outputDetailedInfoTipText() - Method in class weka.attributeSelection.CorrelationAttributeEval: Returns the tip text for this property
outputDistributionTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
outputDistributionTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
outputErrorFlagTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
OutputField - Class in weka.core.pmml.jaxbbindings: Java class for OutputField element declaration.
OutputField() - Constructor for class weka.core.pmml.jaxbbindings.OutputField
outputFileName() - Method in class weka.experiment.CSVResultListener: Get the value of OutputFileName.
outputFilenameTipText() - Method in class weka.core.converters.TextDirectoryLoader: the tip text for this property
outputFileTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
outputFileTipText() - Method in class weka.experiment.CrossValidationResultProducer: Returns the tip text for this property
outputFileTipText() - Method in class weka.experiment.CSVResultListener: Returns the tip text for this property
outputFileTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
outputFileTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
outputFormat() - Method in class weka.gui.streams.InstanceJoiner: Gets the format of the output instances.
outputFormat() - Method in class weka.gui.streams.InstanceLoader
outputFormat() - Method in interface weka.gui.streams.InstanceProducer
OutputFormatDialog - Class in weka.gui.experiment: A dialog for setting various output format parameters.
OutputFormatDialog(Frame) - Constructor for class weka.gui.experiment.OutputFormatDialog: initializes the dialog with the given parent frame.
outputItemSetsTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
OutputLogger - Class in weka.core.logging: A logger that logs all output on stdout and stderr to a file.
OutputLogger() - Constructor for class weka.core.logging.OutputLogger
OutputLogger.OutputPrintStream - Class in weka.core.logging: A print stream class to capture all data from stdout and stderr.
outputOffsetMultiplierTipText() - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Returns the tip text for this property
outputOutOfBagComplexityStatisticsTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
outputPeek() - Method in class weka.filters.Filter: Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.filters.unsupervised.attribute.RemoveType: Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.gui.streams.InstanceJoiner: Output an instance after filtering but do not remove from the output queue.
outputPeek() - Method in class weka.gui.streams.InstanceLoader
outputPeek() - Method in interface weka.gui.streams.InstanceProducer
outputPerClassInfoRetrievalStatsTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Return a tip text string for this property
outputPerClassInfoRetrievalStatsTipText() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Return a tip text string for this property
OutputPrintStream(OutputLogger, PrintStream) - Constructor for class weka.core.logging.OutputLogger.OutputPrintStream: Default constructor.
outputProbsForSVMTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
outputs(Vector<Object>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Returns a vector of BeanInstances that can be considered as outputs (or the right-hand side of a sub-flow)
outputsContains(BeanInstance) - Method in class weka.gui.beans.MetaBean
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.Appender: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.Associator: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.BaseStep: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String, Environment) - Method in class weka.knowledgeflow.steps.BaseStep: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.ClassAssigner: Return the structure of data output by this step for a given incoming connection type
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.ClassValuePicker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.DataGenerator: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.DataGrid: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Get, if possible, the outgoing instance structure for the supplied incoming connection type
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.Filter: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.FlowByExpression: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.InstanceStreamToBatchMaker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String, Environment) - Method in class weka.knowledgeflow.steps.Loader: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.SetVariables
outputStructureForConnectionType(String) - Method in interface weka.knowledgeflow.steps.Step: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String, Environment) - Method in interface weka.knowledgeflow.steps.Step: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.SubstringLabeler: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.SubstringReplacer: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.TestSetMaker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.TrainingSetMaker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputStructureForConnectionType(String) - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: If possible, get the output structure for the named connection type as a header-only set of instances.
outputTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
outputTypeSet(int) - Method in class weka.core.Debug.DBO: Return true if the outputtype is set
outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.LinearUnit: This function calculates what the output value should be.
outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to get the output value of this unit.
outputValue(NeuralNode) - Method in interface weka.classifiers.functions.neural.NeuralMethod: This function calculates what the output value should be.
outputValue(boolean) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to get the output value of this unit.
outputValue(NeuralNode) - Method in class weka.classifiers.functions.neural.SigmoidUnit: This function calculates what the output value should be.
outputWordCountsTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
outputWordCountsTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
OutputZipper - Class in weka.experiment: OutputZipper writes output to either gzipped files or to a multi entry zip file.
OutputZipper(File) - Constructor for class weka.experiment.OutputZipper: Constructor.
OVAL - Static variable in class weka.gui.visualize.VisualizePanelEvent

P

p(String) - Static method in class weka.core.Debug.DBO: prints out text.
p() - Method in class weka.core.neighboursearch.CoverTree.CoverTreeNode: Returns the instance represented by the node.
p1evl(double, double[], int) - Static method in class weka.core.Statistics: Evaluates the given polynomial of degree N at x.
Package - Class in weka.core.packageManagement: Abstract base class for Packages.
Package() - Constructor for class weka.core.packageManagement.Package
PACKAGE - Static variable in class weka.core.stemmers.SnowballStemmer: the package name for snowball.
PACKAGE_EXT - Static variable in class weka.core.stemmers.SnowballStemmer: the package name where the stemmers are located.
PackageConstraint - Class in weka.core.packageManagement: Abstract base class for package constraints.
PackageConstraint() - Constructor for class weka.core.packageManagement.PackageConstraint
PackageManager - Class in weka.core.packageManagement: Abstract base class for package managers.
PackageManager() - Constructor for class weka.core.packageManagement.PackageManager
PackageManager - Class in weka.gui: A GUI interface the the package management system.
PackageManager() - Constructor for class weka.gui.PackageManager
packages() - Method in class weka.core.ClassCache: Returns all the stored packages.
PACKAGES_DIR - Static variable in class weka.core.WekaPackageManager: The default packages directory
pad(String, String, int, boolean) - Static method in class weka.core.pmml.PMMLUtils: Utility method to left or right pad strings with arbitrary characters.
padLeft(String, int) - Static method in class weka.core.Utils: Pads a string to a specified length, inserting spaces on the left as required.
padLeftAndAllowOverflow(String, int) - Static method in class weka.core.Utils: Pads a string to a specified length, inserting spaces on the left as required.
padRight(String, int) - Static method in class weka.core.Utils: Pads a string to a specified length, inserting spaces on the right as required.
padRightAndAllowOverflow(String, int) - Static method in class weka.core.Utils: Pads a string to a specified length, inserting spaces on the right as required.
PAGE_HEADER - Static variable in class weka.gui.PackageManager
paint(Graphics) - Method in class weka.gui.ETable: Paints empty rows too, after letting the UI delegate do its painting.
paint(Graphics) - Method in class weka.gui.SplashWindow: Paints the image on the window.
paintBorder(Component, Graphics, int, int, int, int) - Method in class weka.gui.beans.ShadowBorder: Paints the drop shadow border around the given component.
paintBorder(Component, Graphics, int, int, int, int) - Method in class weka.gui.knowledgeflow.ShadowBorder: Paints the drop shadow border around the given component.
paintComponent(Graphics) - Method in class weka.gui.AttributeVisualizationPanel: Paints this component
paintComponent(Graphics) - Method in class weka.gui.beans.BeanVisual
paintComponent(Graphics) - Method in class weka.gui.hierarchyvisualizer.HierarchyVisualizer: Updates the screen contents.
paintComponent(Graphics) - Method in class weka.gui.knowledgeflow.LayoutPanel
paintComponent(Graphics) - Method in class weka.gui.knowledgeflow.NoteVisual
paintComponent(Graphics) - Method in class weka.gui.knowledgeflow.StepVisual
paintComponent(Graphics) - Method in class weka.gui.Main.BackgroundDesktopPane: draws the background image.
paintComponent(Graphics) - Method in class weka.gui.MemoryUsagePanel: draws the background image.
paintComponent(Graphics) - Method in class weka.gui.PropertyPanel: Paints the component, using the property editor's paint method.
paintComponent(Graphics) - Method in class weka.gui.treevisualizer.TreeVisualizer: Updates the screen contents.
paintComponent(Graphics) - Method in class weka.gui.visualize.ClassPanel: Renders this component
paintComponent(Graphics) - Method in class weka.gui.visualize.Plot2D: Renders this component
paintConnections(Graphics, Integer...) - Static method in class weka.gui.beans.BeanConnection: Renders the connections and their names on the supplied graphics context
paintLabels(Graphics, Integer...) - Static method in class weka.gui.beans.BeanInstance: Renders the textual labels for the beans.
paintValue(Graphics, Rectangle) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
paintValue(Graphics, Rectangle) - Method in class weka.gui.ColorEditor: Paint our current color into the supplied bounding box
paintValue(Graphics, Rectangle) - Method in class weka.gui.CostMatrixEditor: Paints a graphical representation of the object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.EnvironmentField
paintValue(Graphics, Rectangle) - Method in class weka.gui.FileEditor: Paints a representation of the current Object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericArrayEditor: Paints a representation of the current classifier.
paintValue(Graphics, Rectangle) - Method in class weka.gui.GenericObjectEditor: Paints a representation of the current Object.
paintValue(Graphics, Rectangle) - Method in class weka.gui.PasswordField
paintValue(Graphics, Rectangle) - Method in class weka.gui.SimpleDateFormatEditor: Paints a graphical representation of the object.
PairCounts - Class in weka.core.pmml.jaxbbindings: Java class for PairCounts element declaration.
PairCounts() - Constructor for class weka.core.pmml.jaxbbindings.PairCounts
PairedCorrectedTTester - Class in weka.experiment: Behaves the same as PairedTTester, only it uses the corrected resampled t-test statistic.
PairedCorrectedTTester() - Constructor for class weka.experiment.PairedCorrectedTTester
PairedDataHelper<P> - Class in weka.knowledgeflow.steps: A helper class that Step implementations can use when processing paired data (e.g.
PairedDataHelper(Step, PairedDataHelper.PairedProcessor, String, String) - Constructor for class weka.knowledgeflow.steps.PairedDataHelper: Constructor
PairedDataHelper.PairedProcessor<P> - Interface in weka.knowledgeflow.steps: Interface for processors of paired data to implement.
PairedStats - Class in weka.experiment: A class for storing stats on a paired comparison (t-test and correlation)
PairedStats(double) - Constructor for class weka.experiment.PairedStats: Creates a new PairedStats object with the supplied significance level.
PairedStatsCorrected - Class in weka.experiment: A class for storing stats on a paired comparison.
PairedStatsCorrected(double, double) - Constructor for class weka.experiment.PairedStatsCorrected: Creates a new PairedStatsCorrected object with the supplied significance level and train/test ratio.
PairedTTester - Class in weka.experiment: Calculates T-Test statistics on data stored in a set of instances.
PairedTTester() - Constructor for class weka.experiment.PairedTTester
pairwiseCoupling(double[][], double[][]) - Static method in class weka.classifiers.meta.MultiClassClassifier: Implements pairwise coupling.
ParallelIteratedSingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel from a single base learner.
ParallelIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.ParallelIteratedSingleClassifierEnhancer
ParallelMultipleClassifiersCombiner - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers.
ParallelMultipleClassifiersCombiner() - Constructor for class weka.classifiers.ParallelMultipleClassifiersCombiner
Parameter - Class in weka.core.pmml.jaxbbindings: Java class for Parameter element declaration.
Parameter() - Constructor for class weka.core.pmml.jaxbbindings.Parameter
ParameterField - Class in weka.core.pmml.jaxbbindings: Java class for ParameterField element declaration.
ParameterField() - Constructor for class weka.core.pmml.jaxbbindings.ParameterField
ParameterList - Class in weka.core.pmml.jaxbbindings: Java class for ParameterList element declaration.
ParameterList() - Constructor for class weka.core.pmml.jaxbbindings.ParameterList
ParamMatrix - Class in weka.core.pmml.jaxbbindings: Java class for ParamMatrix element declaration.
ParamMatrix() - Constructor for class weka.core.pmml.jaxbbindings.ParamMatrix
parentClass - Variable in class weka.experiment.PropertyNode: The class of the object with this property
parentNode() - Method in class weka.classifiers.trees.m5.RuleNode: Get the parent of this node
ParentSet - Class in weka.classifiers.bayes.net: Helper class for Bayes Network classifiers.
ParentSet() - Constructor for class weka.classifiers.bayes.net.ParentSet: default constructor
ParentSet(int) - Constructor for class weka.classifiers.bayes.net.ParentSet: constructor
ParentSet(ParentSet) - Constructor for class weka.classifiers.bayes.net.ParentSet: copy constructor
parentTipText() - Method in class weka.datagenerators.ClusterDefinition: Returns the tip text for this property
parentValue() - Method in class weka.gui.HierarchyPropertyParser: The value in the parent node.
parse(String, VariableDeclarations, MacroDeclarations) - Static method in class weka.core.expressionlanguage.parser.Parser: Tries to parse and compile a program from the textual representation in expr while exposing the variables and marcos
parse() - Method in class weka.gui.graphvisualizer.BIFParser: This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
parse() - Method in class weka.gui.graphvisualizer.DotParser: This method parses the string or the InputStream that we passed in through the constructor and builds up the m_nodes and m_edges vectors
parseDate(String) - Method in class weka.core.Attribute: Parses the given String as Date, according to the current format and returns the corresponding amount of milliseconds.
parseFromInternal(String) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
parseMatlab(String) - Static method in class weka.classifiers.CostMatrix: creates a matrix from the given Matlab string.
parseMatlab(String) - Static method in class weka.core.matrix.Matrix: creates a matrix from the given Matlab string.
parseMatlab(String) - Static method in class weka.core.Matrix: Deprecated.

creates a matrix from the given Matlab string.
parsePath(String) - Static method in class weka.core.PropertyPath.Path: returns a path object based on the given path string
Parser - Class in weka.core.expressionlanguage.parser: CUP v0.11b 20160615 (GIT 4ac7450) generated parser.
Parser() - Constructor for class weka.core.expressionlanguage.parser.Parser: Deprecated.
Parser(Scanner) - Constructor for class weka.core.expressionlanguage.parser.Parser: Deprecated.
Parser(Scanner, SymbolFactory) - Constructor for class weka.core.expressionlanguage.parser.Parser: Constructor which sets the default scanner.
Parser - Class in weka.core.json: CUP v0.11b 20160615 (GIT 4ac7450) generated parser.
Parser() - Constructor for class weka.core.json.Parser: Deprecated.
Parser(Scanner) - Constructor for class weka.core.json.Parser: Deprecated.
Parser(Scanner, SymbolFactory) - Constructor for class weka.core.json.Parser: Constructor which sets the default scanner.
PART - Class in weka.classifiers.rules: Class for generating a PART decision list.
PART() - Constructor for class weka.classifiers.rules.PART
partition(Instances, int) - Static method in class weka.classifiers.rules.RuleStats: Patition the data into 2, first of which has (numFolds-1)/numFolds of the data and the second has 1/numFolds of the data
Partition - Class in weka.core.pmml.jaxbbindings: Java class for Partition element declaration.
Partition() - Constructor for class weka.core.pmml.jaxbbindings.Partition
PartitionedMultiFilter - Class in weka.filters.unsupervised.attribute: A filter that applies filters on subsets of attributes and assembles the output into a new dataset.
PartitionedMultiFilter() - Constructor for class weka.filters.unsupervised.attribute.PartitionedMultiFilter
PartitionFieldStats - Class in weka.core.pmml.jaxbbindings: Java class for PartitionFieldStats element declaration.
PartitionFieldStats() - Constructor for class weka.core.pmml.jaxbbindings.PartitionFieldStats
PartitionGenerator - Interface in weka.core: This interface can be implemented by algorithms that generate a partition of the instance space (e.g., decision trees).
partitionGeneratorTipText() - Method in class weka.filters.supervised.attribute.PartitionMembership: Returns a description of this option suitable for display as a tip text in the gui.
PartitionMembership - Class in weka.filters.supervised.attribute: * A filter that uses a PartitionGenerator to generate partition membership values; filtered instances are composed of these values plus the class attribute (if set in the input data) and rendered as sparse instances.
PartitionMembership() - Constructor for class weka.filters.supervised.attribute.PartitionMembership
partitionOptions(String[]) - Static method in class weka.classifiers.bayes.BayesNet: Returns the secondary set of options (if any) contained in the supplied options array.
partitionOptions(String[]) - Static method in class weka.core.Utils: Returns the secondary set of options (if any) contained in the supplied options array.
passesTest(Instance) - Method in class weka.datagenerators.Test: Determines whether an instance passes the test.
PasswordField - Class in weka.gui: Property editor widget that wraps and displays a JPasswordField.
PasswordField() - Constructor for class weka.gui.PasswordField
PasswordField(String) - Constructor for class weka.gui.PasswordField
PasswordProperty - Annotation Type in weka.gui: Method annotation that can be used to indicate that a property is a password.
passwordTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
passwordTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
passwordTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
paste(String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Apply paste operation with XMLBIF fragment.
Path(String) - Constructor for class weka.core.PropertyPath.Path: uses the given dot-path
Path(Vector<PropertyPath.PathElement>) - Constructor for class weka.core.PropertyPath.Path: uses the vector with PathElement objects to initialize with
Path(String[]) - Constructor for class weka.core.PropertyPath.Path: uses the given array as elements for the path
PathElement(String) - Constructor for class weka.core.PropertyPath.PathElement: initializes the path element with the given property
pattern(int, int) - Static method in class weka.core.matrix.FloatingPointFormat
patternTipText() - Method in class weka.datagenerators.clusterers.BIRCHCluster: Returns the tip text for this property
PCell - Class in weka.core.pmml.jaxbbindings: Java class for PCell element declaration.
PCell() - Constructor for class weka.core.pmml.jaxbbindings.PCell
PCell(String, String, BigInteger, double) - Constructor for class weka.core.pmml.jaxbbindings.PCell
pchisq(double) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of the Chi-squared distribution
pchisq(double, double) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of the noncentral Chi-squared distribution.
pchisq(double, DoubleVector) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of a set of noncentral Chi-squared distributions.
PCovCell - Class in weka.core.pmml.jaxbbindings: Java class for PCovCell element declaration.
PCovCell() - Constructor for class weka.core.pmml.jaxbbindings.PCovCell
PCovMatrix - Class in weka.core.pmml.jaxbbindings: Java class for PCovMatrix element declaration.
PCovMatrix() - Constructor for class weka.core.pmml.jaxbbindings.PCovMatrix
pctCorrect() - Method in class weka.classifiers.evaluation.Evaluation: Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
pctCorrect() - Method in class weka.classifiers.Evaluation: Gets the percentage of instances correctly classified (that is, for which a correct prediction was made).
pctIncorrect() - Method in class weka.classifiers.evaluation.Evaluation: Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
pctIncorrect() - Method in class weka.classifiers.Evaluation: Gets the percentage of instances incorrectly classified (that is, for which an incorrect prediction was made).
pctUnclassified() - Method in class weka.classifiers.evaluation.Evaluation: Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
pctUnclassified() - Method in class weka.classifiers.Evaluation: Gets the percentage of instances not classified (that is, for which no prediction was made by the classifier).
peek() - Method in class weka.core.Queue: Gets object from the front of the queue.
PENTAHO_IMAGE1 - Static variable in class weka.core.RepositoryIndexGenerator
PENTAHO_IMAGE2 - Static variable in class weka.core.RepositoryIndexGenerator
perBag(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of (possibly fractional) instances in given bag.
percentageTipText() - Method in class weka.filters.unsupervised.instance.RemovePercentage: Returns the tip text for this property
percentAttributesUsed() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns the fraction of all attributes in the data that are used in the logistic model (in percent).
percentTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
percentTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
perClass(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of (possibly fractional) instances of given class.
perClassPerBag(int, int) - Method in class weka.classifiers.trees.j48.Distribution: Returns number of (possibly fractional) instances of given class in given bag.
PerformanceStats - Class in weka.core.neighboursearch: The class that measures the performance of a nearest neighbour search (NNS) algorithm.
PerformanceStats() - Constructor for class weka.core.neighboursearch.PerformanceStats: default constructor.
performCommand(Object...) - Method in class weka.gui.knowledgeflow.AbstractGraphicalCommand: Perform the command
performCommand(Object...) - Method in class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand: Execute the command
performCommand(String, Object...) - Method in interface weka.gui.knowledgeflow.GraphicalEnvironmentCommandHandler: Attempt to perform a graphical command (if supported) in the current graphical environment
performCommand(String, Object...) - Method in class weka.gui.knowledgeflow.KFGraphicalEnvironmentCommandHandler: Perform a command
performCommand(Object...) - Method in class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand: Execute the command
performRequest(String) - Method in class weka.gui.beans.Associator: Perform a particular request
performRequest(String) - Method in class weka.gui.beans.AttributeSummarizer: Perform a named user request
performRequest(String) - Method in class weka.gui.beans.Classifier: Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Perform the named request
performRequest(String) - Method in class weka.gui.beans.Clusterer: Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Perform the named request
performRequest(String) - Method in class weka.gui.beans.CostBenefitAnalysis
performRequest(String) - Method in class weka.gui.beans.CrossValidationFoldMaker: Perform the named request
performRequest(String) - Method in class weka.gui.beans.DataVisualizer: Describe performRequest method here.
performRequest(String) - Method in class weka.gui.beans.Filter: Perform the named request
performRequest(String) - Method in class weka.gui.beans.GraphViewer: Perform the named request
performRequest(String) - Method in class weka.gui.beans.ImageViewer
performRequest(String) - Method in class weka.gui.beans.MetaBean: Perform a particular request
performRequest(String) - Method in class weka.gui.beans.ModelPerformanceChart: Describe performRequest method here.
performRequest(String) - Method in class weka.gui.beans.ScatterPlotMatrix: Perform a named user request
performRequest(String) - Method in class weka.gui.beans.StripChart: Describe performRequest method here.
performRequest(String) - Method in class weka.gui.beans.TextViewer: Perform the named request
performRequest(String) - Method in class weka.gui.beans.TrainTestSplitMaker: Perform the named request
performRequest(String) - Method in interface weka.gui.beans.UserRequestAcceptor: Perform the named request
periodicPruningRateTipText() - Method in class weka.clusterers.Canopy: Returns the tip text for this property.
periodicPruningTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
periodicPruningTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
periodicPruningTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
periodicPruningTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
Perspective - Interface in weka.gui: Interface for GUI elements that can appear as a perspective in a GUIApplication.
PERSPECTIVE_INTERFACE - Static variable in class weka.gui.PerspectiveManager: Interface name of perspectives
PerspectiveInfo - Annotation Type in weka.gui
PerspectiveManager - Class in weka.gui: Manages perspectives and the main menu bar (if visible), holds the currently selected perspective, and implements the perspective button bar.
PerspectiveManager(GUIApplication, String...) - Constructor for class weka.gui.PerspectiveManager: Constructor
PerspectiveManager(GUIApplication, String[], String[]) - Constructor for class weka.gui.PerspectiveManager: Constructor
PerspectiveManager.SelectedPerspectivePreferences - Class in weka.gui: Class to manage user preferences with respect to visible perspectives and whether the perspectives toolbar is always hidden or is visible on application startup
perspectiveToolBarIsVisible() - Method in class weka.gui.PerspectiveManager: Returns true if the perspective toolbar is visible
perturbationFractionTipText() - Method in class weka.datagenerators.classifiers.classification.Agrawal: Returns the tip text for this property
phaseIID(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: See Sugiyama et al.
phaseIIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: See Sugiyama et al.
phaseIU(int, int[][]) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: See Sugiyama et al.
PI - Static variable in class weka.core.xml.XMLDocument: the parsing instructions "<?xml version=\"1.0\" encoding=\"utf-8\"?>" (may not show up in Javadoc due to tags!).
PKIDiscretize - Class in weka.filters.unsupervised.attribute: Discretizes numeric attributes using equal frequency binning and forces the number of bins to be equal to the square root of the number of values of the numeric attribute.

For more information, see:

Ying Yang, Geoffrey I.
PKIDiscretize() - Constructor for class weka.filters.unsupervised.attribute.PKIDiscretize
place(Node) - Method in interface weka.gui.treevisualizer.NodePlace: The function to call to postion the tree that starts at Node r
place(Node) - Method in class weka.gui.treevisualizer.PlaceNode1: Call this function to have each node in the tree starting at 'r' placed in a visual (not logical, they already are) tree position.
place(Node) - Method in class weka.gui.treevisualizer.PlaceNode2: The Funtion to call to have the nodes arranged.
PlaceNode1 - Class in weka.gui.treevisualizer: This class will place the Nodes of a tree.
PlaceNode1() - Constructor for class weka.gui.treevisualizer.PlaceNode1
PlaceNode2 - Class in weka.gui.treevisualizer: This class will place the Nodes of a tree.
PlaceNode2() - Constructor for class weka.gui.treevisualizer.PlaceNode2
PlainText - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions in plain text.
PlainText() - Constructor for class weka.classifiers.evaluation.output.prediction.PlainText
PLAINTEXT_ENDTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the end comment tag for inserting the generated BibTex
PLAINTEXT_STARTTAG - Static variable in class weka.core.TechnicalInformationHandlerJavadoc: the start comment tag for inserting the generated BibTex
pln(String) - Static method in class weka.core.Debug.DBO: prints out text + endofline.
Plot2D - Class in weka.gui.visualize: This class plots datasets in two dimensions.
Plot2D() - Constructor for class weka.gui.visualize.Plot2D: Constructor
Plot2DCompanion - Interface in weka.gui.visualize: Interface for classes that need to draw to the Plot2D panel *before* Plot2D renders anything (eg.
PLOT_SIZE - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
PLOT_SIZE_KEY - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
PlotData2D - Class in weka.gui.visualize: This class is a container for plottable data.
PlotData2D(Instances) - Constructor for class weka.gui.visualize.PlotData2D: Construct a new PlotData2D using the supplied instances
plotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Render the training points on-screen.
plotTrainingData() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Plots the training data on-screen.
plotTrainingData(Instances) - Method in class weka.knowledgeflow.steps.BoundaryPlotter
PluginManager - Class in weka.core: Class that manages a global map of plugins.
PluginManager() - Constructor for class weka.core.PluginManager
PluginManager - Class in weka.gui.beans: Deprecated.
Use weka.core.PluginManager instead
PluginManager() - Constructor for class weka.gui.beans.PluginManager: Deprecated.
pluginRegistered(String, String) - Static method in class weka.core.PluginManager: Checks if a named plugin exists in the map of registered plugins
PLURAL_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants: PLURAL_DUMMY node - node with more than one outgoing edge i.e.
plus(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '+' plus operator
PLUS - Static variable in interface weka.core.expressionlanguage.parser.sym
plus(double) - Method in class weka.core.matrix.DoubleVector: Adds a value to all the elements
plus(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Adds another vector element by element
plus(Matrix) - Method in class weka.core.matrix.Matrix: C = A + B
PLUS_SHAPE - Static variable in class weka.gui.visualize.Plot2D
plusEquals(double) - Method in class weka.core.matrix.DoubleVector: Adds a value to all the elements in place
plusEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Adds another vector in place element by element
plusEquals(Matrix) - Method in class weka.core.matrix.Matrix: A = A + B
pmiss - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: transformation probability to missing value
PMML - Class in weka.core.pmml.jaxbbindings: Java class for PMML element declaration.
PMML() - Constructor for class weka.core.pmml.jaxbbindings.PMML
PMML_FILE_EXTENSION - Static variable in class weka.gui.explorer.ClassifierPanel: The filename extension that should be used for PMML xml files.
PMML_VERSION - Static variable in class weka.classifiers.pmml.producer.AbstractPMMLProducerHelper: PMML version that the jaxbbindings were created from
PMMLClassifier - Class in weka.classifiers.pmml.consumer: Abstract base class for all PMML classifiers.
PMMLFactory - Class in weka.core.pmml: This class is a factory class for reading/writing PMML models
PMMLFactory() - Constructor for class weka.core.pmml.PMMLFactory
PMMLModel - Interface in weka.core.pmml: Interface for all PMML models
PMMLProducer - Interface in weka.core.pmml: Interface to something that can produce a PMML representation of itself.
PMMLUtils - Class in weka.core.pmml: Utility routines.
PMMLUtils() - Constructor for class weka.core.pmml.PMMLUtils
PNGWriter - Class in weka.gui.visualize: This class takes any JComponent and outputs it to a PNG-file.
PNGWriter() - Constructor for class weka.gui.visualize.PNGWriter: initializes the object.
PNGWriter(JComponent) - Constructor for class weka.gui.visualize.PNGWriter: initializes the object with the given Component.
PNGWriter(JComponent, File) - Constructor for class weka.gui.visualize.PNGWriter: initializes the object with the given Component and filename.
pnorm(double) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of the standard normal.
pnorm(double, double, double) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of a normal distribution.
pnorm(double, DoubleVector, double) - Static method in class weka.core.matrix.Maths: Returns the cumulative probability of a set of normal distributions with different means.
POINT - Static variable in class weka.core.Version: point revision
POINT_SIZE - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
POINT_SIZE_KEY - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
PointsClosestToFurthestChildren - Class in weka.core.neighboursearch.balltrees: Implements the Moore's method to split a node of a ball tree.

For more information please see section 2 of the 1st and 3.2.3 of the 2nd:

Andrew W.
PointsClosestToFurthestChildren() - Constructor for class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Constructor.
PointsClosestToFurthestChildren(int[], Instances, EuclideanDistance) - Constructor for class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Constructor.
PoissonDistribution - Class in weka.core.pmml.jaxbbindings: Java class for PoissonDistribution element declaration.
PoissonDistribution() - Constructor for class weka.core.pmml.jaxbbindings.PoissonDistribution
PoissonEstimator - Class in weka.estimators: Simple probability estimator that places a single Poisson distribution over the observed values.
PoissonEstimator() - Constructor for class weka.estimators.PoissonEstimator
polevl(double, double[], int) - Static method in class weka.core.Statistics: Evaluates the given polynomial of degree N at x.
POLYGON - Static variable in class weka.gui.visualize.VisualizePanelEvent
PolyKernel - Class in weka.classifiers.functions.supportVector: The polynomial kernel : K(x, y) = <x, y>^p or K(x, y) = (<x, y>+1)^p
Valid options are:
PolyKernel() - Constructor for class weka.classifiers.functions.supportVector.PolyKernel: default constructor - does nothing.
PolyKernel(Instances, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.PolyKernel: Creates a new PolyKernel instance.
PolynomialKernelType - Class in weka.core.pmml.jaxbbindings: Java class for PolynomialKernelType element declaration.
PolynomialKernelType() - Constructor for class weka.core.pmml.jaxbbindings.PolynomialKernelType
poolSizeTipText() - Method in class weka.attributeSelection.CfsSubsetEval
poolSizeTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer
poolSizeTipText() - Method in class weka.classifiers.meta.LogitBoost
pop() - Method in class weka.core.neighboursearch.covertrees.Stack: Pops (removes) the first (last added) element in the stack.
pop() - Method in class weka.core.Queue: Pops an object from the front of the queue.
populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
populationSizeTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
position() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Returns the position of the split in the sorted values.
position() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Returns the position of the split in the sorted values.
position() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Returns the position of the split in the sorted values.
positiveIndexTipText() - Method in class weka.associations.FPGrowth: Tip text for this property suitable for displaying in the GUI.
postExecution() - Method in class weka.associations.AbstractAssociator: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.attributeSelection.ASEvaluation: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.classifiers.AbstractClassifier: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.classifiers.meta.Stacking
postExecution() - Method in class weka.classifiers.MultipleClassifiersCombiner
postExecution() - Method in class weka.classifiers.SingleClassifierEnhancer
postExecution() - Method in class weka.clusterers.AbstractClusterer: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in interface weka.core.CommandlineRunnable: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.core.converters.TextDirectoryLoader: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.core.FindWithCapabilities
postExecution() - Method in class weka.core.ListOptions
postExecution() - Method in class weka.filters.Filter: Perform any teardown stuff that might need to happen after execution.
postExecution() - Method in class weka.knowledgeflow.FlowRunner
postProcess(int[]) - Method in class weka.attributeSelection.ASEvaluation: Provides a chance for a attribute evaluator to do any special post processing of the selected attribute set.
postProcess(int[]) - Method in class weka.attributeSelection.CfsSubsetEval: Calls locallyPredictive in order to include locally predictive attributes (if requested).
postProcess(int[]) - Method in class weka.attributeSelection.GainRatioAttributeEval
postProcess(int[]) - Method in class weka.attributeSelection.OneRAttributeEval
postProcess(int[]) - Method in class weka.attributeSelection.ReliefFAttributeEval
postProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer: When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.AveragingResultProducer: When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.CrossValidationResultProducer: Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener: Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener: Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer: When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.DatabaseResultProducer: When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.Experiment: Signals that the experiment is finished running, so that cleanup can be done.
postProcess() - Method in class weka.experiment.ExplicitTestsetResultProducer: Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener: Perform any postprocessing.
postProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer: When this method is called, it indicates that no more results will be sent that need to be grouped together in any way.
postProcess() - Method in class weka.experiment.LearningRateResultProducer: When this method is called, it indicates that no more requests to generate results for the current experiment will be sent.
postProcess() - Method in class weka.experiment.RandomSplitResultProducer: Perform any postprocessing.
postProcess() - Method in class weka.experiment.RemoteExperiment: overides the one in Experiment
postProcess(ResultProducer) - Method in interface weka.experiment.ResultListener: Perform any postprocessing.
postProcess() - Method in interface weka.experiment.ResultProducer: Perform any postprocessing.
postProcessDistances(double[]) - Method in interface weka.core.DistanceFunction: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.EuclideanDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.FilteredDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.MinkowskiDistance: Does post processing of the distances (if necessary) returned by distance(distance(Instance first, Instance second, double cutOffValue).
postProcessDistances(double[]) - Method in class weka.core.NormalizableDistance: Does nothing, derived classes may override it though.
PostProcessor() - Constructor for class weka.core.CheckScheme.PostProcessor
PostProcessor() - Constructor for class weka.estimators.CheckEstimator.PostProcessor
PostscriptGraphics - Class in weka.gui.visualize: The PostscriptGraphics class extends the Graphics2D class to produce an encapsulated postscript file rather than on-screen display.
PostscriptGraphics(int, int, OutputStream) - Constructor for class weka.gui.visualize.PostscriptGraphics: Constructor Creates a new PostscriptGraphics object, given dimensions and output file.
PostscriptWriter - Class in weka.gui.visualize: This class takes any Component and outputs it to a Postscript file.
PostscriptWriter() - Constructor for class weka.gui.visualize.PostscriptWriter: initializes the object
PostscriptWriter(JComponent) - Constructor for class weka.gui.visualize.PostscriptWriter: initializes the object with the given Component
PostscriptWriter(JComponent, File) - Constructor for class weka.gui.visualize.PostscriptWriter: initializes the object with the given Component and filename
potential(int, double, double[], double[], boolean) - Method in class weka.classifiers.rules.RuleStats: Calculate the potential to decrease DL of the ruleset, i.e.
PotentialClassIgnorer - Class in weka.filters.unsupervised.attribute: This filter should be extended by other unsupervised attribute filters to allow processing of the class attribute if that's required.
PotentialClassIgnorer() - Constructor for class weka.filters.unsupervised.attribute.PotentialClassIgnorer
pow(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '^' power operator
POW - Static variable in interface weka.core.expressionlanguage.parser.sym
powerSeries(double, double, double) - Static method in class weka.core.Statistics: Power series for incomplete beta integral.
PPCell - Class in weka.core.pmml.jaxbbindings: Java class for PPCell element declaration.
PPCell() - Constructor for class weka.core.pmml.jaxbbindings.PPCell
PPMatrix - Class in weka.core.pmml.jaxbbindings: Java class for PPMatrix element declaration.
PPMatrix() - Constructor for class weka.core.pmml.jaxbbindings.PPMatrix
preBuiltClassifiersTipText() - Method in class weka.classifiers.meta.Vote: Returns the tip text for this property
precision(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the precision with respect to a particular class.
precision(int) - Method in class weka.classifiers.Evaluation: Calculate the precision with respect to a particular class.
PRECISION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Precision
PRECLUDES_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for package preclusion
preComputeCorrelationMatrixTipText() - Method in class weka.attributeSelection.CfsSubsetEval
PrecomputedKernelMatrixKernel - Class in weka.classifiers.functions.supportVector: This kernel is based on a static kernel matrix that is read from a file.
PrecomputedKernelMatrixKernel() - Constructor for class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel
PreConstructedLinearModel - Class in weka.classifiers.trees.m5: This class encapsulates a linear regression function.
PreConstructedLinearModel(double[], double) - Constructor for class weka.classifiers.trees.m5.PreConstructedLinearModel: Constructor
predicted() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the predicted class value.
predicted() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the predicted class value.
predicted() - Method in interface weka.classifiers.evaluation.Prediction: Gets the predicted class value.
predictedClassCounts() - Method in class weka.classifiers.evaluation.Evaluation: Returns the predicted number (really, weight) of instances in each class.
predictIntervals(Instance, double) - Method in class weka.classifiers.functions.GaussianProcesses: Computes a prediction interval for the given instance and confidence level.
predictIntervals(Instance, double) - Method in interface weka.classifiers.IntervalEstimator: Returns an N * 2 array, where N is the number of prediction intervals.
predictIntervals(Instance, double) - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns an N * 2 array, where N is the number of prediction intervals.
predictIntervals(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns the interval for the given confidence value.
predictIntervals(double) - Method in interface weka.estimators.UnivariateIntervalEstimator: Returns the intervals at the given confidence value.
predictIntervals(double) - Method in class weka.estimators.UnivariateKernelEstimator: Returns the interval for the given confidence value.
predictIntervals(double) - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Returns the interval for the given confidence value.
predictIntervals(double) - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the interval for the given confidence value.
predictIntervals(double) - Method in class weka.estimators.UnivariateNormalEstimator: Returns the interval for the given confidence value.
prediction - Variable in class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer: the prediction.
Prediction - Interface in weka.classifiers.evaluation: Encapsulates a single evaluatable prediction: the predicted value plus the actual class value.
PredictionAppender - Class in weka.gui.beans: Bean that can can accept batch or incremental classifier events and produce dataset or instance events which contain instances with predictions appended.
PredictionAppender() - Constructor for class weka.gui.beans.PredictionAppender: Creates a new PredictionAppender instance.
PredictionAppender - Class in weka.knowledgeflow.steps: Step that can produce data with predictions appended from batch or incremental classifiers and clusterers
PredictionAppender() - Constructor for class weka.knowledgeflow.steps.PredictionAppender
PredictionAppenderBeanInfo - Class in weka.gui.beans: Bean info class for PredictionAppender.
PredictionAppenderBeanInfo() - Constructor for class weka.gui.beans.PredictionAppenderBeanInfo
PredictionAppenderCustomizer - Class in weka.gui.beans: GUI Customizer for the prediction appender bean
PredictionAppenderCustomizer() - Constructor for class weka.gui.beans.PredictionAppenderCustomizer
PredictionContainer() - Constructor for class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer
predictionIntervals() - Method in class weka.classifiers.evaluation.NumericPrediction: Returns the predictions intervals.
predictions() - Method in class weka.classifiers.evaluation.Evaluation: Returns the predictions that have been collected.
predictions() - Method in class weka.classifiers.Evaluation: Returns the predictions that have been collected.
PredictiveModelQuality - Class in weka.core.pmml.jaxbbindings: Java class for PredictiveModelQuality element declaration.
PredictiveModelQuality() - Constructor for class weka.core.pmml.jaxbbindings.PredictiveModelQuality
Predictor - Class in weka.core.pmml.jaxbbindings: Java class for Predictor element declaration.
Predictor() - Constructor for class weka.core.pmml.jaxbbindings.Predictor
PredictorTerm - Class in weka.core.pmml.jaxbbindings: Java class for PredictorTerm element declaration.
PredictorTerm() - Constructor for class weka.core.pmml.jaxbbindings.PredictorTerm
predictQuantile(double) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns the quantile for the given percentage.
predictQuantile(double) - Method in class weka.estimators.UnivariateKernelEstimator: Returns the quantile for the given percentage.
predictQuantile(double) - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Returns the quantile for the given percentage.
predictQuantile(double) - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the quantile for the given percentage.
predictQuantile(double) - Method in class weka.estimators.UnivariateNormalEstimator: Returns the quantile for the given percentage.
predictQuantile(double) - Method in interface weka.estimators.UnivariateQuantileEstimator: Returns the quantile for the given percentage
preExecution() - Method in class weka.associations.AbstractAssociator: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in class weka.attributeSelection.ASEvaluation: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in class weka.classifiers.AbstractClassifier: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in class weka.classifiers.meta.Stacking
preExecution() - Method in class weka.classifiers.MultipleClassifiersCombiner
preExecution() - Method in class weka.classifiers.SingleClassifierEnhancer
preExecution() - Method in class weka.clusterers.AbstractClusterer: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in interface weka.core.CommandlineRunnable: Perform any setup stuff that might need to happen before execution.
preExecution() - Method in class weka.core.converters.TextDirectoryLoader: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in class weka.core.FindWithCapabilities
preExecution() - Method in class weka.core.ListOptions
preExecution() - Method in class weka.filters.Filter: Perform any setup stuff that might need to happen before commandline execution.
preExecution() - Method in class weka.knowledgeflow.FlowRunner
preferredLayoutSize(Container) - Method in class weka.gui.WrapLayout: Returns the preferred dimensions for this layout given the visible components in the specified target container.
prefix() - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns tree in prefix order.
prefix() - Method in class weka.classifiers.trees.J48: Returns tree in prefix order.
prefix() - Method in interface weka.core.Matchable: Returns a string that describes a tree representing the object in prefix order.
prepareRenderer(TableCellRenderer, int, int) - Method in class weka.gui.ETable: Shades alternate rows in different colors.
prePlot(Graphics) - Method in interface weka.gui.visualize.Plot2DCompanion: Something to be drawn before the plot itself
preProcess(ResultProducer) - Method in class weka.experiment.AveragingResultProducer: Prepare for the results to be received.
preProcess() - Method in class weka.experiment.AveragingResultProducer: Prepare to generate results.
preProcess() - Method in class weka.experiment.CrossValidationResultProducer: Prepare to generate results.
preProcess(ResultProducer) - Method in class weka.experiment.CSVResultListener: Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultListener: Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer: Prepare for the results to be received.
preProcess() - Method in class weka.experiment.DatabaseResultProducer: Prepare to generate results.
preProcess() - Method in class weka.experiment.ExplicitTestsetResultProducer: Prepare to generate results.
preProcess(ResultProducer) - Method in class weka.experiment.InstancesResultListener: Prepare for the results to be received.
preProcess(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer: Prepare for the results to be received.
preProcess() - Method in class weka.experiment.LearningRateResultProducer: Prepare to generate results.
preProcess() - Method in class weka.experiment.RandomSplitResultProducer: Prepare to generate results.
preProcess(ResultProducer) - Method in interface weka.experiment.ResultListener: Prepare for the results to be received.
preProcess() - Method in interface weka.experiment.ResultProducer: Prepare to generate results.
PreprocessDefaults() - Constructor for class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
preprocessingTipText() - Method in class weka.filters.unsupervised.attribute.KernelFilter: Returns the tip text for this property
PreprocessPanel - Class in weka.gui.explorer: This panel controls simple preprocessing of instances.
PreprocessPanel() - Constructor for class weka.gui.explorer.PreprocessPanel: Creates the instances panel with no initial instances.
PreprocessPanel.PreprocessDefaults - Class in weka.gui.explorer
preserveInstancesOrderTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
preserveOrderInPercentageSplitEvaluationTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
Primitives - Class in weka.core.expressionlanguage.common: A class providing AST (abstract syntax tree) nodes to support primitive types.
Primitives() - Constructor for class weka.core.expressionlanguage.common.Primitives
Primitives.BooleanConstant - Class in weka.core.expressionlanguage.common: An AST node representing a boolean constant
Primitives.BooleanExpression - Interface in weka.core.expressionlanguage.common: An AST node for an expression of boolean type
Primitives.BooleanVariable - Class in weka.core.expressionlanguage.common: An AST node representing a boolean variable
Primitives.DoubleConstant - Class in weka.core.expressionlanguage.common: An AST node representing a double constant
Primitives.DoubleExpression - Interface in weka.core.expressionlanguage.common: An AST node for an expression of double type
Primitives.DoubleVariable - Class in weka.core.expressionlanguage.common: An AST node representing a double variable
Primitives.StringConstant - Class in weka.core.expressionlanguage.common: An AST node representing a string constant
Primitives.StringExpression - Interface in weka.core.expressionlanguage.common: An AST node for an expression of String type
Primitives.StringVariable - Class in weka.core.expressionlanguage.common: An AST node representing a string variable
PrincipalComponents - Class in weka.attributeSelection: Performs a principal components analysis and transformation of the data.
PrincipalComponents() - Constructor for class weka.attributeSelection.PrincipalComponents
PrincipalComponents - Class in weka.filters.unsupervised.attribute: Performs a principal components analysis and transformation of the data.
Dimensionality reduction is accomplished by choosing enough eigenvectors to account for some percentage of the variance in the original data -- default 0.95 (95%).
Based on code of the attribute selection scheme 'PrincipalComponents' by Mark Hall and Gabi Schmidberger.
PrincipalComponents() - Constructor for class weka.filters.unsupervised.attribute.PrincipalComponents
print() - Method in class weka.classifiers.bayes.net.ADNode: print is used for debugging only and shows the ADTree in ASCII graphics
print(String) - Method in class weka.classifiers.bayes.net.VaryNode: print is used for debugging only, called from ADNode
print(Classifier, ConverterUtils.DataSource) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the header, classifications and footer to the buffer.
print(Classifier, Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the header, classifications and footer to the buffer.
print(int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given int to the streams.
print(boolean) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given boolean to the streams.
print(String) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given string to the streams.
print(Object) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given object to the streams.
print(int, int) - Method in class weka.core.matrix.Matrix: Print the matrix to stdout.
print(PrintWriter, int, int) - Method in class weka.core.matrix.Matrix: Print the matrix to the output stream.
print(NumberFormat, int) - Method in class weka.core.matrix.Matrix: Print the matrix to stdout.
print(PrintWriter, NumberFormat, int) - Method in class weka.core.matrix.Matrix: Print the matrix to the output stream.
print(int) - Method in class weka.core.Tee: prints the given int to the streams.
print(long) - Method in class weka.core.Tee: prints the given long to the streams.
print(float) - Method in class weka.core.Tee: prints the given float to the streams.
print(double) - Method in class weka.core.Tee: prints the given double to the streams.
print(boolean) - Method in class weka.core.Tee: prints the given boolean to the streams.
print(char) - Method in class weka.core.Tee: prints the given char to the streams.
print(char[]) - Method in class weka.core.Tee: prints the given char array to the streams.
print(String) - Method in class weka.core.Tee: prints the given string to the streams.
print(Object) - Method in class weka.core.Tee: prints the given object to the streams.
print() - Method in class weka.core.xml.XMLDocument: prints the current DOM document to standard out.
print(Graphics, PageFormat, int) - Method in class weka.gui.DocumentPrinting: Prints the page.
print(JTextPane) - Method in class weka.gui.DocumentPrinting: Prints the document in the JTextPane.
print_hash_code() - Method in class weka.classifiers.rules.DecisionTableHashKey: Prints the hash code
PrintableComponent - Class in weka.gui.visualize: This class extends the component which is handed over in the constructor by a print dialog.
PrintableComponent(JComponent) - Constructor for class weka.gui.visualize.PrintableComponent: initializes the panel.
PrintableHandler - Interface in weka.gui.visualize: This interface is for all JComponent classes that provide the ability to print itself to a file.
PrintablePanel - Class in weka.gui.visualize: This Panel enables the user to print the panel to various file formats.
PrintablePanel() - Constructor for class weka.gui.visualize.PrintablePanel: initializes the panel
printAllModels() - Method in class weka.classifiers.trees.m5.RuleNode: Print all the linear models at the learf (debugging purposes)
printCanopyAssignments(Instances, List<long[]>) - Static method in class weka.clusterers.Canopy: Print the supplied instances and their canopies
printClassification(Classifier, Instance, int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the classification to the buffer.
printClassification(double[], Instance, int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the classification to the buffer.
printClassifications(Classifier, ConverterUtils.DataSource) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the classifications to the buffer.
printClassifications(Classifier, Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the classifications to the buffer.
printClassifiersTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
printColNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
printDialog() - Method in class weka.gui.DocumentPrinting: Shows the print dialog.
printElements() - Method in class weka.classifiers.functions.supportVector.SMOset: Prints all the current elements in the set.
printf(String, Object...) - Method in class weka.core.Tee: A convenience method to write a formatted string to this output stream using the specified format string and arguments.
printf(Locale, String, Object...) - Method in class weka.core.Tee: A convenience method to write a formatted string to this output stream using the specified format string and arguments.
printFeatures() - Method in class weka.classifiers.rules.DecisionTable: Returns a string description of the features selected
printFooter() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the footer to the buffer.
printHeader() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Prints the header to the buffer.
printInsts(int, int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: For printing indices in some given portion of the master index array.
printLeafModels() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Print the models at the leaves
printLeafModels() - Method in class weka.classifiers.trees.m5.RuleNode: print all leaf models
printLeafModelsTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
printList(MiddleOutConstructor.MyIdxList) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: For printing indices in a given point list.
println() - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints a new line to the streams.
println(int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given int to the streams.
println(boolean) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given boolean to the streams.
println(String) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given string to the streams.
println(Object) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: prints the given object to the streams (for Throwables we print the stack trace).
println() - Method in class weka.core.Tee: prints a new line to the streams.
println(int) - Method in class weka.core.Tee: prints the given int to the streams.
println(long) - Method in class weka.core.Tee: prints the given long to the streams.
println(float) - Method in class weka.core.Tee: prints the given float to the streams.
println(double) - Method in class weka.core.Tee: prints the given double to the streams.
println(boolean) - Method in class weka.core.Tee: prints the given boolean to the streams.
println(char) - Method in class weka.core.Tee: prints the given char to the streams.
println(char[]) - Method in class weka.core.Tee: prints the given char array to the streams.
println(String) - Method in class weka.core.Tee: prints the given string to the streams.
println(Object) - Method in class weka.core.Tee: prints the given object to the streams (for Throwables we print the stack trace).
printNewickTipText() - Method in class weka.clusterers.HierarchicalClusterer
printNodeLinearModel() - Method in class weka.classifiers.trees.m5.RuleNode: print the linear model at this node
printRowNamesTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
printSingleAssignment(long[]) - Static method in class weka.clusterers.Canopy
printStackTrace() - Method in class weka.core.Debug.Random: prints the current stacktrace
priorEntropy() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean base-2 log loss wrt the null model.
priorEntropy() - Method in class weka.classifiers.Evaluation: Calculate the entropy of the prior distribution.
prnts - Variable in class weka.gui.graphvisualizer.GraphNode: The indices of parent nodes
prob(int) - Method in class weka.classifiers.trees.j48.Distribution: Returns relative frequency of class over all bags.
prob(int, int) - Method in class weka.classifiers.trees.j48.Distribution: Returns relative frequency of class for given bag.
PROB_COST_FUNC_NAME - Static variable in class weka.classifiers.evaluation.CostCurve: attribute name: Probability Cost Function
probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Return the probability of an attribute value conditioned on a class value
probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
probabilityOfAttValConditionedOnClass(double, String) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
probabilityTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
probRound(double, Random) - Static method in class weka.core.Utils: Rounds a double to the next nearest integer value in a probabilistic fashion (e.g.
probs - Variable in class weka.gui.graphvisualizer.GraphNode: probability table for each outcome given outcomes of parents, if any
probToLogOdds(double) - Static method in class weka.core.Utils: Returns the log-odds for a given probabilitiy.
process(boolean[][], BayesNet) - Method in class weka.classifiers.bayes.net.MarginCalculator
process(Instances) - Method in class weka.core.CheckScheme.PostProcessor: Provides a hook for derived classes to further modify the data.
process(Instances, double[][], Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances
process(Instance, Classifier, Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Process a classifier's prediction for an instance and update a set of plotting instances and additional plotting info.
process(Data) - Method in class weka.knowledgeflow.steps.PairedDataHelper: Initiate routing and processing for a particular data object
process() - Method in class weka.knowledgeflow.StepTask: The actual work gets done here.
processChangedLines(int, int) - Method in class weka.gui.scripting.SyntaxDocument: Determine how many lines have been changed, then apply highlighting to each line.
processColour(String, Color) - Static method in class weka.gui.visualize.VisualizeUtils: Parses a string containing either a named colour or r,g,b values.
processFile(String) - Method in class weka.classifiers.bayes.net.BIFReader: processFile reads a BIFXML file and initializes a Bayes Net
processFilename(String) - Method in class weka.gui.Loader: returns the processed filename, i.e.
processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.CostBenefitAnalysis: Process a list of events that have been collected earlier.
processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.DataVisualizer: Process a list of events that have been collected earlier.
processHeadlessEvents(List<EventObject>) - Method in interface weka.gui.beans.HeadlessEventCollector: Process a list of events that have been collected earlier.
processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.ModelPerformanceChart: Process a list of events that have been collected earlier.
processHeadlessEvents(List<EventObject>) - Method in class weka.gui.beans.TextViewer: Process a list of events that have been collected earlier.
processIncoming(Data) - Method in class weka.knowledgeflow.steps.AlterRelationName: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Appender: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ASEvaluator: Process an incoming Data object
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Associator: Processes incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.BaseStep: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in interface weka.knowledgeflow.steps.BaseStepExtender: Process an incoming data payload (if the step accepts incoming connections).
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Block: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.BoundaryPlotter
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ClassAssigner: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Classifier
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ClassValuePicker: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Clusterer: Process an incoming data object
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ClustererPerformanceEvaluator: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.CostBenefitAnalysis: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.DataVisualizer
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Process an incoming Data object
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Filter: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.FlowByExpression: Main processing routine
processIncoming(Data) - Method in class weka.knowledgeflow.steps.GetDataFromResult
processIncoming(Data) - Method in class weka.knowledgeflow.steps.GraphViewer: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ImageSaver: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ImageViewer: Process incoming image data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.InstanceStreamToBatchMaker: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Job
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Join: Process some incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.PredictionAppender: Process incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Saver: Processes incoming data
processIncoming(Data) - Method in class weka.knowledgeflow.steps.SendToPerspective
processIncoming(Data) - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.SetVariables
processIncoming(Data) - Method in class weka.knowledgeflow.steps.Sorter: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in interface weka.knowledgeflow.steps.Step: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
processIncoming(Data) - Method in class weka.knowledgeflow.steps.StripChart: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.SubstringLabeler: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.SubstringReplacer: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.TestSetMaker: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.TextSaver: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.TextViewer: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.TrainingSetMaker: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Process an incoming data payload (if the step accepts incoming connections)
processIncoming(Data) - Method in class weka.knowledgeflow.steps.WriteDataToResult
processIncoming(Data) - Method in class weka.knowledgeflow.steps.WriteWekaLog: Process an incoming piece of data
PROCESSING - Static variable in class weka.experiment.TaskStatusInfo
processing() - Method in interface weka.knowledgeflow.StepManager: Step implementations processing batch data should call this to indicate that they have started some processing.
processing() - Method in class weka.knowledgeflow.StepManagerImpl: Started processing.
processInstance(Instance) - Method in class weka.core.DictionaryBuilder: Process an instance by tokenizing string attributes and updating the dictionary.
processKeyString(String) - Static method in class weka.experiment.DatabaseUtils: processes the string in such a way that it can be stored in the database, i.e., it changes backslashes into slashes and doubles single quotes.
processPrimary(Integer, Integer, Data, PairedDataHelper<Classifier>) - Method in class weka.knowledgeflow.steps.Classifier: Process a training split (primary data handled by the PairedDataHelper)
processPrimary(Integer, Integer, Data, PairedDataHelper<Clusterer>) - Method in class weka.knowledgeflow.steps.Clusterer: Process a training split (primary data handled by the PairedDataHelper)
processPrimary(Integer, Integer, Data, PairedDataHelper<P>) - Method in interface weka.knowledgeflow.steps.PairedDataHelper.PairedProcessor
processSecondary(Integer, Integer, Data, PairedDataHelper<Classifier>) - Method in class weka.knowledgeflow.steps.Classifier: Process a test split/fold (secondary data handled by PairedDataHelper)
processSecondary(Integer, Integer, Data, PairedDataHelper<Clusterer>) - Method in class weka.knowledgeflow.steps.Clusterer: Process a test split/fold (secondary data handled by PairedDataHelper)
processSecondary(Integer, Integer, Data, PairedDataHelper<P>) - Method in interface weka.knowledgeflow.steps.PairedDataHelper.PairedProcessor
processString(String) - Method in class weka.classifiers.bayes.net.BIFReader
PRODUCT_RULE - Static variable in class weka.classifiers.meta.Vote: combination rule: Product of Probabilities (only nominal classes)
production_table() - Method in class weka.core.expressionlanguage.parser.Parser: Access to production table.
production_table() - Method in class weka.core.json.Parser: Access to production table.
ProgrammaticProperty - Annotation Type in weka.gui: Method annotation that can be used with bean properties that are to be considered as programmatic only (i.e.
PROPERTIES - Static variable in class weka.knowledgeflow.JSONFlowUtils
PROPERTIES_DIR - Static variable in class weka.core.WekaPackageManager: The default properties directory
PROPERTIES_FILE - Static variable in class weka.core.Capabilities: the properties file for managing the tests
PROPERTIES_FILE - Static variable in class weka.core.logging.Logger: the properties file.
PROPERTIES_FILE - Static variable in class weka.gui.scripting.GroovyPanel: the Groovy setup.
PROPERTIES_FILE - Static variable in class weka.gui.scripting.JythonPanel: the Groovy setup.
PROPERTIES_FILE - Static variable in class weka.gui.treevisualizer.TreeVisualizer: the props file.
PropertiesHandler() - Constructor for class weka.gui.WekaFileChooser.PropertiesHandler
property - Variable in class weka.experiment.PropertyNode: Other info about the property
PROPERTY_FILE - Static variable in class weka.core.Copyright: the copyright file
PROPERTY_FILE - Static variable in class weka.experiment.DatabaseUtils: The name of the properties file.
PROPERTY_FILE - Static variable in class weka.gui.experiment.ExperimenterDefaults: The name of the properties file.
PROPERTY_FILE - Static variable in class weka.gui.explorer.ExplorerDefaults: The name of the properties file.
PROPERTY_FILE - Static variable in class weka.gui.LookAndFeel: The name of the properties file
propertyChange(PropertyChangeEvent) - Method in class weka.gui.beans.KnowledgeFlowApp: Accept property change events
propertyChange(PropertyChangeEvent) - Method in class weka.gui.PropertySheetPanel: Updates the property sheet panel with a changed property and also passed the event along.
propertyChange(PropertyChangeEvent) - Method in class weka.gui.SettingsEditor.SingleSettingsEditor
PropertyDialog - Class in weka.gui: Support for PropertyEditors with custom editors: puts the editor into a separate frame.
PropertyDialog(PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog: Deprecated.
instead of this constructor, one should use the constructors with an explicit owner (either derived from java.awt.Dialog or from java.awt.Frame) or, if none available, using (Frame) null as owner.
PropertyDialog(Dialog, PropertyEditor) - Constructor for class weka.gui.PropertyDialog: Creates the (screen-centered) editor dialog.
PropertyDialog(Dialog, PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog: Creates the editor dialog at the given position.
PropertyDialog(Frame, PropertyEditor) - Constructor for class weka.gui.PropertyDialog: Creates the (screen-centered) editor dialog.
PropertyDialog(Frame, PropertyEditor, int, int) - Constructor for class weka.gui.PropertyDialog: Creates the editor dialog at the given position.
PropertyHandler - Class in weka.core.xml: This class stores information about properties to ignore or properties that are allowed for a certain class.
PropertyHandler() - Constructor for class weka.core.xml.PropertyHandler: initializes the handling
PropertyNode - Class in weka.experiment: Stores information on a property of an object: the class of the object with the property; the property descriptor, and the current value.
PropertyNode(Object) - Constructor for class weka.experiment.PropertyNode: Creates a mostly empty property.
PropertyNode(Object, PropertyDescriptor, Class<?>) - Constructor for class weka.experiment.PropertyNode: Creates a fully specified property node.
PropertyPanel - Class in weka.gui: Support for drawing a property value in a component.
PropertyPanel(PropertyEditor) - Constructor for class weka.gui.PropertyPanel: Create the panel with the supplied property editor.
PropertyPanel(PropertyEditor, boolean) - Constructor for class weka.gui.PropertyPanel: Create the panel with the supplied property editor, optionally ignoring any custom panel the editor can provide.
PropertyPath - Class in weka.core: A helper class for accessing properties in nested objects, e.g., accessing the "getRidge" method of a LinearRegression classifier part of MultipleClassifierCombiner, e.g., Vote.
PropertyPath() - Constructor for class weka.core.PropertyPath
PropertyPath.Path - Class in weka.core: Contains a (property) path structure
PropertyPath.PathElement - Class in weka.core: Represents a single element of a property path
PropertySelectorDialog - Class in weka.gui: Allows the user to select any (supported) property of an object, including properties that any of it's property values may have.
PropertySelectorDialog(Frame, Object) - Constructor for class weka.gui.PropertySelectorDialog: Create the property selection dialog.
PropertySheetPanel - Class in weka.gui: Displays a property sheet where (supported) properties of the target object may be edited.
PropertySheetPanel() - Constructor for class weka.gui.PropertySheetPanel: Creates the property sheet panel with an about panel.
PropertySheetPanel(boolean) - Constructor for class weka.gui.PropertySheetPanel: Creates the property sheet panel
ProtectedProperties - Class in weka.core: Simple class that extends the Properties class so that the properties are unable to be modified.
ProtectedProperties(Properties) - Constructor for class weka.core.ProtectedProperties: Creates a set of protected properties from a set of normal ones.
prune(Instances, boolean) - Method in class weka.classifiers.rules.JRip.RipperRule: Prune all the possible final sequences of the rule using the pruning data.
prune() - Method in class weka.classifiers.trees.j48.C45PruneableClassifierTree: Prunes a tree using C4.5's pruning procedure.
prune() - Method in class weka.classifiers.trees.j48.PruneableClassifierTree: Prunes a tree.
prune(double) - Method in class weka.classifiers.trees.lmt.LMTNode: Prunes a logistic model tree using the CART pruning scheme, given a cost-complexity parameter alpha.
prune(double[], double[], Instances) - Method in class weka.classifiers.trees.lmt.LMTNode: Method for performing one fold in the cross-validation of the cost-complexity parameter.
prune() - Method in class weka.classifiers.trees.m5.RuleNode: Recursively prune the tree
PruneableClassifierTree - Class in weka.classifiers.trees.j48: Class for handling a tree structure that can be pruned using a pruning set.
PruneableClassifierTree(ModelSelection, boolean, int, boolean, int) - Constructor for class weka.classifiers.trees.j48.PruneableClassifierTree: Constructor for pruneable tree structure.
PruneableDecList - Class in weka.classifiers.rules.part: Class for handling a partial tree structure that can be pruned using a pruning set.
PruneableDecList(ModelSelection, int) - Constructor for class weka.classifiers.rules.part.PruneableDecList: Constructor for pruneable partial tree structure.
pruneItemSets(ArrayList<Object>, Hashtable<ItemSet, Integer>) - Static method in class weka.associations.ItemSet: Prunes a set of (k)-item sets using the given (k-1)-item sets.
pruneItemSets(ArrayList<Object>, Hashtable<ItemSet, Integer>) - Static method in class weka.associations.LabeledItemSet: Prunes a set of (k)-item sets using the given (k-1)-item sets.
pruneRules(List<AssociationRule>, ArrayList<Item>, boolean) - Static method in class weka.associations.FPGrowth
pruneRules(ArrayList<Object>[], double) - Static method in class weka.associations.ItemSet: Prunes a set of rules.
pruneToK(Instances, double[], int) - Method in class weka.classifiers.lazy.IBk: Prunes the list to contain the k nearest neighbors.
PRUNING_LAMBDA - Static variable in class weka.classifiers.functions.supportVector.StringKernel: Pruning method: Lambda See [2] for details.
PRUNING_NONE - Static variable in class weka.classifiers.functions.supportVector.StringKernel: Pruning method: No Pruning
pruningMethodTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
PSI - Static variable in class weka.core.matrix.Maths: The constant 1 / sqrt(2 pi)
Puk - Class in weka.classifiers.functions.supportVector: The Pearson VII function-based universal kernel.

For more information see:

B.
Puk() - Constructor for class weka.classifiers.functions.supportVector.Puk: default constructor - does nothing.
Puk(Instances, int, double, double) - Constructor for class weka.classifiers.functions.supportVector.Puk: Constructor.
PURE_INPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is a pure input unit.
PURE_OUTPUT - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is a pure output unit.
push(T) - Method in class weka.core.neighboursearch.covertrees.Stack: Pushes the given element to the stack.
push(Stack<T>, T) - Method in class weka.core.neighboursearch.covertrees.Stack: Pushes the given element onto the given stack.
push(Object) - Method in class weka.core.Queue: Appends an object to the back of the queue.
pushParameterDefs() - Method in class weka.core.pmml.DefineFunction
put(Object, Object) - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
putAll(Map<? extends Object, ? extends Object>) - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
putResultInTable(String, ResultProducer, Object[], Object[]) - Method in class weka.experiment.DatabaseUtils: Executes a database query to insert a result for the supplied key into the database.

Q

qr() - Method in class weka.core.matrix.Matrix: QR Decomposition
QRDecomposition - Class in weka.core.matrix: QR Decomposition.
QRDecomposition(Matrix) - Constructor for class weka.core.matrix.QRDecomposition: QR Decomposition, computed by Householder reflections.
Quantile - Class in weka.core.pmml.jaxbbindings: Java class for Quantile element declaration.
Quantile() - Constructor for class weka.core.pmml.jaxbbindings.Quantile
queryExecuted(QueryExecuteEvent) - Method in interface weka.gui.sql.event.QueryExecuteListener: This method gets called when a query has been executed.
queryExecuted(QueryExecuteEvent) - Method in class weka.gui.sql.ResultPanel: This method gets called when a query has been executed.
queryExecuted(QueryExecuteEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when a query has been executed.
QueryExecuteEvent - Class in weka.gui.sql.event: An event that is generated when a query is executed.
QueryExecuteEvent(Object, DbUtils, String, int, ResultSet, Exception) - Constructor for class weka.gui.sql.event.QueryExecuteEvent: constructs the event
QueryExecuteListener - Interface in weka.gui.sql.event: A listener for executing queries.
QueryPanel - Class in weka.gui.sql: Represents a panel for entering an SQL query.
QueryPanel(JFrame) - Constructor for class weka.gui.sql.QueryPanel: initializes the panel.
queryTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
queryTipText() - Method in class weka.experiment.InstanceQuery: Returns the tip text for this property
Queue - Class in weka.core: Class representing a FIFO queue.
Queue() - Constructor for class weka.core.Queue
quickSort(double[], double[], int, int) - Static method in class weka.core.neighboursearch.NearestNeighbourSearch: performs quicksort.
quote(String) - Static method in class weka.core.Utils: Quotes a string if it contains special characters.

R

R_MAX - Static variable in class weka.core.NormalizableDistance: Index in ranges for MAX.
R_MIN - Static variable in class weka.core.NormalizableDistance: Index in ranges for MIN.
R_WIDTH - Static variable in class weka.core.NormalizableDistance: Index in ranges for WIDTH.
RadialBasisKernelType - Class in weka.core.pmml.jaxbbindings: Java class for RadialBasisKernelType element declaration.
RadialBasisKernelType() - Constructor for class weka.core.pmml.jaxbbindings.RadialBasisKernelType
radixSortOfPositiveIntegers(int[]) - Static method in class weka.core.RandomSample: Sorts the given array of non-negative integers in ascending order using LSD radix sort.
Rainbow - Class in weka.core.stopwords: Stopwords list based on Rainbow:
http://www.cs.cmu.edu/~mccallum/bow/rainbow/
Valid options are:
Rainbow() - Constructor for class weka.core.stopwords.Rainbow
randEntropy - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the random entropy
RANDOM - Static variable in class weka.clusterers.SimpleKMeans
Random() - Constructor for class weka.core.Debug.Random: Creates a new random number generator.
Random(long) - Constructor for class weka.core.Debug.Random: Creates a new random number generator using a single long seed.
Random(boolean) - Constructor for class weka.core.Debug.Random: Creates a new random number generator.
Random(long, boolean) - Constructor for class weka.core.Debug.Random: Creates a new random number generator using a single long seed.
random(int) - Static method in class weka.core.matrix.DoubleVector: Returns a random vector of uniform distribution
random(int, int) - Static method in class weka.core.matrix.Matrix: Generate matrix with random elements
RANDOM - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: Constant set for choice of pattern.
RANDOM - Static variable in class weka.filters.supervised.attribute.ClassOrder: The class values are sorted in random order
RandomCommittee - Class in weka.classifiers.meta: Class for building an ensemble of randomizable base classifiers.
RandomCommittee() - Constructor for class weka.classifiers.meta.RandomCommittee: Constructor.
RandomForest - Class in weka.classifiers.trees: Class for constructing a forest of random trees.

For more information see:

Leo Breiman (2001).
RandomForest() - Constructor for class weka.classifiers.trees.RandomForest: Constructor that sets base classifier for bagging to RandomTre and default number of iterations to 100.
Randomizable - Interface in weka.core: Interface to something that has random behaviour that is able to be seeded with an integer.
RandomizableClassifier - Class in weka.classifiers: Abstract utility class for handling settings common to randomizable classifiers.
RandomizableClassifier() - Constructor for class weka.classifiers.RandomizableClassifier
RandomizableClusterer - Class in weka.clusterers: Abstract utility class for handling settings common to randomizable clusterers.
RandomizableClusterer() - Constructor for class weka.clusterers.RandomizableClusterer
RandomizableDensityBasedClusterer - Class in weka.clusterers: Abstract utility class for handling settings common to randomizable clusterers.
RandomizableDensityBasedClusterer() - Constructor for class weka.clusterers.RandomizableDensityBasedClusterer
RandomizableFilteredClassifier - Class in weka.classifiers.meta: Class for running an arbitrary classifier on data that has been passed through an arbitrary filter.
RandomizableFilteredClassifier() - Constructor for class weka.classifiers.meta.RandomizableFilteredClassifier: Default constructor.
RandomizableIteratedSingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
RandomizableIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer
RandomizableMultipleClassifiersCombiner - Class in weka.classifiers: Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from multiple classifiers based on a given random number seed.
RandomizableMultipleClassifiersCombiner() - Constructor for class weka.classifiers.RandomizableMultipleClassifiersCombiner
RandomizableParallelIteratedSingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble in parallel from a single base learner.
RandomizableParallelIteratedSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer
RandomizableParallelMultipleClassifiersCombiner - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that build an ensemble in parallel using multiple classifiers based on a given random number seed.
RandomizableParallelMultipleClassifiersCombiner() - Constructor for class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner
RandomizableSingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to randomizable meta classifiers that build an ensemble from a single base learner.
RandomizableSingleClassifierEnhancer() - Constructor for class weka.classifiers.RandomizableSingleClassifierEnhancer
RandomizableSingleClustererEnhancer - Class in weka.clusterers: Abstract utility class for handling settings common to randomizable clusterers.
RandomizableSingleClustererEnhancer() - Constructor for class weka.clusterers.RandomizableSingleClustererEnhancer
randomize(int[], Random) - Method in class weka.classifiers.BVDecomposeSegCVSub: Accepts an array of ints and randomises the values in the array, using the random seed.
randomize(Random) - Method in class weka.core.Instances: Shuffles the instances in the set so that they are ordered randomly.
Randomize - Class in weka.filters.unsupervised.instance: Randomly shuffles the order of instances passed through it.
Randomize() - Constructor for class weka.filters.unsupervised.instance.Randomize
RANDOMIZED - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: Constant set for input order (default)
randomizeDataTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
randomizeDataTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
RandomLiftGraph - Class in weka.core.pmml.jaxbbindings: Java class for RandomLiftGraph element declaration.
RandomLiftGraph() - Constructor for class weka.core.pmml.jaxbbindings.RandomLiftGraph
randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.global.K2
randomOrderTipText() - Method in class weka.classifiers.bayes.net.search.local.K2
RandomProjection - Class in weka.filters.unsupervised.attribute: Reduces the dimensionality of the data by projecting it onto a lower dimensional subspace using a random matrix with columns of unit length.
RandomProjection() - Constructor for class weka.filters.unsupervised.attribute.RandomProjection
RandomRBF - Class in weka.datagenerators.classifiers.classification: RandomRBF data is generated by first creating a random set of centers for each class.
RandomRBF() - Constructor for class weka.datagenerators.classifiers.classification.RandomRBF: initializes the generator with default values
RandomSample - Class in weka.core: Class holding static utility methods for drawing random samples.
RandomSample() - Constructor for class weka.core.RandomSample
randomSeedTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
randomSeedTipText() - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Returns the tip text for this property.
randomSeedTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
randomSeedTipText() - Method in class weka.filters.supervised.instance.SpreadSubsample: Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Randomize: Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.instance.Resample: Returns the tip text for this property
randomSeedTipText() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns the tip text for this property
RandomSplitResultProducer - Class in weka.experiment: Generates a single train/test split and calls the appropriate SplitEvaluator to generate some results.
RandomSplitResultProducer() - Constructor for class weka.experiment.RandomSplitResultProducer
RandomSubset - Class in weka.filters.unsupervised.attribute: Chooses a random subset of non-class attributes, either an absolute number or a percentage.
RandomSubset() - Constructor for class weka.filters.unsupervised.attribute.RandomSubset
RandomSubSpace - Class in weka.classifiers.meta: This method constructs a decision tree based classifier that maintains highest accuracy on training data and improves on generalization accuracy as it grows in complexity.
RandomSubSpace() - Constructor for class weka.classifiers.meta.RandomSubSpace: Constructor.
randomTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
RandomTree - Class in weka.classifiers.trees: Class for constructing a tree that considers K randomly chosen attributes at each node.
RandomTree() - Constructor for class weka.classifiers.trees.RandomTree
RandomVariates - Class in weka.core: Class implementing some simple random variates generator.
RandomVariates() - Constructor for class weka.core.RandomVariates: Simply the constructor of super class
RandomVariates(long) - Constructor for class weka.core.RandomVariates: Simply the constructor of super class
randomWidthFactorTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
Range - Class in weka.core: Class representing a range of cardinal numbers.
Range() - Constructor for class weka.core.Range: Default constructor.
Range(String) - Constructor for class weka.core.Range: Constructor to set initial range.
RangeEditor - Class in weka.gui: A PropertyEditor that can be used to edit Range objects (really, just appropriately formatted strings).
RangeEditor() - Constructor for class weka.gui.RangeEditor
rangesSet() - Method in class weka.core.NormalizableDistance: Check if ranges are set.
rangesTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns the tip text for this property.
rank() - Method in class weka.core.matrix.Matrix: Matrix rank
rank() - Method in class weka.core.matrix.SingularValueDecomposition: Effective numerical matrix rank
rankedAttributes() - Method in class weka.attributeSelection.AttributeSelection: get the final ranking of the attributes.
rankedAttributes() - Method in class weka.attributeSelection.GreedyStepwise: Produces a ranked list of attributes.
rankedAttributes() - Method in interface weka.attributeSelection.RankedOutputSearch: Returns a X by 2 list of attribute indexes and corresponding evaluations from best (highest) to worst.
rankedAttributes() - Method in class weka.attributeSelection.Ranker: Sorts the evaluated attribute list
RankedOutputSearch - Interface in weka.attributeSelection: Interface for search methods capable of producing a ranked list of attributes.
Ranker - Class in weka.attributeSelection: Ranker :

Ranks attributes by their individual evaluations.
Ranker() - Constructor for class weka.attributeSelection.Ranker: Constructor
rawOutputTipText() - Method in class weka.experiment.CrossValidationResultProducer: Returns the tip text for this property
rawOutputTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
rawOutputTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
RBFKernel - Class in weka.classifiers.functions.supportVector: The RBF kernel : K(x, y) = exp(-gamma*(x-y)^2)

Valid options are:
RBFKernel() - Constructor for class weka.classifiers.functions.supportVector.RBFKernel: default constructor - does nothing.
RBFKernel(Instances, int, double) - Constructor for class weka.classifiers.functions.supportVector.RBFKernel: Creates a new RBFKernel instance.
rchisq(int, double, Random) - Static method in class weka.core.matrix.Maths: Generates a sample of a Chi-square distribution.
RCURLY - Static variable in interface weka.core.json.sym
RDG1 - Class in weka.datagenerators.classifiers.classification: A data generator that produces data randomly by producing a decision list.
The decision list consists of rules.
Instances are generated randomly one by one.
RDG1() - Constructor for class weka.datagenerators.classifiers.classification.RDG1: initializes the generator with default values
read(String) - Static method in class weka.core.converters.ConverterUtils.DataSource: convencience method for loading a dataset in batch mode.
read(InputStream) - Static method in class weka.core.converters.ConverterUtils.DataSource: convencience method for loading a dataset in batch mode from a stream.
read(Loader) - Static method in class weka.core.converters.ConverterUtils.DataSource: convencience method for loading a dataset in batch mode.
read(Reader) - Static method in class weka.core.json.JSONNode: Reads the JSON object from the given reader.
read(BufferedReader) - Static method in class weka.core.matrix.Matrix: Read a matrix from a stream.
read(String) - Static method in class weka.core.SerializationHelper: deserializes the given file and returns the object from it.
read(InputStream) - Static method in class weka.core.SerializationHelper: deserializes from the given stream and returns the object from it.
read(String) - Method in class weka.core.Stopwords: Generates a new Stopwords object from the given file
read(File) - Method in class weka.core.Stopwords: Generates a new Stopwords object from the given file
read(BufferedReader) - Method in class weka.core.Stopwords: Generates a new Stopwords object from the reader.
read(String) - Static method in class weka.core.xml.KOML: reads the XML-serialized object from the given file
read(File) - Static method in class weka.core.xml.KOML: reads the XML-serialized object from the given file
read(InputStream) - Static method in class weka.core.xml.KOML: reads the XML-serialized object from a stream
read(String) - Method in class weka.core.xml.XMLDocument: parses the given XML string (can be XML or a filename) and returns a DOM Document.
read(File) - Method in class weka.core.xml.XMLDocument: parses the given file and returns a DOM document.
read(InputStream) - Method in class weka.core.xml.XMLDocument: parses the given stream and returns a DOM document.
read(Reader) - Method in class weka.core.xml.XMLDocument: parses the given reader and returns a DOM document.
read(String) - Method in class weka.core.xml.XMLSerialization: parses the given XML string (can be XML or a filename) and returns an Object generated from the representation
read(File) - Method in class weka.core.xml.XMLSerialization: parses the given file and returns a DOM document
read(InputStream) - Method in class weka.core.xml.XMLSerialization: parses the given stream and returns a DOM document
read(Reader) - Method in class weka.core.xml.XMLSerialization: parses the given reader and returns a DOM document
read() - Method in class weka.core.xml.XMLSerializationMethodHandler: returns the handler for read methods
read(String) - Static method in class weka.core.xml.XStream: reads the XML-serialized object from the given file
read(File) - Static method in class weka.core.xml.XStream: reads the XML-serialized object from the given file
read(InputStream) - Static method in class weka.core.xml.XStream: reads the XML-serialized object from the given input stream
read(Reader) - Static method in class weka.core.xml.XStream: reads the XML-serialized object from the given Reader
read(String) - Static method in class weka.experiment.Experiment: Loads an experiment from a file.
readAll(String) - Static method in class weka.core.SerializationHelper: deserializes the given file and returns the objects from it.
readAll(InputStream) - Static method in class weka.core.SerializationHelper: deserializes from the given stream and returns the object from it.
readBeanConnection(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the BeanConnection from the given DOM node.
readBeanInstance(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the BeanInstance from the given DOM node.
readBeanVisual(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the BeanVisual from the given DOM node.
readBIF(String) - Method in class weka.gui.graphvisualizer.GraphVisualizer: BIF reader
Reads a graph description in XMLBIF03 from a string
readBIF(InputStream) - Method in class weka.gui.graphvisualizer.GraphVisualizer: BIF reader
Reads a graph description in XMLBIF03 from an InputStrem
readBIFFromFile(String) - Method in class weka.classifiers.bayes.net.GUI: BIF reader
Reads a graph description in XMLBIF03 from an file with name sFileName
readBooleanFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readByteFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readCharFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readCollection(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Collection from the given DOM node.
readColor(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Color object from the given DOM node.
readColor(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Color from the given DOM node.
readColorUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the ColorUIResource from the given DOM node.
readCostMatrix(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Matrix from the given DOM node.
readCostMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Matrix (old) from the given DOM node.
readDefaultListModel(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the DefaultListModel from the given DOM node.
readDimension(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Dimension from the given DOM node.
readDOT(Reader) - Method in class weka.gui.graphvisualizer.GraphVisualizer: Dot reader
Reads a graph description in DOT format from a string
readDoubleFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
ReaderToTextPane - Class in weka.gui: A class that sends all lines from a reader to a JTextPane component.
ReaderToTextPane(Reader, JTextPane) - Constructor for class weka.gui.ReaderToTextPane: Sets up the thread.
ReaderToTextPane(Reader, JTextPane, Color) - Constructor for class weka.gui.ReaderToTextPane: Sets up the thread.
readFloatFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readFlow(File) - Method in interface weka.knowledgeflow.FlowLoader: Load a flow from the supplied file
readFlow(InputStream) - Method in interface weka.knowledgeflow.FlowLoader: Load a flow from the supplied input stream
readFlow(Reader) - Method in interface weka.knowledgeflow.FlowLoader: Load a flow from the supplied reader
readFlow(File) - Method in class weka.knowledgeflow.JSONFlowLoader: Read the flow from the supplied file
readFlow(InputStream) - Method in class weka.knowledgeflow.JSONFlowLoader: Read the flow from the supplied input stream
readFlow(Reader) - Method in class weka.knowledgeflow.JSONFlowLoader: Read the flow from the supplied reader
readFlow(File) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a flow from the supplied file
readFlow(File, boolean) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a flow from the supplied file
readFlow(InputStream) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a Flow from the supplied input stream
readFlow(InputStream, boolean) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a Flow from the supplied input stream
readFlow(Reader) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a flow from the supplied reader
readFlow(Reader, boolean) - Static method in class weka.knowledgeflow.JSONFlowUtils: Read a flow from the supplied reader
readFlow(File) - Method in class weka.knowledgeflow.LegacyFlowLoader: Deserialize a legacy flow from the supplied file
readFlow(InputStream) - Method in class weka.knowledgeflow.LegacyFlowLoader: Deserialize a legacy flow from the supplied input stream
readFlow(Reader) - Method in class weka.knowledgeflow.LegacyFlowLoader: Deserialize a legacy flow from the supplied reader
readFont(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Font from the given DOM node.
readFontUIResource(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the FontUIResource from the given DOM node.
readFromXML(Object, String, Element) - Method in class weka.core.xml.XMLSerialization: adds the specific node to the object via a set method
readFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the object from the given DOM node.
readInstance(Instances) - Method in class weka.core.converters.ArffLoader.ArffReader: Reads a single instance using the tokenizer and returns it.
readInstance(Instances, boolean) - Method in class weka.core.converters.ArffLoader.ArffReader: Reads a single instance using the tokenizer and returns it.
readInstance(Reader) - Method in class weka.core.Instances: Deprecated.
instead of using this method in conjunction with the readInstance(Reader) method, one should use the ArffLoader or DataSource class instead.
readIntFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readLoader(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Loader from the given DOM node.
readLongFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readMap(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Map from the given DOM node.
readMatrix(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Matrix from the given DOM node.
readMatrixOld(Element) - Method in class weka.core.xml.XMLBasicSerialization: builds the Matrix (old) from the given DOM node.
readMetaBean(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the MetaBean from the given DOM node.
readOldFormat(Reader) - Method in class weka.classifiers.CostMatrix: Loads a cost matrix in the old format from a reader.
readPoint(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Point from the given DOM node.
readProperties(String) - Static method in class weka.core.ResourceUtils: Reads properties that inherit from three locations.
readProperties(String, ClassLoader) - Static method in class weka.core.ResourceUtils: Reads properties that inherit from three locations.
readProperties(String) - Static method in class weka.core.Utils: Reads properties that inherit from three locations.
readProperties(String, ClassLoader) - Static method in class weka.core.Utils: Reads properties that inherit from three locations.
readPropertyNode(Element) - Method in class weka.experiment.xml.XMLExperiment: builds the PropertyNode from the given DOM node.
readSaver(Element) - Method in class weka.gui.beans.xml.XMLBeans: builds the Saver from the given DOM node.
readShortFromXML(Element) - Method in class weka.core.xml.XMLSerialization: builds the primitive from the given DOM node.
readyToVectorize() - Method in class weka.core.DictionaryBuilder: Returns true if this DictionaryBuilder is ready to vectorize incoming instances
realCount - Variable in class weka.core.AttributeStats: The number of real-like values (i.e.
REALSparseArray - Class in weka.core.pmml.jaxbbindings: Java class for REAL-SparseArray element declaration.
REALSparseArray() - Constructor for class weka.core.pmml.jaxbbindings.REALSparseArray
recall(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the recall with respect to a particular class.
recall(int) - Method in class weka.classifiers.Evaluation: Calculate the recall with respect to a particular class.
RECALL_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Recall
RECTANGLE - Static variable in class weka.gui.visualize.VisualizePanelEvent
redo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: redo the last edit action performed on the network.
reduce_table() - Method in class weka.core.expressionlanguage.parser.Parser: Access to reduce_goto table.
reduce_table() - Method in class weka.core.json.Parser: Access to reduce_goto table.
reducedErrorPruningTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
reducedErrorPruningTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
reduceDimensionality(Instances) - Method in class weka.attributeSelection.AttributeSelection: reduce the dimensionality of a set of instances to include only those attributes chosen by the last run of attribute selection.
reduceDimensionality(Instance) - Method in class weka.attributeSelection.AttributeSelection: reduce the dimensionality of a single instance to include only those attributes chosen by the last run of attribute selection.
reduceDL(double, boolean) - Method in class weka.classifiers.rules.RuleStats: Try to reduce the DL of the ruleset by testing removing the rules one by one in reverse order and update all the stats
reduceMatrix(double[][]) - Static method in class weka.core.ContingencyTables: Reduces a matrix by deleting all zero rows and columns.
reduceNumberOfDistanceCalcsViaCanopiesTipText() - Method in class weka.clusterers.SimpleKMeans: Returns the tip text for this property.
refresh() - Method in class weka.gui.arffviewer.ArffViewer: validates and repaints the frame
refresh() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: validates and repaints the frame
refreshCache(PrintStream...) - Static method in class weka.core.WekaPackageManager: Refresh the local copy of the package meta data
refreshFreqTipText() - Method in class weka.gui.beans.StripChart: GUI Tip text
refreshFreqTipText() - Method in class weka.knowledgeflow.steps.StripChart: GUI Tip text
refreshGOEProperties() - Static method in class weka.core.WekaPackageManager: Refresh the generic object editor properties via re-running of the dynamic class discovery process.
refreshWidthTipText() - Method in class weka.gui.beans.StripChart: GUI Tip text
refreshWidthTipText() - Method in class weka.knowledgeflow.steps.StripChart: GUI Tip text
regenerateGlobalOutputProperties() - Static method in class weka.gui.GenericPropertiesCreator: Regenerate the global output properties.
regexp(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: 'regexp' regexp operator (to check for string matching a given regular expression)
REGEXP - Static variable in interface weka.core.expressionlanguage.parser.sym
RegExpFromFile - Class in weka.core.stopwords: Uses the regular expressions stored in the file for determining whether a word is a stopword (ignored if pointing to a directory).
RegExpFromFile() - Constructor for class weka.core.stopwords.RegExpFromFile
register(Object, Class<?>, String) - Method in class weka.core.xml.XMLSerializationMethodHandler: adds read and write methods for the given class, i.e., read&;lt;name> and write<name> ("name" is prefixed by read and write)
registerEditor(String, String) - Static method in class weka.gui.GenericObjectEditor
registerEditors() - Static method in class weka.gui.GenericObjectEditor: registers all the editors in Weka.
RegOptimizer - Class in weka.classifiers.functions.supportVector: Base class implementation for learning algorithm of SMOreg Valid options are:
RegOptimizer() - Constructor for class weka.classifiers.functions.supportVector.RegOptimizer: the default constructor
regOptimizerTipText() - Method in class weka.classifiers.functions.SMOreg: Returns the tip text for this property
Regression - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML Regression model.
Regression(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.Regression: Constructs a new PMML Regression.
regression(Matrix, double) - Method in class weka.core.matrix.Matrix: Performs a (ridged) linear regression.
regression(Matrix, double[], double) - Method in class weka.core.matrix.Matrix: Performs a weighted (ridged) linear regression.
regression(Matrix, double) - Method in class weka.core.Matrix: Deprecated.

Performs a (ridged) linear regression.
regression(Matrix, double[], double) - Method in class weka.core.Matrix: Deprecated.

Performs a weighted (ridged) linear regression.
Regression - Class in weka.core.pmml.jaxbbindings: Java class for Regression element declaration.
Regression() - Constructor for class weka.core.pmml.jaxbbindings.Regression
RegressionAnalysis - Class in weka.classifiers.evaluation: Analyzes linear regression model by using the Student's t-test on each coefficient.
RegressionAnalysis() - Constructor for class weka.classifiers.evaluation.RegressionAnalysis
RegressionByDiscretization - Class in weka.classifiers.meta: A regression scheme that employs any classifier on a copy of the data that has the class attribute (equal-width) discretized.
RegressionByDiscretization() - Constructor for class weka.classifiers.meta.RegressionByDiscretization: Default constructor.
RegressionGenerator - Class in weka.datagenerators: Abstract class for data generators for regression classifiers.
RegressionGenerator() - Constructor for class weka.datagenerators.RegressionGenerator: initializes the generator with default values
RegressionModel - Class in weka.core.pmml.jaxbbindings: Java class for RegressionModel element declaration.
RegressionModel() - Constructor for class weka.core.pmml.jaxbbindings.RegressionModel
REGRESSIONNORMALIZATIONMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for REGRESSIONNORMALIZATIONMETHOD.
RegressionSplitEvaluator - Class in weka.experiment: A SplitEvaluator that produces results for a classification scheme on a numeric class attribute.
RegressionSplitEvaluator() - Constructor for class weka.experiment.RegressionSplitEvaluator: No args constructor.
RegressionTable - Class in weka.core.pmml.jaxbbindings: Java class for RegressionTable element declaration.
RegressionTable() - Constructor for class weka.core.pmml.jaxbbindings.RegressionTable
RegressionTable(String) - Constructor for class weka.core.pmml.jaxbbindings.RegressionTable
RegSMO - Class in weka.classifiers.functions.supportVector: Implementation of SMO for support vector regression as described in :

A.J.
RegSMO() - Constructor for class weka.classifiers.functions.supportVector.RegSMO: default constructor
RegSMOImproved - Class in weka.classifiers.functions.supportVector: Learn SVM for regression using SMO with Shevade, Keerthi, et al.
RegSMOImproved() - Constructor for class weka.classifiers.functions.supportVector.RegSMOImproved
reInitialize() - Static method in class weka.gui.beans.KnowledgeFlowApp
relation() - Method in class weka.core.Attribute: Returns the header info for a relation-valued attribute, null if the attribute is not relation-valued.
relation(int) - Method in class weka.core.Attribute: Returns a value of a relation-valued attribute.
RELATION - Static variable in class weka.core.json.JSONInstances: the relation name.
RELATION_NAME - Static variable in class weka.classifiers.evaluation.CostCurve: The name of the relation used in cost curve datasets
RELATION_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: The name of the relation used in threshold curve datasets
RELATIONAL - Static variable in class weka.core.Attribute: Constant set for relation-valued attributes.
RelationalAttributeInfo - Class in weka.core: Stores information for relational attributes.
RelationalAttributeInfo(Instances) - Constructor for class weka.core.RelationalAttributeInfo: Constructs the information object based on the given parameter.
RelationalLocator - Class in weka.core: This class locates and records the indices of relational attributes,
RelationalLocator(Instances) - Constructor for class weka.core.RelationalLocator: Initializes the RelationalLocator with the given data.
RelationalLocator(Instances, int, int) - Constructor for class weka.core.RelationalLocator: Initializes the RelationalLocator with the given data.
RelationalLocator(Instances, int[]) - Constructor for class weka.core.RelationalLocator: Initializes the RelationalLocator with the given data.
relationalValue(int) - Method in class weka.core.AbstractInstance: Returns the relational value of a relational attribute.
relationalValue(Attribute) - Method in class weka.core.AbstractInstance: Returns the relational value of a relational attribute.
relationalValue(int) - Method in interface weka.core.Instance: Returns the relational value of a relational attribute.
relationalValue(Attribute) - Method in interface weka.core.Instance: Returns the relational value of a relational attribute.
relationFindTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
relationForTableNameTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text fo this property.
relationName() - Method in class weka.core.Instances: Returns the relation's name.
relationNameTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
relationReplaceTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
relativeAbsoluteError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the relative absolute error.
relativeAbsoluteError() - Method in class weka.classifiers.Evaluation: Returns the relative absolute error.
relativeDL(int, double, boolean) - Method in class weka.classifiers.rules.RuleStats: The description length (DL) of the ruleset relative to if the rule in the given position is deleted, which is obtained by:
MDL if the rule exists - MDL if the rule does not exist
Note the minimal possible DL of the ruleset is calculated(i.e.
ReliefFAttributeEval - Class in weka.attributeSelection: ReliefFAttributeEval :

Evaluates the worth of an attribute by repeatedly sampling an instance and considering the value of the given attribute for the nearest instance of the same and different class.
ReliefFAttributeEval() - Constructor for class weka.attributeSelection.ReliefFAttributeEval: Constructor
RemoteBoundaryVisualizerSubTask - Class in weka.gui.boundaryvisualizer: Class that encapsulates a sub task for distributed boundary visualization.
RemoteBoundaryVisualizerSubTask() - Constructor for class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask
RemoteEngine - Class in weka.experiment: A general purpose server for executing Task objects sent via RMI.
RemoteEngine(String) - Constructor for class weka.experiment.RemoteEngine: Constructor
RemoteExperiment - Class in weka.experiment: Holds all the necessary configuration information for a distributed experiment.
RemoteExperiment() - Constructor for class weka.experiment.RemoteExperiment: Construct a new RemoteExperiment using an empty Experiment as base Experiment
RemoteExperiment(Experiment) - Constructor for class weka.experiment.RemoteExperiment: Construct a new RemoteExperiment using a base Experiment
RemoteExperimentEvent - Class in weka.experiment: Class encapsulating information on progress of a remote experiment
RemoteExperimentEvent(boolean, boolean, boolean, String) - Constructor for class weka.experiment.RemoteExperimentEvent: Constructor
RemoteExperimentListener - Interface in weka.experiment: Interface for classes that want to listen for updates on RemoteExperiment progress
remoteExperimentStatus(RemoteExperimentEvent) - Method in interface weka.experiment.RemoteExperimentListener: Called when progress has been made in a remote experiment
RemoteExperimentSubTask - Class in weka.experiment: Class to encapsulate an experiment as a task that can be executed on a remote host.
RemoteExperimentSubTask() - Constructor for class weka.experiment.RemoteExperimentSubTask
RemoteResult - Class in weka.gui.boundaryvisualizer: Class that encapsulates a result (and progress info) for part of a distributed boundary visualization.
RemoteResult(int, int) - Constructor for class weka.gui.boundaryvisualizer.RemoteResult: Creates a new RemoteResult instance.
remove(String) - Method in class weka.core.ClassCache: Removes the classname from the cache.
remove(int) - Method in class weka.core.Instances: Removes the instance at the given position.
remove(Object) - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
remove(String) - Method in class weka.core.Stopwords: removes the word from the stopword list
remove(PrintStream) - Method in class weka.core.Tee: removes the given PrintStream from the list.
remove(int) - Method in class weka.core.Tee: removes the given PrintStream from the list.
remove(Object) - Method in class weka.core.Trie: Removes a single instance of the specified element from this collection, if it is present.
remove() - Method in class weka.core.Trie.TrieIterator: ignored
remove(String) - Method in class weka.core.Trie.TrieNode: Removes a suffix from the trie.
remove(String) - Method in class weka.core.xml.MethodHandler: removes the method for the property specified by the display name from its internal list.
remove(Class<?>) - Method in class weka.core.xml.MethodHandler: removes the method for the specified class from its internal list.
Remove - Class in weka.filters.unsupervised.attribute: An filter that removes a range of attributes from the dataset.
Remove() - Constructor for class weka.filters.unsupervised.attribute.Remove: Constructor so that we can initialize the Range variable properly.
remove(Integer...) - Method in class weka.gui.beans.BeanConnection: Remove this connection
remove(int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Removes the element at the specified position in this list.
remove(int, int) - Method in class weka.gui.scripting.SyntaxDocument: Applies syntax highlighting after the document has been updated.
REMOVE_CHILDREN - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent
REMOVE_POINT_RADIUS - Static variable in class weka.gui.boundaryvisualizer.BoundaryPanel: The distance we can click away from a point in the GUI and still remove it.
removeActionListener(ActionListener) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Remove a listener
removeAll(Collection<?>) - Method in class weka.core.Trie: Removes all this collection's elements that are also contained in the specified collection
removeAllBeansFromContainer(JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance: Removes all beans from containing component
removeAllElements() - Method in class weka.core.FastVector: Deprecated.

Removes all components from this vector and sets its size to zero.
removeAllElements() - Method in class weka.core.Queue: Removes all objects from the queue m_Tail.m_Next.
removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralConnection: This function will remove all the inputs to this unit.
removeAllInputs() - Method in class weka.classifiers.functions.neural.NeuralNode: This function will remove all the inputs to this unit.
removeAllInstances() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Deletes all training instances from our dataset.
removeAllMissingColsTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
removeAllOutputs() - Method in class weka.classifiers.functions.neural.NeuralConnection: This function will remove all outputs to this unit.
removeAllowed(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: removes the given property (display name) for the specified class from the list of allowed properties.
removeAllPlots() - Method in class weka.gui.visualize.Plot2D: Clears all plots
removeAllPlots() - Method in class weka.gui.visualize.VisualizePanel: Removes all the plots.
removeBatchAssociationRulesListener(BatchAssociationRulesListener) - Method in class weka.gui.beans.Associator: Remove a batch association rules listener
removeBatchClassifierListener(BatchClassifierListener) - Method in class weka.gui.beans.Classifier: Remove a batch classifier listener
removeBatchClustererListener(BatchClustererListener) - Method in class weka.gui.beans.Clusterer: Remove a batch clusterer listener
removeBean(JComponent, Integer...) - Method in class weka.gui.beans.BeanInstance: Remove this bean from the list of beans and from the containing component
removeBeanInstances(JComponent, Integer) - Static method in class weka.gui.beans.BeanInstance: Remove the vector of bean instances from the supplied index in the list of collections.
RemoveByName - Class in weka.filters.unsupervised.attribute: Removes attributes based on a regular expression matched against their names.
RemoveByName() - Constructor for class weka.filters.unsupervised.attribute.RemoveByName
removeCancelListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to remove an action listener from the cancel button.
removeCapabilitiesFilter() - Method in class weka.gui.GenericObjectEditor: Removes the current Capabilities filter.
removeCapabilitiesFilterListener(Explorer.CapabilitiesFilterChangeListener) - Method in class weka.gui.explorer.Explorer: Removes the specified listener from the set of listeners if it is present.
removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffPanel: Removes a ChangeListener from the panel
removeChangeListener(ChangeListener) - Method in class weka.gui.arffviewer.ArffTable: Removes a ChangeListener from the panel
removeChartListener(ChartListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Remove a chart listener
removeChild(FlowByExpression.ExpressionNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode: Remove a child from this bracket node
removeChildFrame(Container) - Method in class weka.gui.GUIChooserApp: tries to remove the child frame, it returns true if it could do such.
removeChildFrame(Container) - Method in class weka.gui.Main: tries to remove the child frame, it returns true if it could do such.
removeClassColumnTipText() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns the tip text for this property
removeClassLoaderForPackage(String) - Method in class weka.core.WekaPackageClassLoaderManager: Removes the named package classloader from those managed by this class.
removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Associator: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Classifier: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Clusterer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
removeConfigurationListener(ConfigurationListener) - Method in interface weka.gui.beans.ConfigurationProducer: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
removeConfigurationListener(ConfigurationListener) - Method in class weka.gui.beans.Filter: We don't have to keep track of configuration listeners (see the documentation for ConfigurationListener/ConfigurationEvent).
removeConnectionList(Integer) - Static method in class weka.gui.beans.BeanConnection: Remove the list of connections at the supplied index
removeConnectionListener(ConnectionListener) - Method in class weka.gui.sql.ConnectionPanel: removes the given listener from the list of listeners.
removeConnectionListener(ConnectionListener) - Method in class weka.gui.sql.SqlViewer: removes the given listener from the list of listeners.
removeConnections(BeanInstance, Integer...) - Static method in class weka.gui.beans.BeanConnection: Remove all connections for a bean.
removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassAssigner
removeDataFormatListener(DataFormatListener) - Method in class weka.gui.beans.ClassValuePicker
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.AbstractDataSource: Remove a listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Appender: Remove a data source listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassAssigner
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.ClassValuePicker
removeDataSourceListener(DataSourceListener) - Method in interface weka.gui.beans.DataSource: Remove a data source listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.DataVisualizer: Remove a listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Filter: Remove a data source listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.FlowByExpression
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Join: Remove a data souce listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Loader: Remove a listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.PredictionAppender: Remove a datasource listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.Sorter: Remove a datasource listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringLabeler: Remove a datasource listener
removeDataSourceListener(DataSourceListener) - Method in class weka.gui.beans.SubstringReplacer: Remove a data source listener
RemoveDuplicates - Class in weka.filters.unsupervised.instance: Removes all duplicate instances from the first batch of data it receives.
RemoveDuplicates() - Constructor for class weka.filters.unsupervised.instance.RemoveDuplicates
removeElement(Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Removes the first (lowest-indexed) occurrence of the argument from this list.
removeElementAt(int) - Method in class weka.core.FastVector: Deprecated.

Deletes an element from this vector.
removeExecutionFinishedCallback(ExecutionFinishedCallback) - Method in interface weka.knowledgeflow.FlowExecutor: Remove a callback
removeExecutionFinishedCallback(ExecutionFinishedCallback) - Method in class weka.knowledgeflow.FlowRunner: Remove a callback
removeExplorerProps(String) - Static method in class weka.core.WekaPackageManager: Remove any ExplorerDefaults properties specified in the supplied package
removeFilterNameTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
RemoveFolds - Class in weka.filters.unsupervised.instance: This filter takes a dataset and outputs a specified fold for cross validation.
RemoveFolds() - Constructor for class weka.filters.unsupervised.instance.RemoveFolds
RemoveFrequentValues - Class in weka.filters.unsupervised.instance: Determines which values (frequent or infrequent ones) of an (nominal) attribute are retained and filters the instances accordingly.
RemoveFrequentValues() - Constructor for class weka.filters.unsupervised.instance.RemoveFrequentValues
removeFromDisabledList(List<String>) - Static method in class weka.core.PluginManager: Remove the supplied list of fully qualified class names to the disabled list
removeFromDisabledList(String) - Static method in class weka.core.PluginManager: Remove the supplied fully qualified class name from the list of disabled plugins
removeFromDisabledList(List<String>) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Remove the supplied list of fully qualified class names to the disabled list
removeFromDisabledList(String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Remove the supplied fully qualified class name from the list of disabled plugins
removeFromPluginBeanProps(File) - Static method in class weka.gui.beans.BeansProperties
removeFromPluginBeanProps(File) - Static method in class weka.gui.beans.KnowledgeFlowApp: Remove a plugin bean props file
removeGraphListener(GraphListener) - Method in class weka.gui.beans.Associator: Remove a graph listener
removeGraphListener(GraphListener) - Method in class weka.gui.beans.Classifier: Remove a graph listener
removeGraphListener(GraphListener) - Method in class weka.gui.beans.Clusterer: Remove a graph listener
removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.ConnectionPanel: removes the given listener from the list of listeners.
removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.QueryPanel: removes the given listener from the list of listeners.
removeHistoryChangedListener(HistoryChangedListener) - Method in class weka.gui.sql.SqlViewer: removes the given listener from the list of listeners.
removeIgnored(String) - Method in class weka.core.xml.PropertyHandler: removes the given display name from the ignore list.
removeIgnored(Class<?>, String) - Method in class weka.core.xml.PropertyHandler: removes the given display name from the ignore list of the class.
removeImageListener(ImageListener) - Method in class weka.gui.beans.DataVisualizer: Remove an image listener
removeImageListener(ImageListener) - Method in class weka.gui.beans.ModelPerformanceChart: Remove an image listener
removeIncomingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Remove an incoming connection to this step of the specified type
removeIncrementalClassifierListener(IncrementalClassifierListener) - Method in class weka.gui.beans.Classifier: Remove an incremental classifier listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.AbstractDataSource: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Appender: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.ClassAssigner
removeInstanceListener(InstanceListener) - Method in interface weka.gui.beans.DataSource: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Filter: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.FlowByExpression
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.InstanceStreamToBatchMaker
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Join: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Loader: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.PredictionAppender: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.Sorter: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringLabeler: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.SubstringReplacer: Remove an instance listener
removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceJoiner
removeInstanceListener(InstanceListener) - Method in class weka.gui.streams.InstanceLoader
removeInstanceListener(InstanceListener) - Method in interface weka.gui.streams.InstanceProducer
removeKeyword(String) - Method in class weka.gui.scripting.SyntaxDocument: Removes an association between a keyword with a particular formatting style.
removeLast() - Method in class weka.classifiers.rules.RuleStats: Remove the last rule in the ruleset as well as it's stats.
removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Method to remove a LayoutCompleteEventListener.
removeLayoutCompleteEventListener(LayoutCompleteEventListener) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method removes a LayoutCompleteEventListener from the LayoutEngine.
removeLinkAt(int) - Method in class weka.attributeSelection.BestFirst.LinkedList2: removes an element (Link) at a specific index from the list.
RemoveMisclassified - Class in weka.filters.unsupervised.instance: A filter that removes instances which are incorrectly classified.
RemoveMisclassified() - Constructor for class weka.filters.unsupervised.instance.RemoveMisclassified
removeNotify() - Method in class weka.gui.beans.FileEnvironmentField: Deprecated.
removeNotify() - Method in class weka.gui.FileEnvironmentField
removeNotify() - Method in class weka.gui.PropertyPanel: Cleans up when the panel is destroyed.
removeOkListener(ActionListener) - Method in class weka.gui.GenericObjectEditor.GOEPanel: This is used to remove an action listener from the ok button.
removeOldClassTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
removeOutgoingConnection(String, StepManagerImpl) - Method in class weka.knowledgeflow.StepManagerImpl: Remove an outgoing connection from this step of the specified type
RemovePercentage - Class in weka.filters.unsupervised.instance: A filter that removes a given percentage of a dataset.
RemovePercentage() - Constructor for class weka.filters.unsupervised.instance.RemovePercentage
removePlotNotificationListener(StripChart.PlotNotificationListener) - Method in class weka.knowledgeflow.steps.StripChart: Remove a plot notification listener
removePlugin(String, String) - Static method in class weka.core.PluginManager: Remove a plugin.
removePlugin(String, String) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Remove a plugin.
removePlugins(String, List<String>) - Static method in class weka.core.PluginManager: Remove plugins of a specific type.
removePlugins(String, List<String>) - Static method in class weka.gui.beans.PluginManager: Deprecated.

Remove plugins of a specific type.
removePreBuiltClassifier(Classifier) - Method in class weka.classifiers.meta.Vote: Remove a prebuilt classifier from the list to use in the ensemble
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.AssociatorCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.BeanVisual: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassAssignerCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.ClustererCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer: Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.DataVisualizer: Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.FilterCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.LoaderCustomizer: Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SaverCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.StripChartCustomizer: Remove a property change listener
removePropertyChangeListener(String, PropertyChangeListener) - Method in class weka.gui.beans.TextViewer: Remove a property change listener from this bean
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer: Remove a property change listener
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.ColorEditor
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.CostMatrixEditor: Removes an object from the list of those that wish to be informed when the cost matrix changes.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.EnvironmentField
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.AbstractSetupPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupModePanel: Removes a PropertyChangeListener who will be notified of value changes.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SetupPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.experiment.SimpleSetupPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.explorer.PreprocessPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericArrayEditor: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.GenericObjectEditor: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PasswordField
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.PropertySheetPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SetInstancesPanel: Removes a PropertyChangeListener.
removePropertyChangeListener(PropertyChangeListener) - Method in class weka.gui.SimpleDateFormatEditor: Removes an object from the list of those that wish to be informed when the date format changes.
removePropertyChangeListenersSubFlow(PropertyChangeListener) - Method in class weka.gui.beans.MetaBean
removeQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.QueryPanel: removes the given listener from the list of listeners.
removeQueryExecuteListener(QueryExecuteListener) - Method in class weka.gui.sql.SqlViewer: removes the given listener from the list of listeners.
RemoveRange - Class in weka.filters.unsupervised.instance: A filter that removes a given range of instances of a dataset.
RemoveRange() - Constructor for class weka.filters.unsupervised.instance.RemoveRange
removeRenderingListener(BoundaryPlotter.RenderingUpdateListener) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Remove the rendering update listener
removeResult(String) - Method in class weka.gui.ResultHistoryPanel: Removes one of the result buffers from the history.
removeResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.ResultPanel: removes the given listener from the list of listeners
removeResultChangedListener(ResultChangedListener) - Method in class weka.gui.sql.SqlViewer: removes the given listener from the list of listeners.
removeResults(int[]) - Method in class weka.gui.ResultHistoryPanel: Remove the entries at the specified indices in the list
removeResults(List<String>) - Method in class weka.gui.ResultHistoryPanel: Remove the specified entries from the list
removeScriptFinishedListener(ScriptExecutionListener) - Method in class weka.gui.scripting.Script: Removes the given listener from its internal list.
removeStep(StepManagerImpl) - Method in class weka.knowledgeflow.Flow: Remove the supplied Step from this flow
removeStepOutputListener(StepOutputListener, String) - Method in class weka.knowledgeflow.StepManagerImpl: De-register non-step third party from receiving data from the managed step
removeSubstring(String, String) - Static method in class weka.core.Utils: Removes all occurrences of a string from another string.
removeTab(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
removeTab(int) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Remove/close a tab
removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffSortedTableModel: removes a listener from the list that is notified each time a change to the data model occurs
removeTableModelListener(TableModelListener) - Method in class weka.gui.arffviewer.ArffTableModel: removes a listener from the list that is notified each time a change to the data model occurs
removeTableModelListener(TableModelListener) - Method in class weka.gui.sql.ResultSetTableModel: removes a listener from the list that is notified each time a change to the data model occurs.
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTestSetProducer: Remove a listener for test sets
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Remove a test set listener
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.ClassAssigner
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.Filter: Remove a test set listener
removeTestSetListener(TestSetListener) - Method in class weka.gui.beans.PredictionAppender: Remove a test set listener
removeTestSetListener(TestSetListener) - Method in interface weka.gui.beans.TestSetProducer: Remove a listener for test set events
removeTextListener(TextListener) - Method in class weka.gui.beans.Associator: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.Classifier: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.Clusterer: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Remove a text listener
removeTextListener(TextListener) - Method in class weka.gui.beans.TextViewer: Remove a text listener
removeTextNotificationListener(TextViewer.TextNotificationListener) - Method in class weka.knowledgeflow.steps.TextViewer: Remove the listener for textual results
removeThresholdDataListener(ThresholdDataListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Remove a Threshold data listener
removeTitleUpdatedListener(TitleUpdatedListener) - Method in class weka.gui.scripting.ScriptingPanel: Removes the listener from the internal list.
removeTrainingInstanceFromMouseLocation(int, int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Removes a single training instance from our dataset, if there is one that is close enough to the specified mouse location.
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.ClassAssigner
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.Filter: Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in class weka.gui.beans.PredictionAppender: Remove a training set listener
removeTrainingSetListener(TrainingSetListener) - Method in interface weka.gui.beans.TrainingSetProducer: Remove a training set listener
RemoveType - Class in weka.filters.unsupervised.attribute: Removes attributes of a given type.
RemoveType() - Constructor for class weka.filters.unsupervised.attribute.RemoveType
removeUnusedTipText() - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Returns the tip text for this property.
RemoveUseless - Class in weka.filters.unsupervised.attribute: This filter removes attributes that do not vary at all or that vary too much.
RemoveUseless() - Constructor for class weka.filters.unsupervised.attribute.RemoveUseless
removeVariable(String) - Method in class weka.core.Environment: Remove a named variable from the map.
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.AbstractDataSource: Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.CostBenefitAnalysis
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.DataVisualizer: Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.GraphViewer: Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.ModelPerformanceChart: Remove a vetoable change listener from this bean
removeVetoableChangeListener(String, VetoableChangeListener) - Method in class weka.gui.beans.TextViewer: Remove a vetoable change listener from this bean
removeVisualizableErrorListener(VisualizableErrorListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Remove a visualizable error listener
RemoveWithValues - Class in weka.filters.unsupervised.instance: Filters instances according to the value of an attribute.
RemoveWithValues() - Constructor for class weka.filters.unsupervised.instance.RemoveWithValues: Default constructor
renameAttribute(int, String) - Method in class weka.core.Instances: Renames an attribute.
renameAttribute(Attribute, String) - Method in class weka.core.Instances: Renames an attribute.
RenameAttribute - Class in weka.filters.unsupervised.attribute: This filter is used for renaming attributes.
Regular expressions can be used in the matching and replacing.
See Javadoc of java.util.regex.Pattern class for more information:
http://java.sun.com/javase/6/docs/api/java/util/regex/Pattern.html
Valid options are:
RenameAttribute() - Constructor for class weka.filters.unsupervised.attribute.RenameAttribute
renameAttribute() - Method in class weka.gui.arffviewer.ArffPanel: renames the current attribute
renameAttribute() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: renames the current selected Attribute
renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffSortedTableModel: renames the attribute at the given col index
renameAttributeAt(int, String) - Method in class weka.gui.arffviewer.ArffTableModel: renames the attribute at the given col index
renameAttributeValue(int, int, String) - Method in class weka.core.Instances: Renames the value of a nominal (or string) attribute value.
renameAttributeValue(Attribute, String, String) - Method in class weka.core.Instances: Renames the value of a nominal (or string) attribute value.
renameNodeValue(int, String, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: change the name of a value of a node
RenameNominalValues - Class in weka.filters.unsupervised.attribute: Renames the values of nominal attributes.
RenameNominalValues() - Constructor for class weka.filters.unsupervised.attribute.RenameNominalValues
RenameRelation - Class in weka.filters: A simple filter that allows the relation name of a set of instances to be altered in various ways.
RenameRelation() - Constructor for class weka.filters.RenameRelation
renameStep(StepManagerImpl, String) - Method in class weka.knowledgeflow.Flow: Rename the supplied step with the supplied name
renameStep(String, String) - Method in class weka.knowledgeflow.Flow: Rename a Step.
rendererName() - Method in interface weka.gui.beans.OffscreenChartRenderer: The name of this off screen renderer
rendererName() - Method in class weka.gui.beans.WekaOffscreenChartRenderer: The name of this off screen renderer
renderHistogram(int, int, List<Instances>, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer: Render histogram(s) (numeric attribute) or bar chart(s) (nominal attribute).
renderHistogram(int, int, List<Instances>, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer: Render histogram(s) (numeric attribute) or pie chart (nominal attribute).
renderingImageUpdate() - Method in class weka.gui.knowledgeflow.steps.BoundaryPlotterInteractiveView: Called when there is an update to rendering of the current image
renderingImageUpdate() - Method in interface weka.knowledgeflow.steps.BoundaryPlotter.RenderingUpdateListener: Called when a change (other than rendering a row) to the current plot has occurred.
renderXYLineChart(int, int, List<Instances>, String, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer: Render an XY line chart
renderXYLineChart(int, int, List<Instances>, String, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer: Render an XY line chart
renderXYScatterPlot(int, int, List<Instances>, String, String, List<String>) - Method in interface weka.gui.beans.OffscreenChartRenderer: Render an XY scatter plot
renderXYScatterPlot(int, int, List<Instances>, String, String, List<String>) - Method in class weka.gui.beans.WekaOffscreenChartRenderer: Render an XY scatter plot
Reorder - Class in weka.filters.unsupervised.attribute: A filter that generates output with a new order of the attributes.
Reorder() - Constructor for class weka.filters.unsupervised.attribute.Reorder
RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
RepeatedHillClimber - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm repeatedly uses hill climbing starting with a randomly generated network structure and return the best structure of the various runs.
RepeatedHillClimber() - Constructor for class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
replaceAllBy(Stack<T>) - Method in class weka.core.neighboursearch.covertrees.Stack: Replace all elements in the stack with the elements of another given stack.
replaceAllTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
replaceAttributeAt(Attribute, int) - Method in class weka.core.Instances: Replaces the attribute at the given position (0 to numAttributes()) with the given attribute and sets all its values to be missing.
replaceMissingValues(double[]) - Method in class weka.core.BinarySparseInstance: Does nothing, since we don't support missing values.
replaceMissingValues(double[]) - Method in class weka.core.DenseInstance: Replaces all missing values in the instance with the values contained in the given array.
replaceMissingValues(double[]) - Method in interface weka.core.Instance: Replaces all missing values in the instance with the values contained in the given array.
replaceMissingValues(double[]) - Method in class weka.core.SparseInstance: Replaces all missing values in the instance with the values contained in the given array.
ReplaceMissingValues - Class in weka.filters.unsupervised.attribute: Replaces all missing values for nominal and numeric attributes in a dataset with the modes and means from the training data.
ReplaceMissingValues() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingValues
replaceMissingValuesTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
replaceMissingWithMAX_VALUE(double[]) - Static method in class weka.core.Utils: Replaces all "missing values" in the given array of double values with MAX_VALUE.
ReplaceMissingWithUserConstant - Class in weka.filters.unsupervised.attribute: Replaces all missing values for nominal, string, numeric and date attributes in the dataset with user-supplied constant values.
ReplaceMissingWithUserConstant() - Constructor for class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
replaceStrings(String, String[], char[]) - Static method in class weka.core.Utils: Converts the specified strings in the given string to the specified characters.
replaceSubstring(String, String, String) - Static method in class weka.core.Utils: Replaces with a new string, all occurrences of a string from another string.
replaceTipText() - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Returns the tip text for this property.
ReplaceWithMissingValue - Class in weka.filters.unsupervised.attribute: A filter that can be used to introduce missing values in a dataset.
ReplaceWithMissingValue() - Constructor for class weka.filters.unsupervised.attribute.ReplaceWithMissingValue
replot() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Quickly replot the display using cached probability estimates
RepositoryIndexGenerator - Class in weka.core: Class for generating html index files and supporting text files for a Weka package meta data repository.
RepositoryIndexGenerator() - Constructor for class weka.core.RepositoryIndexGenerator
repoZipArchiveSize() - Static method in class weka.core.WekaPackageManager: Retrieves the size (in KB) of the repository zip archive stored on the server.
representCopiesUsingWeightsTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
REPTree - Class in weka.classifiers.trees: Fast decision tree learner.
REPTree() - Constructor for class weka.classifiers.trees.REPTree
requiresLog() - Method in class weka.gui.AbstractPerspective: Whether this perspective requires a graphical log to write to
requiresLog() - Method in class weka.gui.explorer.AssociationsPanel
requiresLog() - Method in class weka.gui.explorer.AttributeSelectionPanel
requiresLog() - Method in class weka.gui.explorer.ClassifierPanel
requiresLog() - Method in class weka.gui.explorer.ClustererPanel
requiresLog() - Method in class weka.gui.explorer.PreprocessPanel
requiresLog() - Method in interface weka.gui.Perspective: Whether this perspective requires a graphical log to write to
requiresLog() - Method in class weka.gui.SimpleCLIPanel
resample(Random) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement.
Resample - Class in weka.filters.supervised.instance: Produces a random subsample of a dataset using either sampling with replacement or without replacement.
The original dataset must fit entirely in memory.
Resample() - Constructor for class weka.filters.supervised.instance.Resample
Resample - Class in weka.filters.unsupervised.instance: Produces a random subsample of a dataset using either sampling with replacement or without replacement.
Resample() - Constructor for class weka.filters.unsupervised.instance.Resample
ResampleUtils - Class in weka.core: Helper class for resampling.
ResampleUtils() - Constructor for class weka.core.ResampleUtils
resampleWithWeightIfNecessary(Instances, Random) - Static method in class weka.core.ResampleUtils: Resamples the dataset using Instances.resampleWithWeights(Random) if there are any instance weights other than 1.0 set.
resampleWithWeights(Random) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean[]) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean[], boolean) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the current instance weights.
resampleWithWeights(Random, boolean[], boolean, double) - Method in class weka.core.Instances: Creates a new dataset from this dataset using random sampling with replacement according to current instance weights.
resampleWithWeights(Random, double[]) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, double[], boolean[]) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, double[], boolean[], boolean) - Method in class weka.core.Instances: Creates a new dataset of the same size as this dataset using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, double[], boolean[], boolean, double) - Method in class weka.core.Instances: Creates a new dataset from this dataset using random sampling with replacement according to the given weight vector.
resampleWithWeights(Random, boolean[]) - Method in class weka.estimators.UnivariateMixtureEstimator: Creates a new dataset of the same size using random sampling with replacement according to the given weight vector.
ReservoirSample - Class in weka.filters.unsupervised.instance: Produces a random subsample of a dataset using the reservoir sampling Algorithm "R" by Vitter.
ReservoirSample() - Constructor for class weka.filters.unsupervised.instance.ReservoirSample
reset() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Reset the classifier.
reset() - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to reset the unit for another run.
reset() - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to reset the value and error for this unit, ready for the next run.
reset() - Method in class weka.classifiers.functions.SGD: Reset the classifier.
reset() - Method in class weka.classifiers.functions.SGDText: Reset the classifier.
reset() - Method in class weka.core.converters.AbstractFileLoader: Resets the loader ready to read a new data set
reset() - Method in class weka.core.converters.AbstractLoader: Default implementation sets retrieval mode to NONE
reset() - Method in class weka.core.converters.ArffLoader: Resets the Loader ready to read a new data set or the same data set again.
reset() - Method in class weka.core.converters.C45Loader: Resets the Loader ready to read a new data set or the same data set again.
reset() - Method in class weka.core.converters.ConverterUtils.DataSource: resets the loader.
reset() - Method in class weka.core.converters.CSVLoader
reset() - Method in class weka.core.converters.DatabaseLoader: Resets the Loader ready to read a new data set using set options
reset() - Method in class weka.core.converters.JSONLoader: Resets the Loader ready to read a new data set.
reset() - Method in class weka.core.converters.LibSVMLoader: Resets the Loader ready to read a new data set.
reset() - Method in interface weka.core.converters.Loader: Resets the Loader object ready to begin loading.
reset() - Method in class weka.core.converters.MatlabLoader: Resets the Loader ready to read a new data set.
reset() - Method in class weka.core.converters.SerializedInstancesLoader: Resets the Loader ready to read a new data set
reset() - Method in class weka.core.converters.SVMLightLoader: Resets the Loader ready to read a new data set.
reset() - Method in class weka.core.converters.TextDirectoryLoader: Resets the loader ready to read a new data set
reset() - Method in class weka.core.converters.XRFFLoader: Resets the Loader ready to read a new data set
reset() - Method in class weka.core.DictionaryBuilder: Clear the dictionary(s)
reset() - Method in class weka.core.neighboursearch.PerformanceStats: Resets all internal fields/counters.
reset() - Method in class weka.core.neighboursearch.TreePerformanceStats: Resets all internal fields/counters.
reset() - Method in class weka.knowledgeflow.StepInjectorFlowRunner: Rest the runner
reset() - Method in class weka.knowledgeflow.steps.PairedDataHelper: Reset the helper.
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Sets distribution associated with model.
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Sets distribution associated with model.
resetDistribution(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Sets distribution associated with model.
resetFileFilters() - Method in class weka.gui.beans.FileEnvironmentField: Deprecated.

Resets the list of choosable file filters.
resetFileFilters() - Method in class weka.gui.FileEnvironmentField: Resets the list of choosable file filters.
resetOptions() - Method in class weka.associations.Apriori: Resets the options to the default values.
resetOptions() - Method in class weka.associations.FPGrowth: Reset all options to their default values.
resetOptions() - Method in class weka.core.converters.AbstractFileSaver: resets the options
resetOptions() - Method in class weka.core.converters.AbstractSaver: resets the options
resetOptions() - Method in class weka.core.converters.ArffSaver: Resets the Saver
resetOptions() - Method in class weka.core.converters.C45Saver: Resets the Saver
resetOptions() - Method in class weka.core.converters.CSVSaver: Resets the Saver.
resetOptions() - Method in class weka.core.converters.DatabaseLoader: Resets the Loader to the settings in either the default DatabaseUtils.props or any property file that the user has specified via setCustomPropsFile().
resetOptions() - Method in class weka.core.converters.DatabaseSaver: Resets the Saver ready to save a new data set.
resetOptions() - Method in class weka.core.converters.DictionarySaver
resetOptions() - Method in class weka.core.converters.JSONSaver: Resets the Saver.
resetOptions() - Method in class weka.core.converters.LibSVMSaver: Resets the Saver
resetOptions() - Method in class weka.core.converters.MatlabSaver: Resets the Saver.
resetOptions() - Method in class weka.core.converters.SerializedInstancesSaver: Resets the Saver.
resetOptions() - Method in class weka.core.converters.SVMLightSaver: Resets the Saver.
resetOptions() - Method in class weka.core.converters.XRFFSaver: Resets the Saver
resetStructure() - Method in class weka.core.converters.AbstractSaver: Resets the structure (header information of the instances)
resetStructure() - Method in class weka.core.converters.DatabaseLoader: Resets the structure of instances
resetTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
resetWriter() - Method in class weka.core.converters.AbstractFileSaver: Sets the writer to null.
resetWriter() - Method in class weka.core.converters.DictionarySaver
resetWriter() - Method in class weka.core.converters.SerializedInstancesSaver: Resets the writer, setting writer and objectstream to null.
ResidualModelSelection - Class in weka.classifiers.trees.lmt: Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals.
ResidualModelSelection(int) - Constructor for class weka.classifiers.trees.lmt.ResidualModelSelection: Constructor to create ResidualModelSelection object.
ResidualSplit - Class in weka.classifiers.trees.lmt: Helper class for logistic model trees (weka.classifiers.trees.lmt.LMT) to implement the splitting criterion based on residuals of the LogitBoost algorithm.
ResidualSplit(int) - Constructor for class weka.classifiers.trees.lmt.ResidualSplit: Creates a split object
RESOURCE_INTENSIVE_EXECUTOR_SERVICE_NUM_THREADS - Static variable in class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults: Default (0) means use as many threads as there are cpu processors
RESOURCE_INTENSIVE_EXECUTOR_SERVICE_NUM_THREADS_KEY - Static variable in class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults
ResourceUtils - Class in weka.core: Helper for resources.
ResourceUtils() - Constructor for class weka.core.ResourceUtils
restoreBeans(int, int) - Method in class weka.gui.beans.MetaBean
restoreData(Object) - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer
restoreData(Object) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set a map of images.
restoreData(Object) - Method in interface weka.knowledgeflow.steps.DataCollector: Set the data for this collector
restoreData(Object) - Method in class weka.knowledgeflow.steps.DataVisualizer
restoreData(Object) - Method in class weka.knowledgeflow.steps.ImageViewer: Restore data for this step.
restoreData(Object) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Restore the data (plots) for this step
restoreData(Object) - Method in class weka.knowledgeflow.steps.TextViewer: Restore/set the data in this step
restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to have the connection restore from the saved weights.
restoreWeights() - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to have the connection restore from the saved weights.
restoreWindows() - Method in class weka.gui.Main: restores all windows.
resultChanged(ResultChangedEvent) - Method in interface weka.gui.sql.event.ResultChangedListener: This method gets called when a query has been executed.
resultChanged(ResultChangedEvent) - Method in class weka.gui.sql.SqlViewer: This method gets called when a query has been executed.
resultChanged(ResultChangedEvent) - Method in class weka.gui.sql.SqlViewerDialog: This method gets called when a query has been executed.
ResultChangedEvent - Class in weka.gui.sql.event: An event that is generated when a different Result is activated in the ResultPanel.
ResultChangedEvent(Object, String, String, String, String) - Constructor for class weka.gui.sql.event.ResultChangedEvent: constructs the event
ResultChangedListener - Interface in weka.gui.sql.event: A listener that is notified if another Result is activated in the ResultPanel.
RESULTFEATURE - Enum in weka.core.pmml.jaxbbindings: Java class for RESULT-FEATURE.
ResultField - Class in weka.core.pmml.jaxbbindings: Java class for ResultField element declaration.
ResultField() - Constructor for class weka.core.pmml.jaxbbindings.ResultField
ResultHistoryPanel - Class in weka.gui: A component that accepts named stringbuffers and displays the name in a list box.
ResultHistoryPanel(JTextComponent) - Constructor for class weka.gui.ResultHistoryPanel: Create the result history object
ResultHistoryPanel.RDeleteListener - Interface in weka.gui: Interface for something to be notified when an entry in the list is deleted
ResultHistoryPanel.RKeyAdapter - Class in weka.gui: Extension of KeyAdapter that implements Serializable.
ResultHistoryPanel.RMouseAdapter - Class in weka.gui: Extension of MouseAdapter that implements Serializable.
ResultListener - Interface in weka.experiment: Interface for objects able to listen for results obtained by a ResultProducer
ResultMatrix - Class in weka.experiment: This matrix is a container for the datasets and classifier setups and their statistics.
ResultMatrix() - Constructor for class weka.experiment.ResultMatrix: initializes the matrix as 1x1 matrix.
ResultMatrix(int, int) - Constructor for class weka.experiment.ResultMatrix: initializes the matrix with the given dimensions.
ResultMatrix(ResultMatrix) - Constructor for class weka.experiment.ResultMatrix: initializes the matrix with the values from the given matrix.
ResultMatrixCSV - Class in weka.experiment: Generates the matrix in CSV ('comma-separated values') format.
ResultMatrixCSV() - Constructor for class weka.experiment.ResultMatrixCSV: initializes the matrix as 1x1 matrix.
ResultMatrixCSV(int, int) - Constructor for class weka.experiment.ResultMatrixCSV: initializes the matrix with the given dimensions.
ResultMatrixCSV(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixCSV: initializes the matrix with the values from the given matrix.
ResultMatrixGnuPlot - Class in weka.experiment: Generates output for a data and script file for GnuPlot.
ResultMatrixGnuPlot() - Constructor for class weka.experiment.ResultMatrixGnuPlot: initializes the matrix as 1x1 matrix.
ResultMatrixGnuPlot(int, int) - Constructor for class weka.experiment.ResultMatrixGnuPlot: initializes the matrix with the given dimensions.
ResultMatrixGnuPlot(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixGnuPlot: initializes the matrix with the values from the given matrix.
ResultMatrixHTML - Class in weka.experiment: Generates the matrix output as HTML.
ResultMatrixHTML() - Constructor for class weka.experiment.ResultMatrixHTML: initializes the matrix as 1x1 matrix.
ResultMatrixHTML(int, int) - Constructor for class weka.experiment.ResultMatrixHTML: initializes the matrix with the given dimensions.
ResultMatrixHTML(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixHTML: initializes the matrix with the values from the given matrix.
ResultMatrixLatex - Class in weka.experiment: Generates the matrix output in LaTeX-syntax.
ResultMatrixLatex() - Constructor for class weka.experiment.ResultMatrixLatex: initializes the matrix as 1x1 matrix.
ResultMatrixLatex(int, int) - Constructor for class weka.experiment.ResultMatrixLatex: initializes the matrix with the given dimensions.
ResultMatrixLatex(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixLatex: initializes the matrix with the values from the given matrix.
ResultMatrixPlainText - Class in weka.experiment: Generates the output as plain text (for fixed width fonts).
ResultMatrixPlainText() - Constructor for class weka.experiment.ResultMatrixPlainText: initializes the matrix as 1x1 matrix.
ResultMatrixPlainText(int, int) - Constructor for class weka.experiment.ResultMatrixPlainText: initializes the matrix with the given dimensions.
ResultMatrixPlainText(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixPlainText: initializes the matrix with the values from the given matrix.
ResultMatrixSignificance - Class in weka.experiment: Only outputs the significance indicators.
ResultMatrixSignificance() - Constructor for class weka.experiment.ResultMatrixSignificance: initializes the matrix as 1x1 matrix.
ResultMatrixSignificance(int, int) - Constructor for class weka.experiment.ResultMatrixSignificance: initializes the matrix with the given dimensions.
ResultMatrixSignificance(ResultMatrix) - Constructor for class weka.experiment.ResultMatrixSignificance: initializes the matrix with the values from the given matrix.
ResultPanel - Class in weka.gui.sql: Represents a panel for displaying the results of a query in table format.
ResultPanel(JFrame) - Constructor for class weka.gui.sql.ResultPanel: initializes the panel
ResultProducer - Interface in weka.experiment: This interface defines the methods required for an object that produces results for different randomizations of a dataset.
resultProducerTipText() - Method in class weka.experiment.AveragingResultProducer: Returns the tip text for this property
resultProducerTipText() - Method in class weka.experiment.DatabaseResultProducer: Returns the tip text for this property
resultProducerTipText() - Method in class weka.experiment.LearningRateResultProducer: Returns the tip text for this property
ResultSetHelper - Class in weka.gui.sql: Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.
ResultSetHelper(ResultSet) - Constructor for class weka.gui.sql.ResultSetHelper: initializes the helper, with unlimited number of rows.
ResultSetHelper(ResultSet, int) - Constructor for class weka.gui.sql.ResultSetHelper: initializes the helper, with the given maximum number of rows (less than 1 means unlimited).
resultsetKey() - Method in class weka.experiment.PairedTTester: Creates a key that maps resultset numbers to their descriptions.
resultsetKey() - Method in interface weka.experiment.Tester: Creates a key that maps resultset numbers to their descriptions.
ResultSetTable - Class in weka.gui.sql: Represents an extended JTable, containing a table model based on a ResultSet and the corresponding query.
ResultSetTable(String, String, String, String, ResultSetTableModel) - Constructor for class weka.gui.sql.ResultSetTable: initializes the table
ResultSetTableCellRenderer - Class in weka.gui.sql: Handles the background colors for missing values differently than the DefaultTableCellRenderer.
ResultSetTableCellRenderer() - Constructor for class weka.gui.sql.ResultSetTableCellRenderer: initializes the Renderer with a standard color
ResultSetTableCellRenderer(Color, Color) - Constructor for class weka.gui.sql.ResultSetTableCellRenderer: initializes the Renderer with the given colors
ResultSetTableModel - Class in weka.gui.sql: The model for an SQL ResultSet.
ResultSetTableModel(ResultSet) - Constructor for class weka.gui.sql.ResultSetTableModel: initializes the model, retrieves all rows.
ResultSetTableModel(ResultSet, int) - Constructor for class weka.gui.sql.ResultSetTableModel: initializes the model, retrieves only the given amount of rows (0 means all).
ResultsPanel - Class in weka.gui.experiment: This panel controls simple analysis of experimental results.
ResultsPanel() - Constructor for class weka.gui.experiment.ResultsPanel: Creates the results panel with no initial experiment.
resumeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron: Tool tip text for resume property
resumeTipText() - Method in class weka.classifiers.meta.AdaBoostM1: Tool tip text for the resume property
resumeTipText() - Method in class weka.classifiers.meta.AdditiveRegression: Tool tip text for the resume property
resumeTipText() - Method in class weka.classifiers.meta.FilteredClassifier: Tool tip text for finalize property
resumeTipText() - Method in class weka.classifiers.meta.LogitBoost: Tool tip text for the resume property
retainAll(Collection<?>) - Method in class weka.core.Trie: Retains only the elements in this collection that are contained in the specified collection
retainStringValsTipText() - Method in class weka.core.converters.ArffLoader: Tool tip text for this property
retrieveData() - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer
retrieveData() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Get the map of completed images
retrieveData() - Method in interface weka.knowledgeflow.steps.DataCollector: Get the data that this collector has collected
retrieveData() - Method in class weka.knowledgeflow.steps.DataVisualizer
retrieveData() - Method in class weka.knowledgeflow.steps.ImageViewer: Retrieve the data stored in this step.
retrieveData() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Retrieve the data (plots) stored in this step
retrieveData() - Method in class weka.knowledgeflow.steps.TextViewer: Get the results stored in this step.
retrieveDir() - Method in class weka.core.converters.AbstractFileSaver: Gets the directory
retrieveDir() - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
retrieveDir() - Method in interface weka.core.converters.Saver: Gets the driectory of the output file This method is used in the KnowledgeFlow GUI.
retrieveFile() - Method in class weka.core.converters.AbstractFileLoader: get the File specified as the source
retrieveFile() - Method in class weka.core.converters.AbstractFileSaver: Gets the destination file.
retrieveFile() - Method in class weka.core.converters.ArffLoader: get the File specified as the source
retrieveFile() - Method in interface weka.core.converters.FileSourcedConverter: Return the current source file/ destination file
retrieveHeadlessEvents() - Method in class weka.gui.beans.CostBenefitAnalysis: Get the list of events processed in headless mode.
retrieveHeadlessEvents() - Method in class weka.gui.beans.DataVisualizer: Get the list of events processed in headless mode.
retrieveHeadlessEvents() - Method in interface weka.gui.beans.HeadlessEventCollector: Get the list of events processed in headless mode.
retrieveHeadlessEvents() - Method in class weka.gui.beans.ModelPerformanceChart: Get the list of events processed in headless mode.
retrieveHeadlessEvents() - Method in class weka.gui.beans.TextViewer: Get the list of events processed in headless mode.
retrieveInstances() - Method in class weka.experiment.InstanceQuery: Makes a database query using the query set through the -Q option to convert a table into a set of instances
retrieveInstances(InstanceQueryAdapter, ResultSet) - Static method in class weka.experiment.InstanceQuery
retrieveInstances(String) - Method in class weka.experiment.InstanceQuery: Makes a database query to convert a table into a set of instances
retrieveURL() - Method in class weka.core.converters.ArffLoader: Return the current url
retrieveURL() - Method in class weka.core.converters.JSONLoader: Return the current url.
retrieveURL() - Method in class weka.core.converters.LibSVMLoader: Return the current url.
retrieveURL() - Method in class weka.core.converters.MatlabLoader: Return the current url.
retrieveURL() - Method in class weka.core.converters.SVMLightLoader: Return the current url.
retrieveURL() - Method in interface weka.core.converters.URLSourcedLoader: Return the current url
retrieveURL() - Method in class weka.core.converters.XRFFLoader: Return the current url
returnLeaves(ArrayList<RuleNode>[]) - Method in class weka.classifiers.trees.m5.RuleNode: Return a list containing all the leaves in the tree
rev() - Method in class weka.core.matrix.DoubleVector: Returns the reverse vector
revalidate() - Method in class weka.gui.AbstractGUIApplication: Force a re-validation and repaint() of the application
revalidate() - Method in interface weka.gui.GUIApplication: Force a re-validation and repaint() of the application
REVERSED - Static variable in interface weka.gui.graphvisualizer.GraphConstants: Types of Edges
reversedArcs(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: Count nr of reversed arcs from other network compared to current network
revertNewLines(String) - Static method in class weka.core.Utils: Reverts \r and \n in a string into carriage returns and new lines.
REVISION - Static variable in class weka.core.Version: the revision
RevisionHandler - Interface in weka.core: For classes that should return their source control revision.
RevisionUtils - Class in weka.core: Contains utility functions for handling revisions.
RevisionUtils() - Constructor for class weka.core.RevisionUtils
RevisionUtils.Type - Enum in weka.core: Enumeration of source control types.
ridgeTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property
ridgeTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
ridgeTipText() - Method in class weka.estimators.MultivariateGaussianEstimator: Returns the tip text for this property
RIGHT_PARENTHESES - Variable in class weka.experiment.ResultMatrix: the right parentheses for enumerating cols/rows.
rightNode() - Method in class weka.classifiers.trees.m5.RuleNode: Get the right child of this node
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split: Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Prints left side of condition satisfied by instances in subset index.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Does nothing because no condition has to be satisfied.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Prints the condition satisfied by instances in a subset.
rightSide(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Does nothing because no condition has to be satisfied.
rightSide(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Prints the condition satisfied by instances in a subset.
RipperRule() - Constructor for class weka.classifiers.rules.JRip.RipperRule: Constructor
RKeyAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RKeyAdapter
rmCoveredBySuccessives(Instances, ArrayList<Rule>, int) - Static method in class weka.classifiers.rules.RuleStats: Static utility function to count the data covered by the rules after the given index in the given rules, and then remove them.
RMouseAdapter() - Constructor for class weka.gui.ResultHistoryPanel.RMouseAdapter
rnorm(int, double, double, Random) - Static method in class weka.core.matrix.Maths: Generates a sample of a normal distribution.
ROC - Class in weka.core.pmml.jaxbbindings: Java class for ROC element declaration.
ROC() - Constructor for class weka.core.pmml.jaxbbindings.ROC
ROCGraph - Class in weka.core.pmml.jaxbbindings: Java class for ROCGraph element declaration.
ROCGraph() - Constructor for class weka.core.pmml.jaxbbindings.ROCGraph
ROOT_FINDER_ACCURACY - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants
ROOT_FINDER_MAX_ITER - Static variable in interface weka.classifiers.lazy.kstar.KStarConstants: How close the root finder for numeric and nominal have to get
ROOT_NODE - Static variable in class weka.core.xml.XMLOptions: the root node.
ROOT_NODE - Static variable in class weka.core.xml.XMLSerialization: the root node of the XML document
rootMeanPriorSquaredError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the root mean prior squared error.
rootMeanPriorSquaredError() - Method in class weka.classifiers.Evaluation: Returns the root mean prior squared error.
rootMeanSquaredError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the root mean squared error.
rootMeanSquaredError() - Method in class weka.classifiers.Evaluation: Returns the root mean squared error.
rootRelativeSquaredError() - Method in class weka.classifiers.evaluation.Evaluation: Returns the root relative squared error if the class is numeric.
rootRelativeSquaredError() - Method in class weka.classifiers.Evaluation: Returns the root relative squared error if the class is numeric.
rotate(double, double, double) - Method in class weka.gui.visualize.PostscriptGraphics
rotate(double) - Method in class weka.gui.visualize.PostscriptGraphics
round(double) - Static method in class weka.core.Utils: Rounds a double to the next nearest integer value.
roundDouble(double, int) - Static method in class weka.core.Utils: Rounds a double to the given number of decimal places.
Row - Class in weka.core.pmml.jaxbbindings: Java class for row element declaration.
Row() - Constructor for class weka.core.pmml.jaxbbindings.Row
rowNameWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
RPAREN - Static variable in interface weka.core.expressionlanguage.parser.sym
RSQUARE - Static variable in interface weka.core.json.sym
Rule - Class in weka.classifiers.rules: Abstract class of generic rule
Rule() - Constructor for class weka.classifiers.rules.Rule
Rule - Class in weka.classifiers.trees.m5: Generates a single m5 tree or rule
Rule() - Constructor for class weka.classifiers.trees.m5.Rule: Constructor declaration
RULEFEATURE - Enum in weka.core.pmml.jaxbbindings: Java class for RULE-FEATURE.
RuleNode - Class in weka.classifiers.trees.m5: Constructs a node for use in an m5 tree or rule
RuleNode(double, double, RuleNode) - Constructor for class weka.classifiers.trees.m5.RuleNode: Creates a new RuleNode instance.
RuleSelectionMethod - Class in weka.core.pmml.jaxbbindings: Java class for RuleSelectionMethod element declaration.
RuleSelectionMethod() - Constructor for class weka.core.pmml.jaxbbindings.RuleSelectionMethod
RuleSet - Class in weka.core.pmml.jaxbbindings: Java class for RuleSet element declaration.
RuleSet() - Constructor for class weka.core.pmml.jaxbbindings.RuleSet
RuleSetModel - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML RuleSetModel.
RuleSetModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.RuleSetModel: Constructor for a RuleSetModel
RuleSetModel - Class in weka.core.pmml.jaxbbindings: Java class for RuleSetModel element declaration.
RuleSetModel() - Constructor for class weka.core.pmml.jaxbbindings.RuleSetModel
rulesMustContainTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
RuleStats - Class in weka.classifiers.rules: This class implements the statistics functions used in the propositional rule learner, from the simpler ones like count of true/false positive/negatives, filter data based on the ruleset, etc.
RuleStats() - Constructor for class weka.classifiers.rules.RuleStats: Default constructor
RuleStats(Instances, ArrayList<Rule>) - Constructor for class weka.classifiers.rules.RuleStats: Constructor that provides ruleset and data
run(Object, String[]) - Method in class weka.associations.AbstractAssociator: Execute the supplied object.
run(Object, String[]) - Method in class weka.attributeSelection.ASEvaluation: Execute the supplied object.
run(Object, String[]) - Method in class weka.classifiers.AbstractClassifier: Execute the supplied object.
run(Object, String[]) - Method in class weka.clusterers.AbstractClusterer: Execute the supplied object.
run(Object, String[]) - Method in interface weka.core.CommandlineRunnable: Execute the supplied object.
run(Object, String[]) - Method in class weka.core.converters.TextDirectoryLoader
run(Object, String[]) - Method in class weka.core.FindWithCapabilities
run(Object, String[]) - Method in class weka.core.ListOptions
run(Object, String[]) - Method in class weka.filters.Filter: Execute the supplied object.
run() - Method in class weka.gui.beans.FlowRunner: Launch all loaded KnowledgeFlow
run() - Method in class weka.gui.ReaderToTextPane: Sit here listening for lines of input and appending them straight to the text component.
run(File, String[]) - Method in class weka.gui.scripting.Script: Executes the script without loading it first.
run() - Method in class weka.gui.scripting.Script.ScriptThread: Executes the script.
run() - Method in class weka.gui.SimpleCLIPanel.ClassRunner: Starts running the main method.
run(Object, String[]) - Method in class weka.knowledgeflow.FlowRunner: Run a FlowRunner object
run() - Method in class weka.knowledgeflow.FlowRunner: Execute the flow
Run - Class in weka: Helper class that executes Weka schemes from the command line.
Run() - Constructor for class weka.Run
Run.SchemeType - Enum in weka
RUN_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the key field containing the run number
RUN_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer: The name of the key field containing the run number.
RUN_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer: The name of the key field containing the run number
runAssociator(Associator, String[]) - Static method in class weka.associations.AbstractAssociator: runs the associator with the given commandline options
runClassifier(Classifier, String[]) - Static method in class weka.classifiers.AbstractClassifier: runs the classifier instance with the given options.
runClusterer(Clusterer, String[]) - Static method in class weka.clusterers.AbstractClusterer: runs the clusterer instance with the given options.
runCommand(String) - Method in class weka.gui.SimpleCLIPanel: Executes a simple cli command.
runDataGenerator(DataGenerator, String[]) - Static method in class weka.datagenerators.DataGenerator: runs the datagenerator instance with the given options.
runEvaluator(ASEvaluation, String[]) - Static method in class weka.attributeSelection.ASEvaluation: runs the evaluator with the given commandline options
runExperiment(boolean) - Method in class weka.experiment.Experiment
runExperiment() - Method in class weka.experiment.Experiment: Runs all iterations of the experiment, continuing past errors.
runExperiment() - Method in class weka.experiment.RemoteExperiment: Overides runExperiment in Experiment
runFileLoader(AbstractFileLoader, String[]) - Static method in class weka.core.converters.AbstractFileLoader: runs the given loader with the provided options
runFileSaver(AbstractFileSaver, String[]) - Static method in class weka.core.converters.AbstractFileSaver: runs the given saver with the specified options
runFilter(Filter, String[]) - Static method in class weka.filters.Filter: runs the filter instance with the given options.
RunNumberPanel - Class in weka.gui.experiment: This panel controls configuration of lower and upper run numbers in an experiment.
RunNumberPanel() - Constructor for class weka.gui.experiment.RunNumberPanel: Creates the panel with no initial experiment.
RunNumberPanel(Experiment) - Constructor for class weka.gui.experiment.RunNumberPanel: Creates the panel with the supplied initial experiment.
RunPanel - Class in weka.gui.experiment: This panel controls the running of an experiment.
RunPanel() - Constructor for class weka.gui.experiment.RunPanel: Creates the run panel with no initial experiment.
RunPanel(Experiment) - Constructor for class weka.gui.experiment.RunPanel: Creates the panel with the supplied initial experiment.
runParallel() - Method in interface weka.knowledgeflow.FlowExecutor: Run the flow by launching all start points in parallel
runParallel() - Method in class weka.knowledgeflow.FlowRunner: Run the flow by launching start points in parallel
runScript(Script, String[]) - Static method in class weka.gui.scripting.Script: Runs the specified script.
runSequentially() - Method in interface weka.knowledgeflow.FlowExecutor: Run the flow sequentially (i.e.
runSequentially() - Method in class weka.knowledgeflow.FlowRunner: Run the flow by launching start points sequentially.
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
runsTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
runsTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
runTokenizer(Tokenizer, String[]) - Static method in class weka.core.tokenizers.Tokenizer: initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.

S

s_atLeastOnePackageUpgradeHasOccurredInThisSession - Static variable in class weka.gui.PackageManager
s_fileFormatsAvailable - Static variable in class weka.gui.beans.SerializedModelSaver: Available file formats.
s_numericAfterDecimalPoint - Static variable in class weka.core.AbstractInstance: Default max number of digits after the decimal point for numeric values
s_startupListeners - Static variable in class weka.gui.beans.KnowledgeFlowApp
SAMPLE_SIZE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Sample Size
sampleSizePercentTipText() - Method in class weka.filters.supervised.instance.Resample: Returns the tip text for this property.
sampleSizePercentTipText() - Method in class weka.filters.unsupervised.instance.Resample: Returns the tip text for this property
sampleSizeTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
sampleSizeTipText() - Method in class weka.filters.unsupervised.instance.ReservoirSample: Returns the tip text for this property
save(StringBuffer) - Method in class weka.gui.SaveBuffer: Save a buffer
save() - Method in class weka.gui.scripting.Script: Saves the file under with the current filename.
save(File, String) - Static method in class weka.gui.scripting.ScriptUtils: Saves the content to a file.
SAVE_DIALOG - Static variable in class weka.gui.knowledgeflow.KFGUIConsts: Constant for a save dialog (same as JFileChooser.SAVE_DIALOG)
saveAs(File) - Method in class weka.gui.scripting.Script: Saves the file under with the given filename (and updates the internal filename).
saveBatch() - Method in class weka.gui.beans.Saver: Saves instances in batch mode
saveBinary(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver: Save a model in binary form.
SaveBuffer - Class in weka.gui: This class handles the saving of StringBuffers to files.
SaveBuffer(Logger, Component) - Constructor for class weka.gui.SaveBuffer: Constructor
saveClassifier(String, Classifier, Instances) - Method in class weka.gui.explorer.ClassifierPanel: Saves the currently selected classifier.
saveComponent() - Method in class weka.gui.visualize.PrintableComponent: displays a save dialog for saving the panel to a file.
saveComponent() - Method in interface weka.gui.visualize.PrintableHandler: displays a save dialog for saving the component to a file.
saveComponent() - Method in class weka.gui.visualize.PrintablePanel: displays a save dialog for saving the panel to a file.
saveDictionary(String, boolean) - Method in class weka.core.DictionaryBuilder: Save the dictionary
saveDictionary(File, boolean) - Method in class weka.core.DictionaryBuilder: Save a dictionary
saveDictionary(Writer) - Method in class weka.core.DictionaryBuilder: Save the dictionary in textual format
saveDictionary(OutputStream) - Method in class weka.core.DictionaryBuilder: Save the dictionary in binary form
saveDictionaryInBinaryFormTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector
saveFile() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: saves the current data into a file
saveFileAs() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: saves the current data into a new file
saveFlow(File) - Method in class weka.knowledgeflow.Flow: Save this Flow to the supplied File
saveInstanceDataTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
saveInstanceDataTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
saveInstancesTipText() - Method in class weka.classifiers.trees.M5P: Returns the tip text for this property
saveInstancesToFile(AbstractFileSaver, Instances) - Method in class weka.gui.explorer.PreprocessPanel: saves the data with the specified saver
saveKOML(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver: Save a model in KOML deep object serialized XML form.
saveLayout(File, int) - Method in class weka.gui.beans.KnowledgeFlowApp
saveLayout(OutputStream, int) - Method in class weka.gui.beans.KnowledgeFlowApp: Save the knowledge flow into the OutputStream passed at input.
saveModel() - Method in class weka.gui.beans.Classifier
saveModel() - Method in class weka.gui.beans.Clusterer
Saver - Interface in weka.core.converters: Interface to something that can save Instances to an output destination in some format.
Saver - Class in weka.gui.beans: Saves data sets using weka.core.converter classes
Saver() - Constructor for class weka.gui.beans.Saver: Contsructor
SAVER - Static variable in class weka.knowledgeflow.JSONFlowUtils
Saver - Class in weka.knowledgeflow.steps: Step that wraps weka.core.converters.Saver classes
Saver() - Constructor for class weka.knowledgeflow.steps.Saver
SAVER_DIALOG - Static variable in class weka.gui.ConverterFileChooser: the saver dialog.
SaverBeanInfo - Class in weka.gui.beans: Bean info class for the saver bean
SaverBeanInfo() - Constructor for class weka.gui.beans.SaverBeanInfo
SaverCustomizer - Class in weka.gui.beans: GUI Customizer for the saver bean
SaverCustomizer() - Constructor for class weka.gui.beans.SaverCustomizer: Constructor
SaverStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the saver step
SaverStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SaverStepEditorDialog: Constructor
saveSettings() - Method in class weka.core.Settings: Save the settings to the metastore
saveSize() - Method in class weka.gui.sql.SqlViewer: obtains the size of the panel and saves it in the history.
saveToFile(String, Object) - Static method in class weka.core.Debug: writes the serialized object to the speicified file
saveWeights() - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to have the connection save the current weights.
saveWeights() - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to have the connection save the current weights.
saveWorkingInstancesToFileQ() - Method in class weka.gui.explorer.PreprocessPanel: Queries the user for a file to save instances as, then saves the instances in a background process.
saveXStream(File, Object, Instances) - Static method in class weka.gui.beans.SerializedModelSaver: Save a model in XStream deep object serialized XML form.
scalarMultiply(double) - Method in class weka.core.AlgVector: Computes the scalar product of this vector with a scalar
scale(int) - Method in class weka.gui.beans.BeanVisual: Reduce this BeanVisual's icon size by the given factor
scale(double) - Method in class weka.gui.beans.BeanVisual
scale(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
scaleIcon(ImageIcon, double) - Static method in class weka.gui.knowledgeflow.StepVisual: Scale the supplied icon by the given factor
scaleTipText() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the tip text for this property.
Scanner - Class in weka.core.expressionlanguage.parser: A lexical scanner for an expression language.
Scanner(Reader) - Constructor for class weka.core.expressionlanguage.parser.Scanner: Creates a new scanner
Scanner - Class in weka.core.json: A scanner for JSON data files.
Scanner(InputStream, SymbolFactory) - Constructor for class weka.core.json.Scanner
Scanner(Reader, SymbolFactory) - Constructor for class weka.core.json.Scanner
Scanner(Reader) - Constructor for class weka.core.json.Scanner: Creates a new scanner
ScatterDefaults() - Constructor for class weka.gui.explorer.VisualizePanel.ScatterDefaults
ScatterPlotMatrix - Class in weka.gui.beans: Bean that encapsulates weka.gui.visualize.MatrixPanel for displaying a scatter plot matrix.
ScatterPlotMatrix() - Constructor for class weka.gui.beans.ScatterPlotMatrix
ScatterPlotMatrix - Class in weka.knowledgeflow.steps: Step that collects data for display in a scatter plot matrix.
ScatterPlotMatrix() - Constructor for class weka.knowledgeflow.steps.ScatterPlotMatrix
ScatterPlotMatrixBeanInfo - Class in weka.gui.beans: Bean info class for the scatter plot matrix bean
ScatterPlotMatrixBeanInfo() - Constructor for class weka.gui.beans.ScatterPlotMatrixBeanInfo
ScatterPlotMatrixInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the ScatterPlotMatrix step
ScatterPlotMatrixInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.ScatterPlotMatrixInteractiveView
ScatterPlotMatrixPerspective - Class in weka.gui.knowledgeflow: Knowledge Flow perspective for the scatter plot matrix
ScatterPlotMatrixPerspective() - Constructor for class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Constructor
Scoreable - Interface in weka.classifiers.bayes.net.search.local: Interface for allowing to score a classifier
Scorecard - Class in weka.core.pmml.jaxbbindings: Java class for Scorecard element declaration.
Scorecard() - Constructor for class weka.core.pmml.jaxbbindings.Scorecard
ScoreDistribution - Class in weka.core.pmml.jaxbbindings: Java class for ScoreDistribution element declaration.
ScoreDistribution() - Constructor for class weka.core.pmml.jaxbbindings.ScoreDistribution
scoreTypeTipText() - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
Script - Class in weka.gui.scripting: A simple helper class for loading, saving scripts.
Script() - Constructor for class weka.gui.scripting.Script: Initializes the script.
Script(Document) - Constructor for class weka.gui.scripting.Script: Initializes the script.
Script(Document, File) - Constructor for class weka.gui.scripting.Script: Initializes the script.
Script - Class in weka.gui.simplecli: Executes commands from a script file.
Script() - Constructor for class weka.gui.simplecli.Script
Script.ScriptThread - Class in weka.gui.scripting: The Thread for running a script.
ScriptExecutionEvent - Class in weka.gui.scripting.event: Event that gets sent when a script is executed.
ScriptExecutionEvent(Script, ScriptExecutionEvent.Type) - Constructor for class weka.gui.scripting.event.ScriptExecutionEvent: Initializes the event.
ScriptExecutionEvent(Script, ScriptExecutionEvent.Type, Object) - Constructor for class weka.gui.scripting.event.ScriptExecutionEvent: Initializes the event.
ScriptExecutionEvent.Type - Enum in weka.gui.scripting.event: Defines the type of event.
ScriptExecutionListener - Interface in weka.gui.scripting.event: For classes that want to be notified about changes in the script execution.
scriptFinished(ScriptExecutionEvent) - Method in interface weka.gui.scripting.event.ScriptExecutionListener: Gets sent when a script execution changes.
scriptFinished(ScriptExecutionEvent) - Method in class weka.gui.scripting.FileScriptingPanel: Gets sent when a script finishes execution.
ScriptingPanel - Class in weka.gui.scripting: Abstract ancestor for scripting panels.
ScriptingPanel() - Constructor for class weka.gui.scripting.ScriptingPanel: Default constructor.
ScriptThread(Script, String[]) - Constructor for class weka.gui.scripting.Script.ScriptThread: Initializes the thread.
ScriptUtils - Class in weka.gui.scripting: A helper class for Script related stuff.
ScriptUtils() - Constructor for class weka.gui.scripting.ScriptUtils
SCROLL_BAR_INCREMENT_LAYOUT - Static variable in class weka.knowledgeflow.KFDefaults
scrollToVisible(int, int) - Method in class weka.gui.JTableHelper: Assumes table is contained in a JScrollPane.
scrollToVisible(JTable, int, int) - Static method in class weka.gui.JTableHelper: Assumes table is contained in a JScrollPane.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.ASSearch: Searches the attribute subset/ranking space.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.BestFirst: Searches the attribute subset space by best first search
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.GreedyStepwise: Searches the attribute subset space by forward selection.
search(ASEvaluation, Instances) - Method in class weka.attributeSelection.Ranker: Kind of a dummy search algorithm.
search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.K2: search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.K2: search determines the network structure/graph of the network with the K2 algorithm, restricted by its initial structure (which can be an empty graph, or a Naive Bayes graph.
search(BayesNet, Instances) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
search() - Method in class weka.gui.arffviewer.ArffPanel: searches for a string in the cells
search() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: searches for a string in the cells
search(Vector<HierarchyPropertyParser.TreeNode>, String) - Method in class weka.gui.HierarchyPropertyParser: Helper function to search for the given target string in a given vector in which the elements' value may hopefully is equal to the target.
SearchAlgorithm - Class in weka.classifiers.bayes.net.search: This is the base class for all search algorithms for learning Bayes networks.
SearchAlgorithm() - Constructor for class weka.classifiers.bayes.net.search.SearchAlgorithm: c'tor
searchAlgorithmTipText() - Method in class weka.classifiers.bayes.BayesNet
searchBackwardsTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
searchFinish() - Method in class weka.core.neighboursearch.PerformanceStats: Signals end of the nearest neighbour search.
searchFinish() - Method in class weka.core.neighboursearch.TreePerformanceStats: Signals end of the nearest neighbour search.
searchMethodTipText() - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Returns the tip text for this property
searchPoints(int, int, boolean) - Method in class weka.gui.visualize.Plot2D: Pops up a window displaying attribute information on any instances at a point+-plotting_point_size (in panel coordinates)
searchStart() - Method in class weka.core.neighboursearch.PerformanceStats: Signals start of the nearest neighbour search.
searchStart() - Method in class weka.core.neighboursearch.TreePerformanceStats: Signals start of the nearest neighbour search.
searchTerminationTipText() - Method in class weka.attributeSelection.BestFirst: Returns the tip text for this property
searchTipText() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Returns the tip text for this property
searchTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
searchTipText() - Method in class weka.filters.supervised.attribute.AttributeSelection: Returns the tip text for this property
SeasonalityExpoSmooth - Class in weka.core.pmml.jaxbbindings: Java class for Seasonality_ExpoSmooth element declaration.
SeasonalityExpoSmooth() - Constructor for class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth
secondInstanceProduced(InstanceEvent) - Method in class weka.gui.streams.InstanceJoiner
secondInstanceProduced(InstanceEvent) - Method in interface weka.gui.streams.SerialInstanceListener
secondValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.MergeTwoValues
secondValueIndexTipText() - Method in class weka.filters.unsupervised.attribute.SwapValues
seedTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.OneRAttributeEval: Returns a string for this option suitable for display in the gui as a tip text
seedTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
seedTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber
seedTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber
seedTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
seedTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
seedTipText() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.functions.VotedPerceptron: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.meta.MultiScheme: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableClassifier: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.RandomTree: Returns the tip text for this property
seedTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.Cobweb: Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.RandomizableClusterer: Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Returns the tip text for this property
seedTipText() - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Returns the tip text for this property
seedTipText() - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Returns the tip text for this property.
seedTipText() - Method in class weka.datagenerators.DataGenerator: Returns the tip text for this property
seedTipText() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns the tip text for this property
seedTipText() - Method in class weka.filters.MultiFilter: Returns the tip text for this property
seedTipText() - Method in class weka.filters.supervised.attribute.ClassOrder: Returns the tip text for this property
seedTipText() - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Returns the tip text for this property
seedTipText() - Method in class weka.filters.unsupervised.attribute.RandomProjection: Returns the tip text for this property
seedTipText() - Method in class weka.filters.unsupervised.attribute.RandomSubset: Returns the tip text for this property.
seedTipText() - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Returns the tip text for this property
seedTipText() - Method in class weka.filters.unsupervised.instance.RemoveFolds: Returns the tip text for this property
seedTipText() - Method in class weka.gui.beans.CrossValidationFoldMaker: Tip text for this property
seedTipText() - Method in class weka.gui.beans.TrainTestSplitMaker: Tip text for this property
Segment - Class in weka.core.pmml.jaxbbindings: Java class for Segment element declaration.
Segment() - Constructor for class weka.core.pmml.jaxbbindings.Segment
Segmentation - Class in weka.core.pmml.jaxbbindings: Java class for Segmentation element declaration.
Segmentation() - Constructor for class weka.core.pmml.jaxbbindings.Segmentation
select(int, int[], int, int, int) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".
select(int, int[], int, int, int) - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension: Implements computation of the kth-smallest element according to Manber's "Introduction to Algorithms".
select(String) - Method in class weka.experiment.DatabaseUtils: Executes a SQL SELECT query that returns a ResultSet.
SelectAttributes(ASEvaluation, String[]) - Static method in class weka.attributeSelection.AttributeSelection: Perform attribute selection with a particular evaluator and a set of options specifying search method and input file etc.
SelectAttributes(Instances) - Method in class weka.attributeSelection.AttributeSelection: Perform attribute selection on the supplied training instances.
SelectAttributes(ASEvaluation, String[], Instances) - Static method in class weka.attributeSelection.AttributeSelection: Perform attribute selection with a particular evaluator and a set of options specifying search method and options for the search method and evaluator.
selectAttributesCVSplit(Instances) - Method in class weka.attributeSelection.AttributeSelection: Select attributes for a split of the data.
selectedAttributes() - Method in class weka.attributeSelection.AttributeSelection: get the final selected set of attributes.
selectedAttributesTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the tip text for this property
SelectedPerspectivePreferences() - Constructor for class weka.gui.PerspectiveManager.SelectedPerspectivePreferences
SelectedTag - Class in weka.core: Represents a selected value from a finite set of values, where each value is a Tag (i.e.
SelectedTag(int, Tag[]) - Constructor for class weka.core.SelectedTag: Creates a new SelectedTag instance.
SelectedTag(String, Tag[]) - Constructor for class weka.core.SelectedTag: Creates a new SelectedTag instance.
SelectedTagEditor - Class in weka.gui: A PropertyEditor that uses tags, where the tags are obtained from a weka.core.SelectedTag object.
SelectedTagEditor() - Constructor for class weka.gui.SelectedTagEditor
SELECTION_GREEDY - Static variable in class weka.classifiers.functions.LinearRegression: Attribute selection method: Greedy method
SELECTION_M5 - Static variable in class weka.classifiers.functions.LinearRegression: Attribute selection method: M5 method
SELECTION_NONE - Static variable in class weka.classifiers.functions.LinearRegression: Attribute selection method: No attribute selection
selectModel(Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Selects C4.5-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.BinC45ModelSelection: Selects C4.5-type split for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection: Selects C4.5-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.C45ModelSelection: Selects C4.5-type split for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.j48.ModelSelection: Selects a model for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.ModelSelection: Selects a model for the given train data using the given test data
selectModel(Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Selects NBTree-type split for the given dataset.
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.j48.NBTreeModelSelection: Selects NBTree-type split for the given dataset.
selectModel(Instances, double[][], double[][]) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Selects split based on residuals for the given dataset.
selectModel(Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Method not in use
selectModel(Instances, Instances) - Method in class weka.classifiers.trees.lmt.ResidualModelSelection: Method not in use
SemanticException - Exception in weka.core.expressionlanguage.core: An exception that should be used if a program doesn't have valid semantics
SemanticException(String, Exception) - Constructor for exception weka.core.expressionlanguage.core.SemanticException: Constructs a SemanticException with a message and cause
SemanticException(String) - Constructor for exception weka.core.expressionlanguage.core.SemanticException: Constructs a SemanticException with a message
SEND_INSTANCES - Static variable in class weka.gui.treevisualizer.TreeDisplayEvent: Command to remove instances from this node and send them to the VisualizePanel.
SEND_TO_PERSPECTIVE_COMMAND_KEY - Static variable in class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand: Command ID
SendToPerspective - Class in weka.knowledgeflow.steps: Step that can send incoming instances to a perspective.
SendToPerspective() - Constructor for class weka.knowledgeflow.steps.SendToPerspective
SendToPerspectiveGraphicalCommand - Class in weka.gui.knowledgeflow: Class implementing sending a set of Instances to a named perspective
SendToPerspectiveGraphicalCommand() - Constructor for class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand
SendToPerspectiveStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Dialog for the SendToPerspective step
SendToPerspectiveStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SendToPerspectiveStepEditorDialog
SEP1 - Static variable in class weka.knowledgeflow.steps.SetVariables: Separators for internal variable specification
SEP1 - Static variable in class weka.knowledgeflow.steps.StorePropertiesInEnvironment: Separators for internal variable specification
SEP2 - Static variable in class weka.knowledgeflow.steps.SetVariables
SEP2 - Static variable in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
SEP3 - Static variable in class weka.knowledgeflow.steps.SetVariables
seq(int, int) - Static method in class weka.core.matrix.IntVector: Generates an IntVector that stores all integers inclusively between two integers.
Sequence - Class in weka.core.pmml.jaxbbindings: Java class for Sequence element declaration.
Sequence() - Constructor for class weka.core.pmml.jaxbbindings.Sequence
SequenceModel - Class in weka.core.pmml.jaxbbindings: Java class for SequenceModel element declaration.
SequenceModel() - Constructor for class weka.core.pmml.jaxbbindings.SequenceModel
SequenceReference - Class in weka.core.pmml.jaxbbindings: Java class for SequenceReference element declaration.
SequenceReference() - Constructor for class weka.core.pmml.jaxbbindings.SequenceReference
SequenceRule - Class in weka.core.pmml.jaxbbindings: Java class for SequenceRule element declaration.
SequenceRule() - Constructor for class weka.core.pmml.jaxbbindings.SequenceRule
SERIAL_VERSION_UID - Static variable in class weka.core.SerializationHelper: the field name of serialVersionUID.
SerialInstanceListener - Interface in weka.gui.streams: Defines an interface for objects able to produce two output streams of instances.
SerializationHelper - Class in weka.core: A helper class for determining serialVersionUIDs and checking whether classes contain one and/or need one.
SerializationHelper() - Constructor for class weka.core.SerializationHelper
serialize(Object) - Static method in class weka.core.xml.XStream: Serializes the supplied object xml
SERIALIZED_OBJ_FILE_EXTENSION - Static variable in class weka.core.Instances: The filename extension that should be used for bin.
SerializedClassifier - Class in weka.classifiers.misc: A wrapper around a serialized classifier model.
SerializedClassifier() - Constructor for class weka.classifiers.misc.SerializedClassifier
serializedClassifierFileTipText() - Method in class weka.filters.supervised.attribute.AddClassification: Returns the tip text for this property.
serializedClustererFileTipText() - Method in class weka.filters.unsupervised.attribute.AddCluster: Returns the tip text for this property.
SerializedInstancesLoader - Class in weka.core.converters: Reads a source that contains serialized Instances.
SerializedInstancesLoader() - Constructor for class weka.core.converters.SerializedInstancesLoader
SerializedInstancesSaver - Class in weka.core.converters: Serializes the instances to a file with extension bsi.
SerializedInstancesSaver() - Constructor for class weka.core.converters.SerializedInstancesSaver: Constructor.
SerializedModelSaver - Class in weka.gui.beans: A bean that saves serialized models
SerializedModelSaver() - Constructor for class weka.gui.beans.SerializedModelSaver: Constructor.
SerializedModelSaver - Class in weka.knowledgeflow.steps: Step that can save models encapsulated in incoming Data objects to the filesystem.
SerializedModelSaver() - Constructor for class weka.knowledgeflow.steps.SerializedModelSaver
SerializedModelSaverBeanInfo - Class in weka.gui.beans: Bean info class for the serialized model saver bean
SerializedModelSaverBeanInfo() - Constructor for class weka.gui.beans.SerializedModelSaverBeanInfo
SerializedModelSaverCustomizer - Class in weka.gui.beans: GUI Customizer for the SerializedModelSaver bean
SerializedModelSaverCustomizer() - Constructor for class weka.gui.beans.SerializedModelSaverCustomizer: Constructor
SerializedObject - Class in weka.core: Class for storing an object in serialized form in memory.
SerializedObject(Object) - Constructor for class weka.core.SerializedObject: Creates a new serialized object (without compression).
SerializedObject(Object, boolean) - Constructor for class weka.core.SerializedObject: Creates a new serialized object.
serializePMMLModel(PMMLModel, String) - Static method in class weka.core.pmml.PMMLFactory: Serialize a PMMLModel object that encapsulates a PMML model
serializePMMLModel(PMMLModel, File) - Static method in class weka.core.pmml.PMMLFactory: Serialize a PMMLModel object that encapsulates a PMML model
serializePMMLModel(PMMLModel, OutputStream) - Static method in class weka.core.pmml.PMMLFactory: Serialize a PMMLModel object that encapsulates a PMML model
serializeStepsToJSON(List<StepVisual>, String) - Static method in class weka.gui.knowledgeflow.VisibleLayout: Utility method to serialize a list of steps (encapsulated in StepVisuals) to a JSON flow.
SerialUIDChanger - Class in weka.core.xml: This class enables one to change the UID of a serialized object and therefore not losing the data stored in the binary format.
SerialUIDChanger() - Constructor for class weka.core.xml.SerialUIDChanger
serialVersionUID - Static variable in class weka.gui.explorer.VisualizePanel.ScatterDefaults
set(int, Instance) - Method in class weka.core.Instances: Replaces the instance at the given position.
set(int, double) - Method in class weka.core.matrix.DoubleVector: Set a single element.
set(double) - Method in class weka.core.matrix.DoubleVector: Set all elements to a value
set(int, int, double) - Method in class weka.core.matrix.DoubleVector: Set some elements to a value
set(int, int, double[], int) - Method in class weka.core.matrix.DoubleVector: Set some elements using a 2-D array
set(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Set the elements using a DoubleVector
set(int, int, DoubleVector, int) - Method in class weka.core.matrix.DoubleVector: Set some elements using a DoubleVector.
set(int) - Method in class weka.core.matrix.IntVector: Sets the value of an element.
set(int, int, int[], int) - Method in class weka.core.matrix.IntVector: Sets the values of elements from an int array.
set(int, int, IntVector, int) - Method in class weka.core.matrix.IntVector: Sets the values of elements from another IntVector.
set(IntVector) - Method in class weka.core.matrix.IntVector: Sets the values of elements from another IntVector.
set(int, int) - Method in class weka.core.matrix.IntVector: Sets a single element.
set(int, int, double) - Method in class weka.core.matrix.Matrix: Set a single element.
set(int, T) - Method in class weka.core.neighboursearch.covertrees.Stack: Sets the ith element in the stack.
set(int, Object) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Replaces the element at the specified position in this list with the specified element.
set(String, String) - Static method in class weka.gui.explorer.ExplorerDefaults
Set - Class in weka.gui.simplecli: Sets a variable.
Set() - Constructor for class weka.gui.simplecli.Set
SET_SYSTEM_PROPERTIES_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for setting system properties
setAbsoluteValue(Double) - Method in class weka.core.pmml.jaxbbindings.Coefficients: Sets the value of the absoluteValue property.
setActivationFunction(ACTIVATIONFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the activationFunction property.
setActivationFunction(ACTIVATIONFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the activationFunction property.
setActive(boolean) - Method in class weka.gui.AbstractPerspective: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.beans.AttributeSummarizer: Set active status of this perspective.
setActive(boolean) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setActive(boolean) - Method in class weka.gui.beans.ScatterPlotMatrix: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.beans.SQLViewerPerspective: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.explorer.AssociationsPanel
setActive(boolean) - Method in class weka.gui.explorer.AttributeSelectionPanel
setActive(boolean) - Method in class weka.gui.explorer.ClassifierPanel
setActive(boolean) - Method in class weka.gui.explorer.ClustererPanel
setActive(boolean) - Method in class weka.gui.explorer.PreprocessPanel
setActive(boolean) - Method in class weka.gui.explorer.VisualizePanel: Make sure current settings are applied when this panel becomes active
setActive(boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Called when this perspective becomes the "active" (i.e.
setActive(boolean) - Method in interface weka.gui.Perspective: Set active status of this perspective.
setActive(boolean) - Method in class weka.gui.SimpleCLIPanel
setActivePerspective(int) - Method in class weka.gui.PerspectiveManager: Set the active perspective
setActivePerspective(String) - Method in class weka.gui.PerspectiveManager: Set the active perspective
setActiveTab(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setActiveTab(int) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set the active (visible) tab
setAcuity(double) - Method in class weka.clusterers.Cobweb: set the acuity.
setAdditionalMeasures(String[]) - Method in class weka.experiment.AveragingResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator: Set a list of method names for additional measures to look for in Classifiers.
setAdditionalMeasures(String[]) - Method in class weka.experiment.CrossValidationResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.DatabaseResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Set a list of method names for additional measures to look for in Classifiers.
setAdditionalMeasures(String[]) - Method in class weka.experiment.ExplicitTestsetResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.LearningRateResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.RandomSplitResultProducer: Set a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in class weka.experiment.RegressionSplitEvaluator: Set a list of method names for additional measures to look for in Classifiers.
setAdditionalMeasures(String[]) - Method in interface weka.experiment.ResultProducer: Sets a list of method names for additional measures to look for in SplitEvaluators.
setAdditionalMeasures(String[]) - Method in interface weka.experiment.SplitEvaluator: Sets a list of method names for additional measures to look for in SplitEvaluators.
setAddMatchingEndBlocks(boolean) - Method in class weka.gui.scripting.SyntaxDocument: Sets whether matching block ends are inserted or not.
setAdjRSquared(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the adjRSquared property.
setAdjustWeights(boolean) - Method in class weka.filters.supervised.instance.SpreadSubsample: Sets whether the instance weights will be adjusted to maintain total weight per class.
setAdvanceDataSetFirst(boolean) - Method in class weka.experiment.Experiment: Set the value of m_AdvanceDataSetFirst.
setAffinity(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the affinity property.
setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the aggregate property.
setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the aggregate property.
setAggregate(Aggregate) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the aggregate property.
setAIC(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the aic property.
setAICc(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the aiCc property.
setAlgorithm(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the algorithm property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.MiningModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Sets the value of the algorithmName property.
setAlgorithmName(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the algorithmName property.
setAllAttributeWeightsToOne(boolean) - Method in class weka.filters.unsupervised.attribute.Reorder: Whether to set all attribute weights to one in output data.
setAllowMultipleTabs(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp
setAllowMultipleTabs(boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set whether multiple tabs are allowed
setAllowUnclassifiedInstances(boolean) - Method in class weka.classifiers.trees.RandomTree: Set the value of AllowUnclassifiedInstances.
setAlpha(double) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Set prior used in probability table estimation
setAlpha(Double) - Method in class weka.core.pmml.jaxbbindings.Level: Sets the value of the alpha property.
setAlternate(Alternate) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the alternate property.
setAlternateTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Sets the value of the alternateTargetCategory property.
setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the altitude property.
setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the altitude property.
setAltitude(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron: Sets the value of the altitude property.
setAmplitude(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Sets the amplitude multiplier.
setAnimated() - Method in class weka.gui.beans.BeanVisual: Deprecated.
setAnova(Anova) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the anova property.
setAntecedent(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the antecedent property.
setAnyDistribution(AnyDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate: Sets the value of the anyDistribution property.
setAnyDistribution(AnyDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the anyDistribution property.
setAppend(boolean) - Method in class weka.gui.beans.TextSaver
setAppend(boolean) - Method in class weka.knowledgeflow.steps.TextSaver: Set whether the file should be appended to rather than overwritten
setAppendPredictedProbabilities(boolean) - Method in class weka.gui.beans.PredictionAppender: Set whether to append predicted probabilities rather than class value (for discrete class data sets)
setAppendProbabilities(boolean) - Method in class weka.knowledgeflow.steps.PredictionAppender: Set whether to append probability distributions rather than predicted classes
setApplication(Application) - Method in class weka.core.pmml.jaxbbindings.Header: Sets the value of the application property.
setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the apply property.
setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the apply property.
setApply(Apply) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the apply property.
setAppropriateSize() - Method in class weka.classifiers.bayes.net.GUI: Sets the preferred size for m_GraphPanel GraphPanel to the minimum size that is neccessary to display the graph.
setArffFile(String) - Method in class weka.gui.streams.InstanceLoader
setArffFile(String) - Method in class weka.gui.streams.InstanceSavePanel
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.BoundaryValueMeans: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.BoundaryValues: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.ClassLabels: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.CorrelationFields: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.MissingValueWeights: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TextDictionary: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TimeException: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.XCoordinates: Sets the value of the array property.
setArray(ArrayType) - Method in class weka.core.pmml.jaxbbindings.YCoordinates: Sets the value of the array property.
setAssociatedConnections(Vector<BeanConnection>) - Method in class weka.gui.beans.MetaBean
setAssociationModel(AssociationModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the associationModel property.
setAssociator(Associator) - Method in class weka.associations.CheckAssociator: Set the associator to test.
setAssociator(Associator) - Method in class weka.associations.SingleAssociatorEnhancer: Set the base associator.
setAssociator(Associator) - Method in class weka.gui.beans.Associator: Set the associator for this wrapper
setAssociator(Associator) - Method in class weka.knowledgeflow.steps.Associator: Set the associator to use.
setAsText(String) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
setAsText(String) - Method in class weka.gui.ColorEditor: Throws an exception as we are not representable in text form
setAsText(String) - Method in class weka.gui.CostMatrixEditor: Some objects can be represented as text, but a cost matrix cannot.
setAsText(String) - Method in class weka.gui.EnvironmentField
setAsText(String) - Method in class weka.gui.FileEnvironmentField
setAsText(String) - Method in class weka.gui.GenericArrayEditor: Returns null as we don't support getting/setting values as text.
setAsText(String) - Method in class weka.gui.GenericObjectEditor: Returns null as we don't support getting/setting values as text.
setAsText(String) - Method in class weka.gui.PasswordField
setAsText(String) - Method in class weka.gui.RangeEditor: Sets the current property value as text.
setAsText(String) - Method in class weka.gui.SelectedTagEditor: Sets the current property value as text.
setAsText(String) - Method in class weka.gui.SimpleDateFormatEditor: Sets the date format string.
setAttList_Irr(boolean[]) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the array that defines which of the attributes are seen to be irrelevant.
setAttribute(int) - Method in class weka.gui.AttributeSummaryPanel: Sets the attribute that statistics will be displayed for.
setAttribute(int) - Method in class weka.gui.AttributeVisualizationPanel: Tells the panel which attribute to visualize.
setAttribute(String) - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Set the name or index of the attribute to sort on
setAttributeColor(SyntaxDocument.ATTR_TYPE, Color) - Method in class weka.gui.scripting.SyntaxDocument: Sets the foreground (font) color of the specified attribute.
setAttributeColor(MutableAttributeSet, Color) - Static method in class weka.gui.scripting.SyntaxDocument: Sets the foreground (font) color of the specified attribute.
setAttributeFont(SyntaxDocument.ATTR_TYPE, int) - Method in class weka.gui.scripting.SyntaxDocument: Sets the font of the specified attribute.
setAttributeFont(MutableAttributeSet, Font) - Static method in class weka.gui.scripting.SyntaxDocument: Sets the font of the specified attribute.
setAttributeID(int) - Method in class weka.experiment.ClassifierSplitEvaluator: Set the index of Attibute Identifying the instances
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.Add: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.AddNoise: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.AddValues: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Sets the index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Sets index of the attribute used.
setAttributeIndex(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Sets index of the attribute used.
setAttributeIndexes(String) - Method in class weka.filters.unsupervised.attribute.NominalToString: Sets index of the attribute used.
setAttributeIndices(String) - Method in class weka.core.converters.DictionarySaver: Sets which attributes are to be worked on.
setAttributeIndices(String) - Method in class weka.core.DictionaryBuilder: Sets which attributes are to be worked on.
setAttributeIndices(String) - Method in interface weka.core.DistanceFunction: Sets the range of attributes to use in the calculation of the distance.
setAttributeIndices(String) - Method in class weka.core.FilteredDistance: Sets the range of attributes to use in the calculation of the distance.
setAttributeIndices(String) - Method in class weka.core.NormalizableDistance: Sets the range of attributes to use in the calculation of the distance.
setAttributeIndices(String) - Method in class weka.filters.supervised.attribute.Discretize: Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndices(String) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Set which attributes are to be acted on (or not, if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Copy: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Sets which attributes are to be turned into numeric attributes (only date attributes among the selection will be transformed).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.FirstOrder: Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets which attributes are to be worked on.
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Set which attributes are to be acted on (or not, if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Sets which attributes are to be acted on.
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Sets the columns to use, e.g., first-last or first-3,5-last
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Sets which attributes are to be "binarized" (only numeric attributes among the selection will be transformed).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Sets which attributes are to be turned into date attributes (only numeric attributes among the selection will be transformed).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Sets which attributes are to be "nominalized" (only numeric attributes among the selection will be transformed).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Set which attributes are to be transformed (or kept if invert is true).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Remove: Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Sets which attributes are to be acted on.
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.Reorder: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Sets which attributes are to be "nominalized" (only numeric attributes among the selection will be transformed).
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.SortLabels: Set the range of attributes to process.
setAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets which attributes are to be worked on.
setAttributeIndicesArray(int[]) - Method in class weka.core.DictionaryBuilder: Sets which attributes are to be processed.
setAttributeIndicesArray(int[]) - Method in class weka.filters.supervised.attribute.Discretize: Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndicesArray(int[]) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Set which attributes are to be acted on (or not, if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Sets which attributes are to be used.
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Copy: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Sets which attributes are to be transformed to numeric attributes (only date attributes among the selection will be transformed).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets which attributes are to be Discretized (only numeric attributes among the selection will be Discretized).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder: Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Sets which attributes are to be used for interquartile calculations and outlier/extreme value detection (only numeric attributes among the selection will be used).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Set which attributes are to be acted on (or not, if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Sets which attributes are to be transformed to binary.
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Sets which attributes are to be transformed to date attributes (only numeric attributes among the selection will be transformed).
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Sets which attributes are to be transoformed to nominal.
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Set which attributes are to be transformed (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Remove: Set which attributes are to be deleted (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.Reorder: Set which attributes are to be copied (or kept if invert is true)
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Sets which attributes are to be transoformed to nominal.
setAttributeIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets which attributes are to be processed.
setAttributeName(String) - Method in class weka.filters.unsupervised.attribute.Add: Set the new attribute's name.
setAttributeName(String) - Method in class weka.filters.unsupervised.attribute.AddID: Set the new attribute's name
setAttributeNamePrefix(String) - Method in class weka.core.DictionaryBuilder: Set the attribute name prefix.
setAttributeNamePrefix(String) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Set the attribute name prefix.
setAttributeNamePrefix(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the attribute name prefix.
setAttributeRange(String) - Method in class weka.filters.unsupervised.attribute.StringToNominal: Sets range of indices of the attributes used.
setAttributes(String) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the range of attributes to output.
setAttributes(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Set the list of attributes to consider for replacing missing values
setAttributeSelectionMethod(SelectedTag) - Method in class weka.classifiers.functions.LinearRegression: Sets the method used to select attributes for use in the linear regression.
setAttributeSpecs(List<AddUserFields.AttributeSpec>) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Set the list of attribute specs to use to create the new attributes.
setAttributesToOperateOn(String) - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Set the attributes to operate on
setAttributeType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.Add: Sets the type of attribute to generate.
setAttributeType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RemoveType: Sets the attribute type to be deleted by the filter.
setAttributeWeight(Attribute, double) - Method in class weka.core.Instances: Sets the weight of an attribute.
setAttributeWeight(int, double) - Method in class weka.core.Instances: Sets the weight of an attribute.
setAttributeWeight() - Method in class weka.gui.arffviewer.ArffPanel: sets the weight for the current attribute
setAttributeWeightAt(int, double) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets the weight of the attribute at the given col index
setAttributeWeightAt(int, double) - Method in class weka.gui.arffviewer.ArffTableModel: set the attribute weight at the given col index
setAttrIndexRange(String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets which attributes are used in the cluster.
setAttsToApplyTo(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Set the attributes to apply the rule to
setAttsToApplyTo(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Set the attributes to apply the rule to
setAutoBuild(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: This will set whether the network is automatically built or if it is left up to the user.
setAutoKeyGeneration(boolean) - Method in class weka.core.converters.DatabaseSaver: En/Dis-ables the automatic generation of a primary key.
setAverageDocLength(double) - Method in class weka.core.DictionaryBuilder: Set the average document length to use when normalizing
setAvgNumberOfItemsPerTA(Double) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the avgNumberOfItemsPerTA property.
setAvgNumberOfItemsPerTransaction(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the avgNumberOfItemsPerTransaction property.
setAvgNumberOfTAsPerTAGroup(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the avgNumberOfTAsPerTAGroup property.
setBackground(Color) - Method in class weka.gui.ResultHistoryPanel: Set the background color for this component and the list
setBackground(Color) - Method in class weka.gui.visualize.BMPWriter: sets the background color to use in creating the BMP.
setBackground(Color) - Method in class weka.gui.visualize.JPEGWriter: sets the background color to use in creating the JPEG.
setBackground(Color) - Method in class weka.gui.visualize.PNGWriter: sets the background color to use in creating the PNG.
setBackground(Color) - Method in class weka.gui.visualize.PostscriptGraphics
setBackgroundColor(Color) - Method in class weka.gui.scripting.SyntaxDocument: Sets the background color.
setBagSizePercent(int) - Method in class weka.classifiers.meta.Bagging: Sets the size of each bag, as a percentage of the training set size.
setBalanceClass(boolean) - Method in class weka.datagenerators.classifiers.classification.Agrawal: Sets whether the class is balanced.
setBallSplitter(BallSplitter) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Sets the ball splitting algorithm to be used by the TopDown constructor.
setBallTreeConstructor(BallTreeConstructor) - Method in class weka.core.neighboursearch.BallTree: Sets the BallTreeConstructor for building the BallTree (default TopDownConstructor).
setBase(double) - Method in class weka.core.neighboursearch.CoverTree: Sets the base to use for expansion constant.
setBaseEvaluation(Evaluation) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: Set the base evaluation object to use.
setBaseExperiment(Experiment) - Method in class weka.experiment.RemoteExperiment: Set the base experiment.
setBaseForSampling(String) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the base for sampling
setBaseline(Baseline) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the baseline property.
setBaselineMethod(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the baselineMethod property.
setBaselineModel(BaselineModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the baselineModel property.
setBaselineScore(Double) - Method in class weka.core.pmml.jaxbbindings.Characteristic: Sets the value of the baselineScore property.
setBaselineScore(Double) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the baselineScore property.
setBaselineStrataVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the baselineStrataVariable property.
setBaseSystemName(String) - Method in class weka.core.packageManagement.PackageManager: Set the name of the main software system for which we manage packages.
setBaseSystemVersion(Object) - Method in class weka.core.packageManagement.PackageManager: Set the current version of the base system for which we manage packages.
setBatchSize(String) - Method in class weka.classifiers.AbstractClassifier: Set the preferred batch size for batch prediction.
setBatchSize(String) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.meta.Bagging: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.meta.FilteredClassifier: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.meta.RandomCommittee: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.meta.RandomSubSpace: Set the batch size to use.
setBatchSize(String) - Method in class weka.classifiers.trees.RandomForest: Set the preferred batch size for batch prediction.
setBatchSize(String) - Method in interface weka.core.BatchPredictor: Set the batch size to use.
setBeanContext(BeanContext) - Method in class weka.gui.beans.AbstractDataSource: Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.CostBenefitAnalysis
setBeanContext(BeanContext) - Method in class weka.gui.beans.DataVisualizer: Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.GraphViewer: Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.Loader: Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.ModelPerformanceChart: Set a bean context for this bean
setBeanContext(BeanContext) - Method in class weka.gui.beans.TextViewer: Set a bean context for this bean
setBeanInstances(Vector<Object>, JComponent, Integer...) - Static method in class weka.gui.beans.BeanInstance: Adds the supplied collection of beans at the supplied index in the list of collections.
setBestFit(TIMESERIESALGORITHM) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Sets the value of the bestFit property.
setBeta(double) - Method in class weka.core.pmml.jaxbbindings.PCell: Sets the value of the beta property.
setBias(double) - Method in class weka.classifiers.functions.SGDText
setBias(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron: Sets the value of the bias property.
setBiasToUniformClass(double) - Method in class weka.filters.supervised.instance.Resample: Sets the bias towards a uniform class.
setBIC(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the bic property.
setBIFFile(String) - Method in class weka.classifiers.bayes.BayesNet: Set name of network in BIF file to compare with
setBIFFile(String) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Set name of network in BIF file to read structure from
setBinarizeNumericAttributes(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval: Binarize numeric attributes.
setBinaryAttributesNominal(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary: Sets if binary attributes are to be treates as nominal ones.
setBinaryAttributesNominal(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Sets if binary attributes are to be treates as nominal ones.
setBinarySimilarity(BinarySimilarity) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the binarySimilarity property.
setBinarySplits(boolean) - Method in class weka.classifiers.rules.PART: Set the value of binarySplits.
setBinarySplits(boolean) - Method in class weka.classifiers.trees.J48: Set the value of binarySplits.
setBinRangePrecision(int) - Method in class weka.filters.supervised.attribute.Discretize: Set the precision for bin boundaries.
setBinRangePrecision(int) - Method in class weka.filters.unsupervised.attribute.Discretize: Set the precision for bin boundaries.
setBins(int) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets the number of bins to divide each selected numeric attribute into
setBins(int) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Ignored
setBinValue(String) - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin: Sets the value of the binValue property.
setBlendFactor(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Set the blending factor
setBlendMethod(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Set the blending method
setBlockEnd(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the string that is the end of a block.
setBlockOnLastFold(boolean) - Method in class weka.gui.beans.Classifier: Set whether to block on receiving the last fold of the last run rather than rejecting any further data until all processing is complete.
setBlockStart(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the string that is the start of a block.
setBold(boolean) - Method in class weka.gui.CloseableTabTitle: Set a bold look for the tab
setBoolean(String, boolean) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer: Sets the value of a boolean variable
setBooleanCols(Range) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Sets which attributes are boolean.
setBooleanIndices(String) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Sets which attributes are boolean
setBooleanOperator(String) - Method in class weka.core.pmml.jaxbbindings.CompoundPredicate: Sets the value of the booleanOperator property.
setBooleanOperator(String) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Sets the value of the booleanOperator property.
setBoundaryValueMeans(BoundaryValueMeans) - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Sets the value of the boundaryValueMeans property.
setBoundaryValues(BoundaryValues) - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Sets the value of the boundaryValues property.
setBoundaryValues(BoundaryValues) - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Sets the value of the boundaryValues property.
setBreakTiesRandomly(boolean) - Method in class weka.classifiers.trees.RandomForest: Set whether to break ties randomly.
setBreakTiesRandomly(boolean) - Method in class weka.classifiers.trees.RandomTree: Set whether to break ties randomly.
setBuffer(StringBuffer) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the buffer to use.
setBufferSize(int) - Method in class weka.core.converters.CSVLoader: Set the buffer size to use - i.e.
setBufferSize(String) - Method in class weka.gui.beans.Sorter: Set the size of the in-memory buffer
setBufferSize(String) - Method in class weka.knowledgeflow.steps.Sorter: Set the size of the in-memory buffer
setBuildCalibrationModels(boolean) - Method in class weka.classifiers.functions.SMO: Set the value of buildCalibrationModels.
setBuildRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.M5Base: Set the value of regressionTree.
setBusinessProblem(String) - Method in class weka.core.pmml.jaxbbindings.Decisions: Sets the value of the businessProblem property.
setButtonEnabled(boolean) - Method in class weka.gui.CloseableTabTitle: Enable/disable the close widget
setC(double) - Method in class weka.classifiers.functions.SMO: Set the value of C.
setC(double) - Method in class weka.classifiers.functions.SMOreg: Set the value of C.
setC00Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the c00Parameter property.
setC01Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the c01Parameter property.
setC10Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the c10Parameter property.
setC11Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the c11Parameter property.
setCacheKeyName(String) - Method in class weka.experiment.DatabaseResultListener: Set the value of CacheKeyName.
setCacheSize(int) - Method in class weka.classifiers.functions.supportVector.CachedKernel: Sets the size of the cache to use (a prime number)
setCacheSize(int) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets the size of the cache to use (a prime number)
setCalcOutOfBag(boolean) - Method in class weka.classifiers.meta.Bagging: Set whether the out of bag error is calculated.
setCalculateStdDevs(boolean) - Method in class weka.experiment.AveragingResultProducer: Set the value of CalculateStdDevs.
setCalibrator(Classifier) - Method in class weka.classifiers.functions.SMO: sets the calibrator to use
setCanChangeClassInDialog(boolean) - Method in class weka.gui.GenericObjectEditor: Sets whether the user can change the class in the dialog.
setCanopies(Instances) - Method in class weka.clusterers.Canopy: Set the canopies to use (replaces any learned by this clusterer already)
setCanopyMaxNumCanopiesToHoldInMemory(int) - Method in class weka.clusterers.SimpleKMeans: Set the maximum number of candidate canopies to retain in memory during training.
setCanopyMinimumCanopyDensity(double) - Method in class weka.clusterers.SimpleKMeans: Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.
setCanopyPeriodicPruningRate(int) - Method in class weka.clusterers.SimpleKMeans: Set the how often to prune low density canopies during training (if using canopy clustering)
setCanopyT1(double) - Method in class weka.clusterers.SimpleKMeans: Set the t1 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
setCanopyT2(double) - Method in class weka.clusterers.SimpleKMeans: Set the t2 radius to use when canopy clustering is being used as start points and/or to reduce the number of distance calcs
setCapabilities(Capabilities) - Method in class weka.core.FindWithCapabilities: Uses the given Capabilities for the search.
setCapabilities(Capabilities) - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: sets the initial capabilities.
setCapabilitiesFilter(Capabilities) - Method in class weka.gui.ConverterFileChooser: sets the capabilities that the savers must have.
setCapabilitiesFilter(Capabilities) - Method in class weka.gui.GenericObjectEditor: Sets the capabilities to use for filtering.
setCapacity(int) - Method in class weka.core.FastVector: Deprecated.

Sets the vector's capacity to the given value.
setCapacity(int) - Method in class weka.core.matrix.DoubleVector: Sets the capacity of the vector
setCapacity(int) - Method in class weka.core.matrix.IntVector: Sets the capacity of the vector
setCar(boolean) - Method in class weka.associations.Apriori: Sets class association rule mining
setCardinality(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Counts: Sets the value of the cardinality property.
setCardinality(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Sets the cardinality of the attributes (incl class attribute)
setCaseSensitive(boolean) - Method in class weka.gui.scripting.SyntaxDocument: Sets whether the keywords are case-sensitive or not.
setCastInteger(String) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the castInteger property.
setCategoricalScoringMethod(CATSCORINGMETHOD) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the categoricalScoringMethod property.
setCategories(Categories) - Method in class weka.core.pmml.jaxbbindings.Predictor: Sets the value of the categories property.
setCategory(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the category property.
setCell(int, int, Object) - Method in class weka.classifiers.CostMatrix: Set the value of a particular cell in the matrix
setCenter(double) - Method in class weka.gui.treevisualizer.Node: Set the value of center.
setCenterData(boolean) - Method in class weka.attributeSelection.PrincipalComponents: Set whether to center (rather than standardize) the data.
setCenterData(boolean) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Set whether to center (rather than standardize) the data.
setCenteredLocation() - Method in class weka.gui.arffviewer.ArffViewer: positions the window at the center of the screen
setChanged(boolean) - Method in class weka.gui.arffviewer.ArffPanel: can only reset the changed state to FALSE
setChar(Character) - Method in class weka.core.Trie.TrieNode: sets the character this node represents
setCharSet(String) - Method in class weka.core.converters.TextDirectoryLoader: Set the character set to use when reading text files (an empty string indicates that the default character set will be used).
setChartingEvalWindowSize(int) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Set whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).
setChartingEvalWindowSize(int) - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Set whether to compute evaluation for charting over a fixed sized window of the most recent instances (rather than the whole stream).
setChebychev(Chebychev) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the chebychev property.
setChecked(int, boolean) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: sets the checked state of the element at the given index
setChecked(int, boolean) - Method in class weka.gui.CheckBoxList: sets the checked state of the element at the given index
setCheckErrorRate(boolean) - Method in class weka.classifiers.rules.JRip: Sets whether to check for error rate is in stopping criterion
setChecksTurnedOff(boolean) - Method in class weka.classifiers.functions.SMO: Disables or enables the checks (which could be time-consuming).
setChecksTurnedOff(boolean) - Method in class weka.classifiers.functions.supportVector.Kernel: These methods remain for backwards compatibility.
setChecksTurnedOff(boolean) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Disables or enables the checks (which could be time-consuming).
setChild(String, HNode) - Method in class weka.classifiers.trees.ht.SplitNode: Add a child
setChildField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the childField property.
setChiSquareValue(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the chiSquareValue property.
setCindex(int, double, double) - Method in class weka.gui.visualize.AttributePanel: Set the index of the attribute by which to colour the data.
setCindex(int) - Method in class weka.gui.visualize.AttributePanel: Set the index of the attribute by which to colour the data.
setCindex(int) - Method in class weka.gui.visualize.ClassPanel: Set the index of the attribute to display coloured labels for
setCindex(int) - Method in class weka.gui.visualize.Plot2D: Set the index of the attribute to use for colouring
setCindex(int) - Method in class weka.gui.visualize.PlotData2D: Set the colouring index of the data
setCityBlock(CityBlock) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the cityBlock property.
setClass(Attribute) - Method in class weka.core.Instances: Sets the class attribute.
setClassColumn(String) - Method in class weka.gui.beans.ClassAssigner
setClassColumn(String) - Method in class weka.knowledgeflow.steps.ClassAssigner: Set the class column to use
setClassFlag(boolean) - Method in class weka.datagenerators.ClusterGenerator: Sets the class flag, if class flag is set, the cluster is listed as class atrribute in an extra attribute.
setClassForIRStatistics(int) - Method in class weka.experiment.ClassifierSplitEvaluator: Set the value of ClassForIRStatistics.
setClassificationMethod(SVMCLASSIFICATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the classificationMethod property.
setClassifier(Classifier) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the classifier to use for accuracy estimation
setClassifier(Classifier) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set the classifier to use for accuracy estimation
setClassifier(Classifier) - Method in class weka.attributeSelection.WrapperSubsetEval: Set the classifier to use for accuracy estimation
setClassifier(Classifier) - Method in class weka.classifiers.BVDecompose: Set the classifiers being analysed
setClassifier(Classifier) - Method in class weka.classifiers.BVDecomposeSegCVSub: Set the classifiers being analysed
setClassifier(Classifier) - Method in class weka.classifiers.CheckClassifier: Set the classifier for boosting.
setClassifier(Classifier) - Method in class weka.classifiers.CheckSource: Sets the classifier to use for the comparison.
setClassifier(Classifier) - Method in class weka.classifiers.SingleClassifierEnhancer: Set the base learner.
setClassifier(Classifier) - Method in class weka.classifiers.trees.RandomForest: This method only accepts RandomTree arguments.
setClassifier(Classifier) - Method in class weka.experiment.ClassifierSplitEvaluator: Sets the classifier.
setClassifier(Classifier) - Method in class weka.experiment.RegressionSplitEvaluator: Sets the classifier.
setClassifier(Classifier) - Method in class weka.filters.supervised.attribute.AddClassification: Sets the classifier to classify instances with.
setClassifier(Classifier) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the classifier to classify instances with.
setClassifier(Classifier) - Method in class weka.gui.beans.BatchClassifierEvent: Set the classifier
setClassifier(Classifier) - Method in class weka.gui.beans.IncrementalClassifierEvent
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the classifier to use.
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Set a classifier to use
setClassifier(Classifier) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the classifier to use
setClassifier(Classifier) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Sets the classifier used for making the predictions.
setClassifier(Classifier) - Method in class weka.knowledgeflow.steps.Classifier: Set the classifier to train
setClassifierName(String) - Method in class weka.experiment.ClassifierSplitEvaluator: Set the Classifier to use, given it's class name.
setClassifierName(String) - Method in class weka.experiment.RegressionSplitEvaluator: Set the Classifier to use, given it's class name.
setClassifierPanel(ClassifierPanel) - Method in interface weka.gui.explorer.ClassifierPanelLaunchHandlerPlugin: Allows the classifier panel to pass in a reference to itself
setClassifiers(Classifier[]) - Method in class weka.classifiers.meta.MultiScheme: Sets the list of possible classifers to choose from.
setClassifiers(Classifier[]) - Method in class weka.classifiers.MultipleClassifiersCombiner: Sets the list of possible classifers to choose from.
setClassifierTemplate(Classifier) - Method in class weka.gui.beans.Classifier: Set the template classifier for this wrapper
setClassifyIterations(int) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets the number of times an instance is classified
setClassIndex(int) - Method in class weka.associations.Apriori: Sets the class index
setClassIndex(int) - Method in interface weka.associations.CARuleMiner: Sets the class index for the class association rule miner
setClassIndex(int) - Method in class weka.associations.FilteredAssociator: Sets the class index
setClassIndex(int) - Method in class weka.classifiers.BVDecompose: Sets index of attribute to discretize on
setClassIndex(int) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets index of attribute to discretize on
setClassIndex(int) - Method in class weka.classifiers.CheckSource: Sets the class index of the dataset.
setClassIndex(String) - Method in class weka.core.converters.JSONSaver: Sets index of the class attribute.
setClassIndex(String) - Method in class weka.core.converters.LibSVMSaver: Sets index of the class attribute.
setClassIndex(String) - Method in class weka.core.converters.SVMLightSaver: Sets index of the class attribute.
setClassIndex(String) - Method in class weka.core.converters.XRFFSaver: Sets index of the class attribute.
setClassIndex(String) - Method in class weka.core.FindWithCapabilities: sets the class index, -1 for none, first and last are also valid.
setClassIndex(int) - Method in class weka.core.Instances: Sets the class index of the set.
setClassIndex(int) - Method in class weka.core.TestInstances: sets the class index (0-based)
setClassIndex(int) - Method in class weka.filters.CheckSource: Sets the class index of the dataset.
setClassIndex(String) - Method in class weka.filters.unsupervised.attribute.ClassAssigner: sets the class index.
setClassIndex(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the attribute on which misclassifications are based.
setClassIndex(int) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Sets the 0-based class index.
setClassLabels(ClassLabels) - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix: Sets the value of the classLabels property.
setClassMissing() - Method in class weka.core.AbstractInstance: Sets the class value of an instance to be "missing".
setClassMissing() - Method in interface weka.core.Instance: Sets the class value of an instance to be "missing".
setClassname(String) - Method in class weka.core.AllJavadoc: sets the classname of the class to generate the Javadoc for
setClassname(String) - Method in class weka.core.Javadoc: sets the classname of the class to generate the Javadoc for
setClassname(String) - Method in class weka.core.ListOptions: sets the classname of the class to generate the Javadoc for
setClassName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Sets the class containing the transformation method.
setClassOrder(int) - Method in class weka.filters.supervised.attribute.ClassOrder: Set the wanted class order
setClassType(int) - Method in class weka.core.TestInstances: sets the class attribute type
setClassType(Class<?>) - Method in class weka.gui.GenericObjectEditor: Sets the class of values that can be edited.
setClassValue(double) - Method in class weka.core.AbstractInstance: Sets the class value of an instance to the given value (internal floating-point format).
setClassValue(String) - Method in class weka.core.AbstractInstance: Sets the class value of an instance to the given value.
setClassValue(double) - Method in interface weka.core.Instance: Sets the class value of an instance to the given value (internal floating-point format).
setClassValue(String) - Method in interface weka.core.Instance: Sets the class value of an instance to the given value.
setClassValue(String) - Method in class weka.gui.beans.ClassValuePicker: Set the class value considered to be the "positive" class value.
setClassValue(String) - Method in class weka.knowledgeflow.steps.ClassValuePicker: Set the class value considered to be the "positive" class value.
setClassValueIndex(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the class value index to use
setClearEachDataset(boolean) - Method in class weka.gui.streams.InstanceViewer
setClip(int, int, int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
setClip(Shape) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
setCloseTo(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the "close to" number.
setCloseToDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the "close to" default.
setCloseToTolerance(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the "close to" Tolerance.
setClosure(String) - Method in class weka.core.pmml.jaxbbindings.Interval: Sets the value of the closure property.
setClusterCanopyAssignments(List<long[]>) - Method in class weka.clusterers.Canopy: Set the canopies that each canopy (cluster center) is within T1 distance of
setClusterDefinitions(ClusterDefinition[]) - Method in class weka.datagenerators.clusterers.SubspaceCluster: sets the clusters to use
setClusterer(Clusterer) - Method in class weka.attributeSelection.UnsupervisedSubsetEvaluator: Set the clusterer to use
setClusterer(Clusterer) - Method in class weka.clusterers.CheckClusterer: Set the clusterer for testing.
setClusterer(Clusterer) - Method in class weka.clusterers.ClusterEvaluation: set the clusterer
setClusterer(Clusterer) - Method in class weka.clusterers.MakeDensityBasedClusterer: Sets the clusterer to wrap.
setClusterer(Clusterer) - Method in class weka.clusterers.SingleClustererEnhancer: Set the base clusterer.
setClusterer(DensityBasedClusterer) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Sets the clusterer.
setClusterer(Clusterer) - Method in class weka.filters.unsupervised.attribute.AddCluster: Sets the clusterer to assign clusters with.
setClusterer(Clusterer) - Method in class weka.gui.beans.Clusterer: Set the clusterer for this wrapper
setClusterer(Clusterer) - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: Sets the classifier used for making the predictions.
setClusterer(Clusterer) - Method in class weka.knowledgeflow.steps.Clusterer: Set the clusterer to train
setClustererName(String) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Set the Clusterer to use, given it's class name.
setClustererPanel(ClustererPanel) - Method in interface weka.gui.explorer.ClustererPanelLaunchHandlerPlugin: Allows the clusterer panel to pass in a reference to itself
setClusterEvaluation(ClusterEvaluation) - Method in class weka.gui.explorer.ClustererAssignmentsPlotInstances: Sets the cluster evaluation object to use.
setClusteringModel(ClusteringModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the clusteringModel property.
setClusterSubType(SelectedTag) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the cluster sub type.
setClusterType(SelectedTag) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the cluster type.
setCoef0(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Sets the value of the coef0 property.
setCoef0(Double) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Sets the value of the coef0 property.
setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Sets the value of the coefficient property.
setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Sets the value of the coefficient property.
setCoefficient(double) - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Sets the value of the coefficient property.
setCoefficients(Coefficients) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Sets the value of the coefficients property.
setCol(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MatCell: Sets the value of the col property.
setColHidden(int, boolean) - Method in class weka.experiment.ResultMatrix: sets the hidden status of the column (if the index is valid).
setCollapseTree(boolean) - Method in class weka.classifiers.trees.J48: Set the value of collapseTree.
setCollectPredictionsForVisAndAUC(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
setColName(int, String) - Method in class weka.experiment.ResultMatrix: sets the name of the column (if the index is valid).
setColNameWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the column names (0 = optimal).
setColor(Color) - Method in class weka.gui.treevisualizer.Node: Set the value of color.
setColor(Color) - Method in class weka.gui.visualize.PostscriptGraphics: Set current pen color.
setColOrder(int[]) - Method in class weka.experiment.ResultMatrix: sets the ordering of the columns, null means default.
setColoringIndex(int) - Method in class weka.gui.AttributeVisualizationPanel: Set the coloring (class) index for the plot
setColoringIndex(int) - Method in class weka.gui.beans.AttributeSummarizer: Set the coloring index for the attribute summary plots
setColors(ArrayList<Color>) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set a vector of Color objects for the classes
setColourIndex(int, boolean) - Method in class weka.gui.visualize.VisualizePanel: Set the index for colouring.
setColourIndex(int) - Method in class weka.gui.visualize.VisualizePanel: Sets the index used for colouring.
setColours(ArrayList<Color>) - Method in class weka.gui.visualize.AttributePanel: Sets a list of colours to use for colouring data points
setColours(ArrayList<Color>) - Method in class weka.gui.visualize.ClassPanel: Set a list of colours to use for colouring labels
setColours(ArrayList<Color>) - Method in class weka.gui.visualize.Plot2D: Set a list of colours to use when colouring points according to class values or cluster numbers
setColumn(int, double[]) - Method in class weka.core.Matrix: Deprecated.

Sets a column of the matrix to the given column.
setColumn(String) - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair: Sets the value of the column property.
setColumn(String) - Method in class weka.core.pmml.jaxbbindings.InstanceField: Sets the value of the column property.
setColumn(String) - Method in class weka.core.pmml.jaxbbindings.VerificationField: Sets the value of the column property.
setCombinationRule(SelectedTag) - Method in class weka.classifiers.meta.Vote: Sets the combination rule to use.
setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the compareFunction property.
setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the compareFunction property.
setCompareFunction(COMPAREFUNCTION) - Method in class weka.core.pmml.jaxbbindings.KNNInput: Sets the value of the compareFunction property.
setComparisons(Comparisons) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the comparisons property.
setComponent(JComponent) - Method in class weka.gui.visualize.JComponentWriter: sets the component to print to an output format
setComposite(Composite) - Method in class weka.gui.visualize.PostscriptGraphics
setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the compoundPredicate property.
setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Sets the value of the compoundPredicate property.
setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the compoundPredicate property.
setCompoundPredicate(CompoundPredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the compoundPredicate property.
setCompressOutput(boolean) - Method in class weka.core.converters.ArffSaver: Sets whether to compress the output.
setCompressOutput(boolean) - Method in class weka.core.converters.JSONSaver: Sets whether to compress the output.
setCompressOutput(boolean) - Method in class weka.core.converters.XRFFSaver: Sets whether to compress the output.
setComputeAttributeImportance(boolean) - Method in class weka.classifiers.trees.RandomForest: Set whether to compute and output attribute importance scores
setComputeImpurityDecreases(boolean) - Method in class weka.classifiers.trees.RandomTree: Set whether to compute/store impurity decreases for variable importance in RandomForest
setComputeMaxRowsInParallel(int) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the maximum number of threads to use when computing image rows
setConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the confidence property.
setConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Sets the value of the confidence property.
setConfidence(double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the confidence property.
setConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the confidence property.
setConfidenceFactor(float) - Method in class weka.classifiers.rules.PART: Set the value of CF.
setConfidenceFactor(float) - Method in class weka.classifiers.trees.J48: Set the value of CF.
setConfidenceLevel(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the confidenceLevel property.
setConfidenceLowerBound(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the confidenceLowerBound property.
setConfidenceUpperBound(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the confidenceUpperBound property.
setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewer: whether to present a MessageBox on Exit or not
setConfirmExit(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: whether to present a MessageBox on Exit or not
setConfusionMatrix(ConfusionMatrix) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the confusionMatrix property.
setConnectionName(String) - Method in class weka.knowledgeflow.Data: Set the connection name for this Data object
setConnections(Vector<BeanConnection>, Integer...) - Static method in class weka.gui.beans.BeanConnection: Describe setConnections method here.
setConnectPoints(boolean[]) - Method in class weka.gui.visualize.PlotData2D: Set whether consecutive points should be connected by lines
setConnectPoints(ArrayList<Boolean>) - Method in class weka.gui.visualize.PlotData2D: Set whether consecutive points should be connected by lines
setConsequent(double) - Method in class weka.classifiers.rules.JRip.RipperRule: Sets the internal representation of the class label to be predicted
setConsequent(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the consequent property.
setConservativeForwardSelection(boolean) - Method in class weka.attributeSelection.GreedyStepwise: Set whether attributes should continue to be added during a forward search as long as merit does not decrease
setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the constant property.
setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the constant property.
setConstant(Constant) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the constant property.
setConsumeNonMatching(boolean) - Method in class weka.gui.beans.SubstringLabeler: Set whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.
setConsumeNonMatching(boolean) - Method in class weka.gui.beans.SubstringLabelerRules: Set whether to consume non matching instances.
setConsumeNonMatching(boolean) - Method in class weka.knowledgeflow.steps.SubstringLabeler: Set whether instances that do not match any of the rules should be "consumed" rather than output with a missing value set for the new attribute.
setContainChildBalls(boolean) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets whether if a parent ball should completely enclose its two child balls.
setContent(String) - Method in class weka.core.pmml.jaxbbindings.ArrayType: Sets the value of the content property.
setContent(String) - Method in class weka.gui.scripting.Script: Sets the content.
setContentType(String) - Method in class weka.gui.DocumentPrinting: Sets the content type.
setContinuousScoringMethod(CONTSCORINGMETHOD) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the continuousScoringMethod property.
setContrastMatrixType(String) - Method in class weka.core.pmml.jaxbbindings.Predictor: Sets the value of the contrastMatrixType property.
setContStats(ContStats) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the contStats property.
setConvertNominal(boolean) - Method in class weka.classifiers.trees.LMT: Set the value of convertNominal.
setCoord1(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Sets the value of the coord1 property.
setCoord2(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Sets the value of the coord2 property.
setCoord3(Float) - Method in class weka.core.pmml.jaxbbindings.KohonenMap: Sets the value of the coord3 property.
setCopyright(String) - Method in class weka.core.pmml.jaxbbindings.Header: Sets the value of the copyright property.
setCoreConvertersOnly(boolean) - Method in class weka.gui.ConverterFileChooser: Whether to display only the hardocded core converters.
setCorrelationFields(CorrelationFields) - Method in class weka.core.pmml.jaxbbindings.Correlations: Sets the value of the correlationFields property.
setCorrelationMethods(CorrelationMethods) - Method in class weka.core.pmml.jaxbbindings.Correlations: Sets the value of the correlationMethods property.
setCorrelations(Correlations) - Method in class weka.core.pmml.jaxbbindings.ModelExplanation: Sets the value of the correlations property.
setCorrelationValues(CorrelationValues) - Method in class weka.core.pmml.jaxbbindings.Correlations: Sets the value of the correlationValues property.
setCostMatrix(CostMatrix) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Sets the misclassification cost matrix.
setCostMatrixSource(SelectedTag) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Sets the source location of the cost matrix.
setCostMatrixString(String) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Set the cost matrix to use as a string
setCount(double) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Sets the value of the count property.
setCount(double) - Method in class weka.core.pmml.jaxbbindings.TargetValueCount: Sets the value of the count property.
setCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeException: Sets the value of the count property.
setCount(int, double) - Method in class weka.experiment.ResultMatrix: sets the count for the row (if the index is valid).
setCounter(int) - Method in class weka.associations.ItemSet: Sets the counter
setCounts(Counts) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Sets the value of the counts property.
setCounts(Counts) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the counts property.
setCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the countTable property.
setCountWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the counts (0 = optimal).
setCovariances(Covariances) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the covariances property.
setCreatorApplication(Document) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Set the name of the application (if specified) that created this model
setCreatorApplication(Document) - Method in interface weka.core.pmml.PMMLModel: Set the name of the application (if specified) that created this.
setCriterion(String) - Method in class weka.core.pmml.jaxbbindings.RuleSelectionMethod: Sets the value of the criterion property.
setCrossVal(int) - Method in class weka.classifiers.rules.DecisionTable: Sets the number of folds for cross validation (1 = leave one out)
setCrossValidate(boolean) - Method in class weka.classifiers.lazy.IBk: Sets whether hold-one-out cross-validation will be used to select the best k value.
setCumHazard(double) - Method in class weka.core.pmml.jaxbbindings.BaselineCell: Sets the value of the cumHazard property.
setCumulativeLink(CUMULATIVELINKFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the cumulativeLink property.
setCurrentDirectory(String) - Method in class weka.gui.FileEnvironmentField
setCurrentDirectory(File) - Method in class weka.gui.FileEnvironmentField
setCurrentFilename(String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the filename of the current tab
setCurrentInstance(Instance) - Method in class weka.gui.beans.IncrementalClassifierEvent: Set the current instance for this event
setCurrentTabTitleEditedStatus(boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set the edited status for the current (visible) tab
setCurrentZoomSetting(int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setCurveData(PlotData2D, Attribute) - Method in class weka.gui.beans.CostBenefitAnalysis: Set the threshold curve data to use.
setCustomColour(Color) - Method in class weka.gui.visualize.PlotData2D: Set a custom colour to use for this plot.
setCustomHeight(int) - Method in class weka.gui.visualize.JComponentWriter: sets the custom height to use
setCustomName(String) - Method in class weka.gui.beans.Appender: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Associator: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in interface weka.gui.beans.BeanCommon: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.ClassAssigner: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Classifier: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.ClassValuePicker: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Clusterer: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.CostBenefitAnalysis: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.CrossValidationFoldMaker: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.DataVisualizer: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Filter: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.FlowByExpression
setCustomName(String) - Method in class weka.gui.beans.ImageSaver
setCustomName(String) - Method in class weka.gui.beans.ImageViewer
setCustomName(String) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Join: Set a custom name for this step
setCustomName(String) - Method in class weka.gui.beans.Loader: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.MetaBean: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.PredictionAppender: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Saver: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.SerializedModelSaver: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.Sorter: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.StripChart: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.SubstringLabeler: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.SubstringReplacer: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.TestSetMaker: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.TextSaver
setCustomName(String) - Method in class weka.gui.beans.TextViewer: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.TrainingSetMaker: Set a custom (descriptive) name for this bean
setCustomName(String) - Method in class weka.gui.beans.TrainTestSplitMaker: Set a custom (descriptive) name for this bean
setCustomPropsFile(File) - Method in class weka.core.converters.DatabaseLoader: Sets the custom properties file to use.
setCustomPropsFile(File) - Method in class weka.core.converters.DatabaseSaver: Sets the custom properties file to use.
setCustomPropsFile(File) - Method in class weka.experiment.InstanceQuery: Sets the custom properties file to use.
setCustomWidth(int) - Method in class weka.gui.visualize.JComponentWriter: sets the custom width to use
setCutoff(double) - Method in class weka.clusterers.Cobweb: set the cutoff
setCVisible(boolean) - Method in class weka.gui.treevisualizer.Node: Sets all the children of this node either to visible or invisible
setCVParameters(Object[]) - Method in class weka.classifiers.meta.CVParameterSelection: Set method for CVParameters.
setCVType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: set cross validation strategy to be used in searching for networks.
setD00Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the d00Parameter property.
setD01Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the d01Parameter property.
setD10Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the d10Parameter property.
setD11Parameter(double) - Method in class weka.core.pmml.jaxbbindings.BinarySimilarity: Sets the value of the d11Parameter property.
setData(Instances) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Assuming a network structure is defined and we want to learn from data, the data set must be put if correct order first and possibly discretized/missing values filled in before proceeding to CPT learning.
setData(Instances) - Method in class weka.classifiers.rules.RuleStats: Set the data of the stats, overwriting the old one if any
setData(String) - Method in class weka.knowledgeflow.steps.DataGrid: Set the data to be output by this DataGrid in textual ARFF format.
setDatabaseURL(String) - Method in class weka.experiment.DatabaseUtils: Set the value of DatabaseURL.
setDataDictionary(DataDictionary) - Method in class weka.core.pmml.jaxbbindings.PMML: Sets the value of the dataDictionary property.
setDataFileName(String) - Method in class weka.classifiers.BVDecompose: Sets the name of the data file used for the decomposition
setDataFileName(String) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets the name of the dataset file.
setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the data generator to use for generating new instances
setDataGenerator(DataGenerator) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the density estimator to use
setDataGenerator(DataGenerator) - Method in class weka.knowledgeflow.steps.DataGenerator: Set the data generator
setDataName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Sets the value of the dataName property.
setDataName(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the dataName property.
setDataPoint(double[]) - Method in class weka.gui.beans.ChartEvent: Set the data point
setDataset(File) - Method in class weka.classifiers.CheckSource: Sets the dataset to use for testing.
setDataset(Instances) - Method in class weka.core.AbstractInstance: Sets the reference to the dataset.
setDataset(Instances) - Method in interface weka.core.Instance: Sets the reference to the dataset.
setDataset(File) - Method in class weka.filters.CheckSource: Sets the dataset to use for testing.
setDataSet(PlotData2D, Attribute) - Method in class weka.gui.CostBenefitAnalysisPanel: Set the threshold data for the panel to use.
setDatasetFormat(Instances) - Method in class weka.datagenerators.DataGenerator: Sets the format of the dataset that is to be generated.
setDatasetKeyColumns(Range) - Method in class weka.experiment.PairedTTester: Set the value of DatasetKeyColumns.
setDatasetKeyColumns(Range) - Method in interface weka.experiment.Tester: Set the value of DatasetKeyColumns.
setDatasetKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setDatasets(DefaultListModel) - Method in class weka.experiment.Experiment: Set the datasets to use in the experiment
setDatasets(DefaultListModel) - Method in class weka.experiment.RemoteExperiment: Set the datasets to use in the experiment
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.Constant: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.Discretize: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.ParameterField: Sets the value of the dataType property.
setDataType(DATATYPE) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the dataType property.
setDataType(int) - Method in class weka.gui.beans.xml.XMLBeans: sets what kind of data is to be read/written
setDataUsage(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the dataUsage property.
setDateAttributes(String) - Method in class weka.core.converters.CSVLoader: Set the attribute range to be forced to type date.
setDateFormat(String) - Method in class weka.core.converters.CSVLoader: Set the format to use for parsing date values.
setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.Add: Set the date format, complying to ISO-8601.
setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Sets the output date format.
setDateFormat(SimpleDateFormat) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Sets the output date format.
setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Sets the output date format.
setDateFormat(SimpleDateFormat) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Sets the output date format.
setDateFormat(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Set the date format to use for parsing the date replacement constant
setDateReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Set the date replacement value
setDB(boolean) - Method in class weka.gui.beans.Loader
setDebug(boolean) - Method in class weka.attributeSelection.CfsSubsetEval: Set whether to output debugging info
setDebug(boolean) - Method in class weka.classifiers.AbstractClassifier: Set debugging mode.
setDebug(boolean) - Method in class weka.classifiers.BVDecompose: Sets debugging mode
setDebug(boolean) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets debugging mode
setDebug(boolean) - Method in class weka.classifiers.functions.Logistic: Sets whether debugging output will be printed.
setDebug(boolean) - Method in class weka.classifiers.functions.supportVector.Kernel: Enables or disables the output of debug information (if the derived kernel supports that)
setDebug(boolean) - Method in class weka.classifiers.meta.MultiScheme: Set debugging mode
setDebug(boolean) - Method in class weka.classifiers.rules.JRip: Sets whether debug information is output to the console
setDebug(boolean) - Method in class weka.classifiers.trees.RandomForest: Set debugging mode.
setDebug(boolean) - Method in class weka.clusterers.AbstractClusterer: Set debugging mode.
setDebug(boolean) - Method in class weka.clusterers.EM: Set debug mode - verbose output
setDebug(boolean) - Method in class weka.core.Check: Set debugging mode
setDebug(boolean) - Method in class weka.core.converters.TextDirectoryLoader: Sets whether to print some debug information.
setDebug(boolean) - Method in class weka.core.Debug.Random: sets whether to print the generated random values or not
setDebug(boolean) - Method in class weka.core.Optimization: Set whether in debug mode
setDebug(boolean) - Method in class weka.core.stopwords.AbstractStopwords: Set debugging mode.
setDebug(boolean) - Method in class weka.datagenerators.DataGenerator: Sets the debug flag.
setDebug(boolean) - Method in class weka.estimators.CheckEstimator: Set debugging mode
setDebug(boolean) - Method in class weka.estimators.Estimator: Set debugging mode.
setDebug(boolean) - Method in class weka.experiment.DatabaseUtils: Sets whether there should be printed some debugging output to stderr or not.
setDebug(boolean) - Method in class weka.filters.Filter: Set debugging mode.
setDebug(boolean) - Method in class weka.filters.unsupervised.attribute.AddExpression: Set debug mode.
setDebug(boolean) - Method in class weka.gui.scripting.ScriptingPanel: Turns on/off debugging mode.
setDebug(boolean) - Method in class weka.gui.SimpleCLIPanel.CommandlineCompletion: sets debug mode on/off.
setDebug(boolean) - Method in class weka.gui.streams.InstanceCounter
setDebug(boolean) - Method in class weka.gui.streams.InstanceJoiner
setDebug(boolean) - Method in class weka.gui.streams.InstanceLoader
setDebug(boolean) - Method in class weka.gui.streams.InstanceSavePanel
setDebug(boolean) - Method in class weka.gui.streams.InstanceTable
setDebug(boolean) - Method in class weka.gui.streams.InstanceViewer
setDebuggingOutput(boolean) - Method in class weka.attributeSelection.GreedyStepwise: Set whether to output debugging info to the console
setDecay(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setDecimals(int) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the number of decimals to round to.
setDecisions(Decisions) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the decisions property.
setDefaultChild(String) - Method in class weka.core.pmml.jaxbbindings.Node: Sets the value of the defaultChild property.
setDefaultConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet: Sets the value of the defaultConfidence property.
setDefaultScore(String) - Method in class weka.core.pmml.jaxbbindings.RuleSet: Sets the value of the defaultScore property.
setDefaultValue(String) - Method in class weka.core.pmml.jaxbbindings.Discretize: Sets the value of the defaultValue property.
setDefaultValue(BigInteger) - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Sets the value of the defaultValue property.
setDefaultValue(String) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the defaultValue property.
setDefaultValue(Double) - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Sets the value of the defaultValue property.
setDefaultValue(Double) - Method in class weka.core.pmml.jaxbbindings.TargetValue: Sets the value of the defaultValue property.
setDefaultValue() - Method in class weka.gui.GenericObjectEditor: Sets the current object to be the default, taken as the first item in the chooser.
setDegree(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Sets the value of the degree property.
setDegreesOfFreedom(double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the degreesOfFreedom property.
setDegreesOfFreedom(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the degreesOfFreedom property.
setDegreesOfFreedom(int) - Method in class weka.experiment.PairedStats: Sets the degrees of freedom (if calibration is required).
setDeleteEmptyBins(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization: Sets whether to delete empty bins.
setDeleteListener(ResultHistoryPanel.RDeleteListener) - Method in class weka.gui.ResultHistoryPanel: Set a listener for deletions from the list
setDelimiter(DELIMITER2) - Method in class weka.core.pmml.jaxbbindings.Delimiter: Sets the value of the delimiter property.
setDelimiters(String) - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Set the value of delimiters.
setDelimiters(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the delimiter characters to use.
setDelta(double) - Method in class weka.associations.Apriori: Set the value of delta.
setDelta(double) - Method in class weka.associations.FPGrowth: Set the value of delta.
setDelta(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Sets the m_fDelta.
setDelta(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Sets the m_fDelta.
setDelta(Double) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the delta property.
setDensityBasedClusterer(DensityBasedClusterer) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Set the clusterer for use in filtering
setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.BayesInput: Sets the value of the derivedField property.
setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.NeuralInput: Sets the value of the derivedField property.
setDerivedField(DerivedField) - Method in class weka.core.pmml.jaxbbindings.NeuralOutput: Sets the value of the derivedField property.
setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setDescendantPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setDescending(boolean) - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Set whether the sort should be descending rather than ascending
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Decision: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Decisions: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.Header: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.LinearKernelType: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType: Sets the value of the description property.
setDescription(String) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Sets the value of the description property.
setDescription(String) - Method in class weka.core.Settings.SettingKey: Set the description (display name) of this setting
setDesign(boolean) - Method in class weka.gui.beans.AttributeSummarizer: Set whether the appearance of this bean should be design or application
setDesiredWeightOfInstancesPerInterval(double) - Method in class weka.filters.unsupervised.attribute.Discretize: Set the DesiredWeightOfInstancesPerInterval value.
setDestination(File) - Method in class weka.core.converters.AbstractFileSaver: Sets the destination file (and directories if necessary).
setDestination(OutputStream) - Method in class weka.core.converters.AbstractFileSaver: Sets the destination output stream.
setDestination(File) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setDestination(OutputStream) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setDestination(OutputStream) - Method in class weka.core.converters.ArffSaver: Sets the destination output stream.
setDestination(String, String, String) - Method in class weka.core.converters.DatabaseSaver: Sets the database url.
setDestination(String) - Method in class weka.core.converters.DatabaseSaver: Sets the database url.
setDestination() - Method in class weka.core.converters.DatabaseSaver: Sets the database url using the DatabaseUtils file.
setDestination(OutputStream) - Method in class weka.core.converters.DictionarySaver
setDestination(OutputStream) - Method in class weka.core.converters.JSONSaver: Sets the destination output stream.
setDestination(File) - Method in interface weka.core.converters.Saver: Resets the Saver object and sets the destination to be the supplied File object.
setDestination(OutputStream) - Method in interface weka.core.converters.Saver: Resets the Saver object and sets the destination to be the supplied InputStream.
setDestination(OutputStream) - Method in class weka.core.converters.SerializedInstancesSaver: Sets the destination output stream.
setDestination(OutputStream) - Method in class weka.core.converters.XRFFSaver: Sets the destination output stream.
setDetectionPerAttribute(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Set whether an Outlier/ExtremeValue attribute pair is generated for each numeric attribute ("true") or just one pair for all numeric attributes together ("false").
setDF(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the df property.
setDf(BigInteger) - Method in class weka.core.pmml.jaxbbindings.PCell: Sets the value of the df property.
setDiagDefault(Double) - Method in class weka.core.pmml.jaxbbindings.Matrix: Sets the value of the diagDefault property.
setDictionaryFile(File) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Set the dictionary file to read from
setDictionaryFileToSaveTo(File) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the dictionary file to save the dictionary to.
setDictionaryIsBinary(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Set whether the dictionary file contains a binary serialized dictionary, rather than a plain text one
setDictionarySource(InputStream) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Set an input stream to load a binary serialized dictionary from, rather than source it from a file
setDictionarySource(Reader) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Set an input reader to load a textual dictionary from, rather than source it from a file
setDir(String) - Method in class weka.core.converters.AbstractFileSaver: Sets the directory where the instances should be stored
setDir(String) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setDir(String) - Method in interface weka.core.converters.Saver: Sets the directory of the output file.
setDir(String) - Method in class weka.core.Javadoc: sets the dir containing the file that is to be updated.
setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractFileSaver: Sets the directory and the file prefix.
setDirAndPrefix(String, String) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setDirAndPrefix(String, String) - Method in interface weka.core.converters.Saver: Sets the file prefix and the directory.
setDirection(SelectedTag) - Method in class weka.attributeSelection.BestFirst: Set the search direction
setDirectory(File) - Method in class weka.core.converters.TextDirectoryLoader: sets the source directory
setDirectory(File) - Method in class weka.gui.beans.SerializedModelSaver: Set the directory that the model(s) will be saved into.
setDiscardPredictions(boolean) - Method in class weka.classifiers.evaluation.Evaluation: Sets whether to discard predictions, ie, not storing them for future reference via predictions() method in order to conserve memory.
setDiscardPredictions(boolean) - Method in class weka.classifiers.Evaluation: Sets whether to discard predictions, ie, not storing them for future reference via predictions() method in order to conserve memory.
setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the discretize property.
setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the discretize property.
setDiscretize(Discretize) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the discretize property.
setDiscrStats(DiscrStats) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the discrStats property.
setDisplayConnectors(boolean) - Method in class weka.gui.beans.BeanVisual: Turn on/off the connector points
setDisplayConnectors(boolean, Color) - Method in class weka.gui.beans.BeanVisual: Turn on/off the connector points
setDisplayConnectors(boolean) - Method in class weka.gui.knowledgeflow.NoteVisual: Turn on/off the connector points
setDisplayConnectors(boolean, Color) - Method in class weka.gui.knowledgeflow.NoteVisual: Turn on/off the connector points
setDisplayConnectors(boolean) - Method in class weka.gui.knowledgeflow.StepVisual: Turn on/off the connector points
setDisplayConnectors(boolean, Color) - Method in class weka.gui.knowledgeflow.StepVisual: Turn on/off the connector points
setDisplayedFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setDisplayedResultsets(int[]) - Method in class weka.experiment.PairedTTester: Sets the indicies of the datasets to display (null means all).
setDisplayedResultsets(int[]) - Method in interface weka.experiment.Tester: Sets the indicies of the datasets to display (null means all).
setDisplayModelInOldFormat(boolean) - Method in class weka.classifiers.bayes.NaiveBayes: Set whether to display model output in the old, original format.
setDisplayModelInOldFormat(boolean) - Method in class weka.clusterers.EM: Set whether to display model output in the old, original format.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the displayName property.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the displayName property.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the displayName property.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the displayName property.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Sets the value of the displayName property.
setDisplayName(String) - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Sets the value of the displayName property.
setDisplayRules(boolean) - Method in class weka.classifiers.rules.DecisionTable: Sets whether rules are to be printed
setDisplayStdDevs(boolean) - Method in class weka.clusterers.SimpleKMeans: Sets whether standard deviations and nominal count.
setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.Decision: Sets the value of the displayValue property.
setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValue: Sets the value of the displayValue property.
setDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.Value: Sets the value of the displayValue property.
setDistance(DistanceFunction) - Method in class weka.core.FilteredDistance: Sets the distance
setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.HierarchicalClusterer
setDistanceFunction(DistanceFunction) - Method in class weka.clusterers.SimpleKMeans: sets the distance function to use for instance comparison.
setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.CoverTree: Sets the distance function to use for nearest neighbour search.
setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.KDTree: sets the distance function to use for nearest neighbour search.
setDistanceFunction(DistanceFunction) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: sets the distance function to use for nearest neighbour search.
setDistanceIsBranchLength(boolean) - Method in class weka.clusterers.HierarchicalClusterer
setDistanceWeighting(SelectedTag) - Method in class weka.classifiers.lazy.IBk: Sets the distance weighting method used.
setDistMult(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the distance multiplier.
setDistParameter(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the distParameter property.
setDistribution(String, double[][]) - Method in class weka.classifiers.bayes.net.EditableBayesNet: specify distribution of a node
setDistribution(int, double[][]) - Method in class weka.classifiers.bayes.net.EditableBayesNet: specify distribution of a node
setDistribution(Distribution) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Sets the distribution associated with model.
setDistribution(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the distribution property.
setDistribution(SelectedTag) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets the distribution to use for calculating the random matrix
setDistributionSpread(double) - Method in class weka.filters.supervised.instance.SpreadSubsample: Sets the value for the distribution spread
setDocType(String) - Method in class weka.core.xml.XMLDocument: sets the DOCTYPE-String to use in the XML output.
setDocument(Document) - Method in class weka.core.xml.XMLDocument: sets the DOM document to use.
setDocument(JTextPane) - Method in class weka.gui.DocumentPrinting: Sets the document from the given JTextPane.
setDocument(String, Document) - Method in class weka.gui.DocumentPrinting: Sets the document and the according content type.
setDocumentNormalization(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Sets the value of the documentNormalization property.
setDoNotCheckCapabilities(boolean) - Method in class weka.associations.AbstractAssociator: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.attributeSelection.ASEvaluation: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.classifiers.AbstractClassifier: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.classifiers.functions.supportVector.Kernel: These methods remain for backwards compatibility.
setDoNotCheckCapabilities(boolean) - Method in class weka.clusterers.AbstractClusterer: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in interface weka.core.CapabilitiesIgnorer: If argument is true, capabilities are not actually checked to improve runtime.
setDoNotCheckCapabilities(boolean) - Method in class weka.core.converters.AbstractSaver: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.core.FindWithCapabilities: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.estimators.Estimator: Set whether not to check capabilities.
setDoNotCheckCapabilities(boolean) - Method in class weka.filters.Filter: Set whether not to check capabilities.
setDoNotCheckForModifiedClassAttribute(boolean) - Method in class weka.classifiers.meta.FilteredClassifier: Use this method to determine whether classifier checks whether class attribute has been modified by filter.
setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.rules.PART: Sets the value of doNotMakeSplitPointActualValue.
setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.trees.J48: Sets the value of doNotMakeSplitPointActualValue.
setDoNotMakeSplitPointActualValue(boolean) - Method in class weka.classifiers.trees.LMT: Sets the value of doNotMakeSplitPointActualValue.
setDoNotOperateOnPerClassBasis(boolean) - Method in class weka.core.converters.DictionarySaver: Set the DoNotOperateOnPerClassBasis value.
setDoNotOperateOnPerClassBasis(boolean) - Method in class weka.core.DictionaryBuilder: Set the DoNotOperateOnPerClassBasis value.
setDoNotOperateOnPerClassBasis(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the DoNotOperateOnPerClassBasis value.
setDoNotPrintModels(boolean) - Method in class weka.classifiers.meta.Vote: Set whether to print the individual ensemble models in the output
setDoNotStandardizeAttributes(boolean) - Method in class weka.classifiers.functions.Logistic: Sets whether not to standardize attributes
setDontFilterAfterFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.
setDontNormalize(boolean) - Method in class weka.classifiers.functions.SGD: Turn normalization off/on.
setDontNormalize(boolean) - Method in class weka.core.NormalizableDistance: Sets whether if the attribute values are to be normalized in distance calculation.
setDontReplaceMissing(boolean) - Method in class weka.classifiers.functions.SGD: Turn global replacement of missing values off/on.
setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.Canopy: Sets whether missing values are to be replaced.
setDontReplaceMissingValues(boolean) - Method in class weka.clusterers.SimpleKMeans: Sets whether missing values are to be replaced.
setDontShowDialog(String) - Static method in class weka.core.Utils: Specify that the named dialog is not to be displayed in the future.
setDontShowDialogResponse(String, String) - Static method in class weka.core.Utils: Specify that the named dialog is not to be shown again in the future.
setDouble(String, double) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer: Sets the value of a double variable
setDynamicArgsField(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the name of the attribute in the incoming instance structure that contains the arguments to the command to execute
setDynamicCmdField(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the name of the attribute in the incoming instance structure that contains the command to execute
setDynamicVarsInternalRep(String) - Method in class weka.knowledgeflow.steps.SetVariables
setDynamicWorkingDirField(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the name of the attribute in the incoming instance structure that containst the working directory for the command to execute
setEditable(boolean) - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Set the editable status of the combo box.
setEditable(boolean) - Method in class weka.gui.EnvironmentField: Set the editable status of the combo box.
setEditable(boolean) - Method in class weka.gui.PasswordField: Set the editable status of the password box.
setEdited(boolean) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the edited status of this flow
setEditedStatus(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setEditedStatus(int, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setElement(int, int, double) - Method in class weka.classifiers.CostMatrix: Set the value of a cell as a double
setElement(int, double) - Method in class weka.core.AlgVector: Sets an element of the matrix to the given value.
setElement(int, int, double) - Method in class weka.core.Matrix: Deprecated.

Sets an element of the matrix to the given value.
setElementAt(E, int) - Method in class weka.core.FastVector: Deprecated.

Sets the element at the given index.
setElementAt(Object, int) - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Sets the component at the specified index of this list to be the specified object.
setElements(double[]) - Method in class weka.core.AlgVector: Sets the elements of the vector to values of the given array.
setEliminateColinearAttributes(boolean) - Method in class weka.classifiers.functions.LinearRegression: Set the value of EliminateColinearAttributes.
setEmpty(String) - Method in class weka.core.TestOptions
setEnabled(boolean) - Method in class weka.core.Debug: sets whether the logging is enabled or not
setEnabled(boolean) - Method in class weka.core.Memory: sets whether the memory management is enabled
setEnabled(boolean) - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Set the enabled status of the combo box.
setEnabled(boolean) - Method in class weka.gui.beans.FileEnvironmentField: Deprecated.

Set the enabled status of the combo box and button
setEnabled(boolean) - Method in class weka.gui.EnvironmentField: Set the enabled status of the combo box.
setEnabled(boolean) - Method in class weka.gui.FileEnvironmentField: Set the enabled status of the combo box and button
setEnabled(boolean) - Method in class weka.gui.GenericObjectEditor: Sets whether the editor is "enabled", meaning that the current values will be painted.
setEnabled(boolean) - Method in class weka.gui.PasswordField: Set the enabled status of the password box
setEnabled(boolean) - Method in class weka.gui.PropertyPanel: Passes on enabled/disabled status to the custom panel (if one is set).
setEnablePerspectiveTab(String, boolean) - Method in class weka.gui.PerspectiveManager: Enable/disable a perspective's button/tab
setEnablePerspectiveTabs(List<String>, boolean) - Method in class weka.gui.PerspectiveManager: Enable/disable the tab/button for each perspective in the supplied list of perspective IDs
setEnclosureCharacters(String) - Method in class weka.core.converters.CSVLoader: Set the character(s) to use/recognize as string enclosures
setEndTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Sets the value of the endTime property.
setEndTimeVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the endTimeVariable property.
setEntropicAutoBlend(boolean) - Method in class weka.classifiers.lazy.KStar: Set whether entropic blending is to be used.
setEnumClass(String) - Method in class weka.core.EnumHelper: Set the fully qualified enum class name
setEnumerateColNames(boolean) - Method in class weka.experiment.ResultMatrix: sets whether the column names are prefixed with "(x)" where "x" is the index.
setEnumerateRowNames(boolean) - Method in class weka.experiment.ResultMatrix: sets whether to the row names are prefixed with the index.
setEnvironment(Environment) - Method in class weka.classifiers.meta.Vote: Set environment variable values to substitute in the paths of serialized models to load
setEnvironment(Environment) - Method in class weka.classifiers.misc.InputMappedClassifier: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.core.converters.AbstractFileLoader: Set the environment variables to use.
setEnvironment(Environment) - Method in class weka.core.converters.AbstractFileSaver: Set the environment variables to use.
setEnvironment(Environment) - Method in class weka.core.converters.DatabaseLoader: Set the environment variables to use.
setEnvironment(Environment) - Method in class weka.core.converters.DatabaseSaver: Set the environment variables to use.
setEnvironment(Environment) - Method in interface weka.core.EnvironmentHandler: Set environment variables to use.
setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Set environment varialbes to use
setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector
setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Set environment to use
setEnvironment(Environment) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
setEnvironment(Environment) - Method in class weka.gui.beans.Associator: Set environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.Classifier: Set environment variables to pass on to the classifier (if if is an EnvironmentHandler)
setEnvironment(Environment) - Method in class weka.gui.beans.ClassifierCustomizer: Set any environment variables to pass to the PropertySheetPanel
setEnvironment(Environment) - Method in class weka.gui.beans.DataVisualizer
setEnvironment(Environment) - Method in class weka.gui.beans.DataVisualizerCustomizer: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Set the environment variables to display in the drop down list.
setEnvironment(Environment) - Method in class weka.gui.beans.FlowByExpression
setEnvironment(Environment) - Method in class weka.gui.beans.FlowByExpressionCustomizer
setEnvironment(Environment) - Method in class weka.gui.beans.FlowRunner: Set the environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.ImageSaver: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.ImageSaverCustomizer: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.Join: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.JoinCustomizer
setEnvironment(Environment) - Method in class weka.gui.beans.KnowledgeFlowApp: Set the environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.Loader: Set environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.LoaderCustomizer
setEnvironment(Environment) - Method in class weka.gui.beans.ModelPerformanceChart
setEnvironment(Environment) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.Saver: Set environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.SaverCustomizer
setEnvironment(Environment) - Method in class weka.gui.beans.SerializedModelSaver: Set environment variables to use.
setEnvironment(Environment) - Method in class weka.gui.beans.SerializedModelSaverCustomizer
setEnvironment(Environment) - Method in class weka.gui.beans.Sorter: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SorterCustomizer: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabeler: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabelerCustomizer: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringLabelerRules
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacer: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacerCustomizer: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.SubstringReplacerRules
setEnvironment(Environment) - Method in class weka.gui.beans.TextSaver: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.beans.TextSaverCustomizer: Set the environment variables to use
setEnvironment(Environment) - Method in class weka.gui.EnvironmentField: Set the environment variables to display in the drop down list.
setEnvironment(Environment) - Method in class weka.gui.filters.AddUserFieldsCustomizer: Set environment variables to use
setEnvironment(Environment) - Method in class weka.gui.knowledgeflow.StepEditorDialog: Set environment variables
setEnvironment(Environment) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the environment variables to use with this layout
setEnvironment(Environment) - Method in class weka.gui.PropertySheetPanel: Set environment variables to pass on to any editor that can use them
setEnvironment(Environment) - Method in class weka.knowledgeflow.FlowRunner
setEnvironmentVariables(Environment) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set environment variables for this execution environment
setEnvironmentVariables(Environment) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set environment variables for this execution environment
setEpochs(int) - Method in class weka.classifiers.functions.SGD: Set the number of epochs to use
setEpochs(int) - Method in class weka.classifiers.functions.SGDText: Set the number of epochs to use
setEpsilon(double) - Method in class weka.classifiers.functions.SGD: Set the epsilon threshold on the error for epsilon insensitive and Huber loss functions
setEpsilon(double) - Method in class weka.classifiers.functions.SMO: Set the value of epsilon.
setEpsilon(double) - Method in class weka.classifiers.functions.supportVector.RegSMO: Set the value of epsilon.
setEpsilonParameter(double) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Set the value of epsilon parameter of the epsilon insensitive loss function.
setError(Exception) - Method in class weka.knowledgeflow.ExecutionResult: Set an exception, in the case that an error occurred during the processing done by a StepTask
setErrorOnProbabilities(boolean) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of errorOnProbabilities.
setErrorOnProbabilities(boolean) - Method in class weka.classifiers.trees.LMT: Set the value of errorOnProbabilities.
setErrorPlotPointSizeProportionalToMargin(boolean) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Set whether the point size on classification error plots should be proportional to the prediction margin.
setErrorPlotPointSizeProportionalToMargin(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Set whether the size of plot data points will be proportional to the prediction margin
setEstimator(BayesNetEstimator) - Method in class weka.classifiers.bayes.BayesNet: Set the Estimator Algorithm used in calculating the CPTs
setEstimator(UnivariateDensityEstimator) - Method in class weka.classifiers.meta.RegressionByDiscretization: Set the estimator
setEstimator(Estimator) - Method in class weka.estimators.CheckEstimator: Set the estimator for boosting.
setEstimator(NaiveBayes) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Set the naive Bayes estimator to use
setEuclidean(Euclidean) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the euclidean property.
setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Sets the distance function used to (or to be used to) build the tree.
setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets the distance function to use to build the tree.
setEuclideanDistanceFunction(EuclideanDistance) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the EuclideanDistance object to use for splitting nodes.
setEvaluateWithRespectToCosts(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Set whether to evaluate with respoect to costs
setEvaluation(Evaluation) - Method in class weka.classifiers.evaluation.EvaluationMetricHelper: Sets the Evaluation object to use
setEvaluation(Evaluation) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Sets the Evaluation object to use.
setEvaluationMeasure(SelectedTag) - Method in class weka.attributeSelection.ClassifierAttributeEval: Sets the performance evaluation measure to use for selecting attributes for the decision table
setEvaluationMeasure(SelectedTag) - Method in class weka.attributeSelection.ClassifierSubsetEval: Sets the performance evaluation measure to use for selecting attributes for the decision table
setEvaluationMeasure(SelectedTag) - Method in class weka.attributeSelection.WrapperSubsetEval: Sets the performance evaluation measure to use for selecting attributes for the decision table
setEvaluationMeasure(SelectedTag) - Method in class weka.classifiers.rules.DecisionTable: Sets the performance evaluation measure to use for selecting attributes for the decision table
setEvaluationMetric(SelectedTag) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the evaluation metric to use
setEvaluationMetricsToOutput(String) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Set the evaluation metrics to output (as a comma-separated list).
setEvaluationMetricsToOutput(String) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator: Set the evaluation metrics to output (as a comma-separated list).
setEvaluator(ASEvaluation) - Method in class weka.attributeSelection.AttributeSelection: set the attribute/subset evaluator
setEvaluator(ASEvaluation) - Method in class weka.attributeSelection.CheckAttributeSelection: Set the evaluator to test.
setEvaluator(ASEvaluation) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Sets the attribute evaluator
setEvaluator(ASEvaluation) - Method in class weka.filters.supervised.attribute.AttributeSelection: set attribute/subset evaluator
setEvaluator(ASEvaluation) - Method in class weka.knowledgeflow.steps.ASEvaluator: Set the evaluator to wrap (just calls setWrappedAlgorithm)
setEvalUsingTrainingData(boolean) - Method in class weka.attributeSelection.OneRAttributeEval: Use the training data to evaluate attributes rather than cross validation
setEvidence(int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: set evidence state of a node.
setEvidence(int, int) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
setEvidence(int, int) - Method in class weka.classifiers.bayes.net.MarginCalculator
setExcludeNominalAttributes(boolean) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Set whether nominal attributes are to be excluded from the transformation
setExcludeNumericAttributes(boolean) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Set whether numeric attributes are being excluded from the transformation
setExecuting(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setExecuting(int, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setExecutionEnvironment(BaseExecutionEnvironment) - Method in interface weka.knowledgeflow.FlowExecutor: Set the execution environment to use
setExecutionEnvironment(BaseExecutionEnvironment) - Method in class weka.knowledgeflow.FlowRunner: Set the execution environment to use
setExecutionSlots(int) - Method in class weka.gui.beans.Classifier: Set the number of execution slots (threads) to use to train models with.
setExecutionSlots(int) - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Set the number of executions slots to use.
setExecutionStatus(int) - Method in class weka.experiment.TaskStatusInfo: Set the execution status of this Task.
setExecutionThread(KnowledgeFlowApp.RunThread) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setExecutionThread(int, KnowledgeFlowApp.RunThread) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setExitIfNoWindowsOpen(boolean) - Static method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Sets whether System.exit gets called when no more windows are open.
setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewer: whether to do a System.exit(0) on close
setExitOnClose(boolean) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: whether to do a System.exit(0) on close
setExpectedResultsPerAverage(int) - Method in class weka.experiment.AveragingResultProducer: Set the value of ExpectedResultsPerAverage.
setExperiment(Experiment) - Method in class weka.experiment.RemoteExperimentSubTask: Set the experiment for this sub task
setExperiment(Experiment) - Method in class weka.gui.experiment.AbstractSetupPanel: Sets the experiment to configure.
setExperiment(Experiment) - Method in class weka.gui.experiment.AlgorithmListPanel: Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.DatasetListPanel: Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.DistributeExperimentPanel: Sets the experiment to be configured.
setExperiment(Experiment) - Method in class weka.gui.experiment.GeneratorPropertyIteratorPanel: Sets the experiment which will have the custom properties edited.
setExperiment(RemoteExperiment) - Method in class weka.gui.experiment.HostListPanel: Tells the panel to act on a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.ResultsPanel: Tells the panel to use a new experiment.
setExperiment(Experiment) - Method in class weka.gui.experiment.RunNumberPanel: Sets the experiment to be configured.
setExperiment(Experiment) - Method in class weka.gui.experiment.RunPanel: Sets the experiment the panel operates on.
setExperiment(Experiment) - Method in class weka.gui.experiment.SetupPanel: Sets the experiment to configure.
setExperiment(Experiment) - Method in class weka.gui.experiment.SimpleSetupPanel: Sets the experiment to configure.
setExplicitPropsFile(boolean) - Method in class weka.gui.GenericPropertiesCreator: if FALSE, the locating of a props-file of the Utils-class is used, otherwise it's tried to load the specified file
setExplorer(Explorer) - Method in class weka.gui.explorer.AssociationsPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorer(Explorer) - Method in class weka.gui.explorer.AttributeSelectionPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorer(Explorer) - Method in class weka.gui.explorer.ClassifierPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data).
setExplorer(Explorer) - Method in class weka.gui.explorer.ClustererPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorer(Explorer) - Method in interface weka.gui.explorer.Explorer.ExplorerPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorer(Explorer) - Method in class weka.gui.explorer.PreprocessPanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExplorer(Explorer) - Method in class weka.gui.explorer.VisualizePanel: Sets the Explorer to use as parent frame (used for sending notifications about changes in the data)
setExponent(double) - Method in class weka.classifiers.functions.supportVector.PolyKernel: Sets the exponent value.
setExponent(double) - Method in class weka.classifiers.functions.VotedPerceptron: Set the value of exponent.
setExponent(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the exponent property.
setExponent(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Sets the value of the exponent property.
setExpression(String) - Method in class weka.datagenerators.classifiers.regression.Expression: Sets the mathematical expression to generate y out of x.
setExpression(String) - Method in class weka.filters.unsupervised.attribute.AddExpression: Set the expression to apply
setExpression(String) - Method in class weka.filters.unsupervised.attribute.MathExpression: Set the expression to apply
setExpression(String) - Method in class weka.filters.unsupervised.attribute.RemoveByName: Sets the regular expression to match the attribute names against.
setExpression(String) - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Sets the expression used for filtering.
setExpressionString(String) - Method in class weka.gui.beans.FlowByExpression: Set the expression (in internal format)
setExpressionString(String) - Method in class weka.knowledgeflow.steps.FlowByExpression: Set the expression (in internal format)
setExtender(String) - Method in class weka.core.pmml.jaxbbindings.Extension: Sets the value of the extender property.
setExtremeValuesAsOutliers(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Set whether extreme values are also tagged as outliers.
setExtremeValuesFactor(double) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Sets the factor for determining the thresholds for extreme values.
setFalse(False) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the false property.
setFalse(False) - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Sets the value of the false property.
setFalse(False) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the false property.
setFalse(False) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the false property.
setFalseNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats: Sets the number of positive instances predicted as negative
setFalsePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats: Sets the number of negative instances predicted as positive
setFalseStepName(String) - Method in class weka.gui.beans.FlowByExpression: Set the name of the connected step to send "false" instances to
setFalseStepName(String) - Method in class weka.knowledgeflow.steps.FlowByExpression: Set the name of the connected step to send "false" instances to
setFastDistanceCalc(boolean) - Method in class weka.clusterers.SimpleKMeans: Sets whether to use faster distance calculation.
setFastRegression(boolean) - Method in class weka.classifiers.trees.LMT: Set the value of fastRegression.
setFeature(RESULTFEATURE) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the feature property.
setFeature(RESULTFEATURE) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the feature property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.Discretize: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldColumnPair: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldRef: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldValue: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.InstanceField: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.KNNInput: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.SimpleSetPredicate: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the field property.
setField(String) - Method in class weka.core.pmml.jaxbbindings.VerificationField: Sets the value of the field property.
setFieldCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Sets the value of the fieldCount property.
setFieldCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the fieldCount property.
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.DerivedFieldMetaInfo: Upadate the field definitions for this derived field
setFieldDefs(Instances) - Method in class weka.core.pmml.DerivedFieldMetaInfo: Upadate the field definitions for this derived field
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Discretize: Set the field definitions for this Expression to use
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Expression: Set the field definitions for this Expression to use
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.FieldRef
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.NormContinuous: Set the field definitions for this Expression to use
setFieldDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.NormDiscrete: Set the field definitions for this Expression to use
setFieldName(String) - Method in class weka.core.pmml.jaxbbindings.BayesInput: Sets the value of the fieldName property.
setFieldName(String) - Method in class weka.core.pmml.jaxbbindings.BayesOutput: Sets the value of the fieldName property.
setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the fieldRef property.
setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the fieldRef property.
setFieldRef(FieldRef) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the fieldRef property.
setFieldSeparator(String) - Method in class weka.core.converters.CSVLoader: Sets the character used as column separator.
setFieldSeparator(String) - Method in class weka.core.converters.CSVSaver: Sets the character used as column separator.
setFieldWeight(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the fieldWeight property.
setFieldWeight(Double) - Method in class weka.core.pmml.jaxbbindings.KNNInput: Sets the value of the fieldWeight property.
setFile(File) - Method in class weka.core.converters.AbstractFileLoader: sets the source File
setFile(File) - Method in class weka.core.converters.AbstractFileSaver: Sets the destination file.
setFile(File) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setFile(File) - Method in class weka.core.converters.ArffLoader: sets the source File
setFile(File) - Method in class weka.core.converters.ArffSaver: Sets the destination file.
setFile(File) - Method in interface weka.core.converters.FileSourcedConverter: Set the file to load from/ to save in
setFile(File) - Method in class weka.core.converters.JSONSaver: Sets the destination file.
setFile(File) - Method in interface weka.core.converters.Saver: Sets the output file
setFile(File) - Method in class weka.core.converters.XRFFSaver: Sets the destination file.
setFile(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument: Sets the value of the file property.
setFile(File) - Method in class weka.gui.visualize.JComponentWriter: sets the file to store the output in
setFile(File) - Method in class weka.knowledgeflow.steps.ImageSaver: Set the file to save to
setFile(File) - Method in class weka.knowledgeflow.steps.TextSaver: Set the file to save to
setFileFilter(FileFilter) - Method in class weka.gui.FileEnvironmentField: Set the file filter to be the selected one in the drop down box
setFileFormat(Tag) - Method in class weka.gui.beans.SerializedModelSaver: Set the file format to use for saving.
setFileMustExist(boolean) - Method in class weka.gui.ConverterFileChooser: Whether the selected file must exst (only open dialog).
setFilename(String) - Method in class weka.core.FindWithCapabilities: Sets the dataset filename to base the capabilities on.
setFilename(String) - Method in class weka.gui.arffviewer.ArffPanel: sets the filename
setFilename(int, String) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the filename of the specified panel
setFilename(String) - Method in class weka.gui.beans.ImageSaver: Set the filename to save to
setFilename(String) - Method in class weka.gui.beans.TextSaver: Set the filename to save to
setFilenamePrefix(String) - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Set the text to prepend to the filename
setFilePath(String) - Method in class weka.core.FileHelper: Set the file path
setFilePath(File) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the file path for the flow being edited by this layout
setFilePrefix(String) - Method in class weka.core.converters.AbstractFileSaver: Sets the file name prefix
setFilePrefix(String) - Method in class weka.core.converters.AbstractSaver: Default implementation throws an IOException.
setFilePrefix(String) - Method in interface weka.core.converters.Saver: Sets the file prefix.
setFillWithMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Sets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).
setFilter(Filter) - Method in class weka.associations.FilteredAssociator: Sets the filter
setFilter(Filter) - Method in class weka.classifiers.meta.FilteredClassifier: Sets the filter
setFilter(Filter) - Method in class weka.clusterers.FilteredClusterer: Sets the filter.
setFilter(Filter) - Method in class weka.core.FilteredDistance: Sets the filter
setFilter(Filter) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Sets the filter
setFilter(Filter) - Method in class weka.filters.CheckSource: Sets the filter to use for the comparison.
setFilter(Filter) - Method in class weka.gui.beans.Filter: Set the filter to be wrapped by this bean
setFilter(Filter) - Method in class weka.knowledgeflow.steps.Filter: Set the filter.
setFilterAfterFirstBatch(boolean) - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Set whether to apply the filter to instances that arrive once the first (training) batch has been seen.
setFilters(Filter[]) - Method in class weka.filters.MultiFilter: Sets the list of possible filters to choose from.
setFilters(Filter[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Sets the list of possible filters to choose from.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.GaussianProcesses: Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMO: Sets how the training data will be transformed.
setFilterType(SelectedTag) - Method in class weka.classifiers.functions.SMOreg: Sets how the training data will be transformed.
setFind(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Sets the regular expression that the attribute names must match.
setFindAllRulesForSupportLevel(boolean) - Method in class weka.associations.FPGrowth: If true then turn off the iterative support reduction method of finding x rules that meet the minimum support and metric thresholds and just return all the rules that meet the lower bound on minimum support and the minimum metric.
setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: Set the value of FindNumBins.
setFindNumBins(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Set the value of FindNumBins.
setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Sets index of the first value used.
setFirstValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues: Sets index of the first value used.
setFlow(Vector<Vector<?>>) - Method in class weka.gui.beans.KnowledgeFlowApp: Set the flow for the KnowledgeFlow to edit.
setFlow(Flow) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the flow to edit in this layout
setFlow(Flow) - Method in interface weka.knowledgeflow.FlowExecutor: Set the flow to be executed
setFlow(Flow) - Method in class weka.knowledgeflow.FlowRunner: Set the flow to execute
setFlowExecutor(FlowExecutor) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the FlowExcecutor to use for executing the flow
setFlowExecutor(FlowExecutor) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set the executor that will actually be responsible for running the flow.
setFlowFile(File) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setFlowFile(int, File) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setFlowFile(File) - Method in class weka.knowledgeflow.steps.Job
setFlowLayoutOperation(VisibleLayout.LayoutOperation) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set the current flow layout operation
setFlowName(String) - Method in class weka.knowledgeflow.Flow: Set the name of this Flow
setFlows(Vector<Object>) - Method in class weka.gui.beans.FlowRunner: Set the vector holding the flows(s) to run
setFocus() - Method in class weka.gui.sql.ConnectionPanel: sets the focus in a designated control.
setFocus() - Method in class weka.gui.sql.InfoPanel: sets the focus in a designated control
setFocus() - Method in class weka.gui.sql.QueryPanel: sets the focus in a designated control.
setFocus() - Method in class weka.gui.sql.ResultPanel: sets the focus in a designated control
setFold(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Selects a fold.
setFold(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Selects a fold.
setFoldColumn(int) - Method in class weka.experiment.PairedTTester: Set the value of FoldColumn.
setFoldColumn(int) - Method in interface weka.experiment.Tester: Set the value of FoldColumn.
setFolds(int) - Method in class weka.attributeSelection.AttributeSelection: set the number of folds for cross validation
setFolds(int) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the number of folds to use for accuracy estimation
setFolds(int) - Method in class weka.attributeSelection.OneRAttributeEval: Set the number of folds to use for cross validation
setFolds(int) - Method in class weka.attributeSelection.WrapperSubsetEval: Set the number of folds to use for accuracy estimation
setFolds(int) - Method in class weka.classifiers.rules.JRip: Sets the number of folds to use
setFolds(int) - Method in class weka.gui.beans.CrossValidationFoldMaker: Set the number of folds for the cross validation
setFont(Font) - Method in class weka.gui.ResultHistoryPanel: Set the font to use in the list
setFont(Font) - Method in class weka.gui.visualize.PostscriptGraphics: Set current font.
setFontName(String) - Method in class weka.core.FontHelper: Set the font name
setFontName(String) - Method in class weka.gui.scripting.SyntaxDocument: sets the current font family (affects all built-in styles).
setFontSize(int) - Method in class weka.core.FontHelper: Set the font size
setFontSize(int) - Method in class weka.gui.scripting.SyntaxDocument: sets the current font size (affects all built-in styles).
setFontSizeAdjust(int) - Method in class weka.gui.beans.Note: set the font size adjustment
setFontSizeAdjust(int) - Method in class weka.gui.knowledgeflow.NoteVisual: set the font size adjustment
setFontStyle(int) - Method in class weka.core.FontHelper: Set the font style (see constants in Font class)
setForceResampleWithWeights(boolean) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Sets the size of each subSpace, as a percentage of the training set size.
setFormat(String) - Method in class weka.core.Debug.Timestamp: sets the format for the timestamp
setFormat(ImageSaver.ImageFormat) - Method in class weka.knowledgeflow.steps.ImageSaver: Set the format of the image to save
setFrom(String) - Method in class weka.core.pmml.jaxbbindings.Con1: Sets the value of the from property.
setFStatistic(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the fStatistic property.
setFStatistic(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the fStatistic property.
setFunction(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate: Sets the value of the function property.
setFunction(String) - Method in class weka.core.pmml.jaxbbindings.Apply: Sets the value of the function property.
setFunction(SelectedTag) - Method in class weka.datagenerators.classifiers.classification.Agrawal: Sets the function for generating the data.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.MiningModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Sets the value of the functionName property.
setFunctionName(MININGFUNCTION) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the functionName property.
setFValue(Double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the fValue property.
setGamma(double) - Method in class weka.classifiers.functions.supportVector.RBFKernel: Sets the gamma value.
setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.PolynomialKernelType: Sets the value of the gamma property.
setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.RadialBasisKernelType: Sets the value of the gamma property.
setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.SigmoidKernelType: Sets the value of the gamma property.
setGamma(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Sets the value of the gamma property.
setGap(GAP) - Method in class weka.core.pmml.jaxbbindings.Delimiter: Sets the value of the gap property.
setGaussianDistribution(GaussianDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate: Sets the value of the gaussianDistribution property.
setGaussianDistribution(GaussianDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the gaussianDistribution property.
setGeneralRegressionModel(GeneralRegressionModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the generalRegressionModel property.
setGenerateRanking(boolean) - Method in class weka.attributeSelection.GreedyStepwise: Records whether the user has requested a ranked list of attributes.
setGenerateRanking(boolean) - Method in interface weka.attributeSelection.RankedOutputSearch: Sets whether or not ranking is to be performed.
setGenerateRanking(boolean) - Method in class weka.attributeSelection.Ranker: This is a dummy set method---Ranker is ONLY capable of producing a ranked list of attributes for attribute evaluators.
setGenerator(DataGenerator) - Method in class weka.gui.explorer.DataGeneratorPanel: sets the generator to use initially
setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the base for computing the number of samples to obtain from each generator.
setGeneratorSamplesBase(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the base for computing the number of samples to obtain from each generator.
setGlobalBlend(int) - Method in class weka.classifiers.lazy.KStar: Set the global blend parameter
setGlobalModel(NBTreeNoSplit) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Set the global naive bayes model for this node
setGlobalTermWeights(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Sets the value of the globalTermWeights property.
setGracePeriod(double) - Method in class weka.classifiers.trees.HoeffdingTree: Set the number of instances (or total weight of instances) a leaf should observe between split attempts
setGraphicalEnvironment(Object) - Method in class weka.gui.knowledgeflow.AbstractGraphicalCommand: Set a reference to the graphical environment
setGraphicalEnvironment(Object) - Method in class weka.gui.knowledgeflow.GetPerspectiveNamesGraphicalCommand: Set the graphical environment
setGraphicalEnvironment(Object) - Method in class weka.gui.knowledgeflow.SendToPerspectiveGraphicalCommand: Set the graphical environment
setGraphicalEnvironmentCommandHandler(GraphicalEnvironmentCommandHandler) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set the environment for performing commands at the application-level in a graphical environment.
setGraphicalEnvironmentCommandHandler(GraphicalEnvironmentCommandHandler) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set the environment for performing commands at the application-level in a graphical environment.
setGridWidth(int) - Method in class weka.gui.beans.AttributeSummarizer: Set the width of the grid of plots
setGroupField(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate: Sets the value of the groupField property.
setGroupIdentifier(long) - Method in class weka.gui.beans.BatchClassifierEvent
setGUI(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: This will set whether A GUI is brought up to allow interaction by the user with the neural network during training.
setGUIType(SelectedTag) - Method in class weka.gui.Main: Sets the type of GUI to use.
setHandler(CapabilitiesHandler) - Method in class weka.core.FindWithCapabilities: sets the Capabilities handler to generate the data for.
setHandler(CapabilitiesHandler) - Method in class weka.core.TestInstances: sets the Capabilities handler to generate the data for
setHandleRightClicks(boolean) - Method in class weka.gui.ResultHistoryPanel: Set whether the result history list should handle right clicks or whether the parent object will handle them.
setHeader(Instances) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the header of the dataset.
setHeader(Header) - Method in class weka.core.pmml.jaxbbindings.PMML: Sets the value of the header property.
setHeadless(boolean) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set whether this execution environment is headless
setHeadless(boolean) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set whether this execution environment is headless
setHeuristicStop(int) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of heuristicStop.
setHeuristicStop(int) - Method in class weka.classifiers.trees.lmt.LogisticBase: Sets the option "heuristicStop".
setHidden(boolean) - Method in class weka.gui.beans.BeanConnection: Make this connection invisible on the display
setHiddenLayers(String) - Method in class weka.classifiers.functions.MultilayerPerceptron: This will set what the hidden layers are made up of when auto build is enabled.
setHighlight(String) - Method in class weka.gui.treevisualizer.TreeVisualizer: Set the highlight for the node with the given id
setHighlighted(boolean) - Method in class weka.gui.beans.Note
setHighlighted(boolean) - Method in class weka.gui.knowledgeflow.NoteVisual: Set whether the note should appear "highlighted" (i.e.
setHighValue(Double) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the highValue property.
setHistory(DefaultListModel) - Method in class weka.gui.sql.ConnectionPanel: sets the local history to the given one.
setHistory(DefaultListModel) - Method in class weka.gui.sql.QueryPanel: sets the local history to the given one.
setHoeffdingTieThreshold(double) - Method in class weka.classifiers.trees.HoeffdingTree: Set the threshold below which a split will be forced to break ties
setHoldOutFile(File) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set the file that contains hold out/test instances
setID(String) - Method in class weka.core.Defaults: Set the ID for this set of defaults
setId(String) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Item: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Itemset: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.NeuralInput: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Neuron: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Node: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument: Sets the value of the id property.
setId(String) - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Sets the value of the id property.
setID(int) - Method in class weka.core.Tag: Sets the numeric ID of the Tag.
setIDFTransform(boolean) - Method in class weka.core.DictionaryBuilder: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
setIDFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
setIDFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether if the word frequencies in a document should be transformed into:
fij*log(num of Docs/num of Docs with word i)
where fij is the frequency of word i in document(instance) j.
setIDIndex(String) - Method in class weka.filters.unsupervised.attribute.AddID: Sets index of the attribute used.
setIDStr(String) - Method in class weka.core.Tag: Sets the string ID of the Tag.
setIgnoreCase(boolean) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
setIgnoreCase(boolean) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Set whether to ignore case when matching
setIgnoreCase(boolean) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Set whether to ignore case when matching
setIgnoreCaseForNames(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier: Set whether to ignore case when matching attribute names and nominal values.
setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Set the IgnoreClass value.
setIgnoreClass(boolean) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Set the IgnoreClass value.
setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.AddCluster: Sets the ranges of attributes to be ignored.
setIgnoredAttributeIndices(String) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Sets the ranges of attributes to be ignored.
setIgnoredProperties(String) - Method in class weka.core.CheckGOE: Sets the properties to ignore in checkToolTips().
setIgnoreRange(String) - Method in class weka.filters.unsupervised.attribute.MathExpression: Set which attributes are to be ignored
setImageHeight(int) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the image height (in pixels)
setImageWidth(int) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the image width (in pixels)
setImportance(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the importance property.
setImportance(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the importance property.
setIncludeClass(boolean) - Method in class weka.core.InstanceComparator: Sets whether the class should be included in the comparison.
setIncludeClass(boolean) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Sets whether the class can be cleaned, too.
setIncludeRelationName(boolean) - Method in class weka.gui.beans.SerializedModelSaver: Set whether the relation name of the training data used to create the model should be included as part of the filename for the serialized model.
setIncludeRelationNameInFilename(boolean) - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Set whether to include the relation name as part of the filename
setIncrementalLoggingFrequency(String) - Method in class weka.knowledgeflow.steps.WriteWekaLog: Set how frequently to write an incremental data point to the log
setIncrementalSaveSchedule(int) - Method in class weka.gui.beans.SerializedModelSaver: Set how often to save incremental models.
setIncrementalSaveSchedule(int) - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Set how frequently to save an incremental model
setIndentationSize(int) - Method in class weka.gui.scripting.SyntaxDocument: Sets the number of blanks to use for indentation.
setIndex(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeValue: Sets the value of the index property.
setIndex(int) - Method in class weka.core.pmml.MiningFieldMetaInfo: Set the index of this field in the mining schema Instances
setInfoData(Vector<Instances>) - Method in interface weka.gui.visualize.InstanceInfo: Sets the underlying data.
setInfoData(Vector<Instances>) - Method in class weka.gui.visualize.InstanceInfoFrame: Sets the underlying data.
setInfoText(String) - Method in interface weka.gui.visualize.InstanceInfo: Sets the text to display.
setInfoText(String) - Method in class weka.gui.visualize.InstanceInfoFrame: Sets the text to display.
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Sets whether to init as naive bayes
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2: Sets whether to init as naive bayes
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Sets whether to init as naive bayes
setInitAsNaiveBayes(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2: Sets whether to init as naive bayes
setInitFile(File) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Sets the file to initialize the filter with, can be null.
setInitFileClassIndex(String) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Sets class index of the file to initialize the filter with.
setInitialAnchorRandom(boolean) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets whether if the initial anchor is chosen randomly.
setInitialCount(double) - Method in class weka.classifiers.trees.REPTree: Set the value of InitialCount.
setInitializationMethod(SelectedTag) - Method in class weka.clusterers.SimpleKMeans: Set the initialization method to use
setInitialScore(Double) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the initialScore property.
setInitialSplitPaneDividerLocation() - Method in class weka.gui.PackageManager: Setting the initial placement of the divider line on a JSplitPane is problematic.
setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the inlineTable property.
setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the inlineTable property.
setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Sets the value of the inlineTable property.
setInlineTable(InlineTable) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the inlineTable property.
setInputFilename(String) - Method in class weka.gui.GenericPropertiesCreator: sets the file to get the information about the packages from.
setInputFormat(Instances) - Method in class weka.filters.AllFilter: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.Filter: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.RenameRelation: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.SimpleFilter: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.ClassOrder: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.Discretize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.NominalToBinary: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.PartitionMembership: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.Resample: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.SpreadSubsample: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Add: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddCluster: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddExpression: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddID: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddNoise: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.AddValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Center: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Copy: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.FirstOrder: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MathExpression: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NominalToString: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Normalize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Obfuscate: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Remove: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveType: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Reorder: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.Standardize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToNominal: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.SwapValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesDelta: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.attribute.TimeSeriesTranslate: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Randomize: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemovePercentage: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveRange: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.Resample: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.ReservoirSample: Sets the format of the input instances.
setInputFormat(Instances) - Method in class weka.filters.unsupervised.instance.SparseToNonSparse: Sets the format of the input instances.
setInputOrder(SelectedTag) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the input order.
setInputs(Vector<Object>) - Method in class weka.gui.beans.MetaBean
setInstance(int) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Sets the instance at index i of the supplied dataset to be the current instance
setInstance(Instance) - Method in class weka.core.expressionlanguage.weka.InstancesHelper: Sets the current instance to be the supplied instance
setInstance(Instance) - Method in class weka.gui.beans.InstanceEvent: Set the instance
setInstanceFields(InstanceFields) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the instanceFields property.
setInstanceIdVariable(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the instanceIdVariable property.
setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Sets the master index array containing indices of the training instances.
setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.
setInstanceList(int[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the master index array that points to instances in m_Instances, so that only this array is manipulated, and m_Instances is left untouched.
setInstanceList(int[]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the master index array containing indices of the training instances.
setInstanceRange(int) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Sets the number of instances forward to translate values between.
setInstances(Instances) - Method in class weka.core.converters.AbstractSaver: Sets instances that should be stored.
setInstances(Instances) - Method in class weka.core.converters.JSONSaver: Sets instances that should be stored.
setInstances(Instances) - Method in class weka.core.converters.LibSVMSaver: Sets instances that should be stored.
setInstances(Instances) - Method in interface weka.core.converters.Saver: Sets the instances to be saved
setInstances(Instances) - Method in class weka.core.converters.SVMLightSaver: Sets instances that should be stored.
setInstances(Instances) - Method in class weka.core.converters.XRFFSaver: Sets instances that should be stored.
setInstances(Instances) - Method in interface weka.core.DistanceFunction: Sets the instances.
setInstances(Instances) - Method in class weka.core.FilteredDistance: Sets the instances.
setInstances(Instances) - Method in class weka.core.neighboursearch.BallTree: Builds the BallTree based on the given set of instances.
setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Sets the training instances on which the tree is (or is to be) built.
setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets the instances on which the tree is to be built.
setInstances(Instances) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the instances on which the tree is to be built.
setInstances(Instances) - Method in class weka.core.neighboursearch.CoverTree: Builds the Cover Tree on the given set of instances.
setInstances(Instances) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Sets the instances to build the filtering model from.
setInstances(Instances) - Method in class weka.core.neighboursearch.KDTree: Builds the KDTree on the given set of instances.
setInstances(Instances) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets the training instances on which the tree is (or is to be) built.
setInstances(Instances) - Method in class weka.core.neighboursearch.LinearNNSearch: Sets the instances comprising the current neighbourhood.
setInstances(Instances) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Sets the instances.
setInstances(Instances) - Method in class weka.core.NormalizableDistance: Sets the instances.
setInstances(Instances) - Method in class weka.core.xml.XMLInstances: builds up the XML structure based on the given data
setInstances(Instances) - Method in class weka.experiment.AveragingResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.CrossValidationResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.DatabaseResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.LearningRateResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in class weka.experiment.PairedTTester: Set the value of Instances.
setInstances(Instances) - Method in class weka.experiment.RandomSplitResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in interface weka.experiment.ResultProducer: Sets the dataset that results will be obtained for.
setInstances(Instances) - Method in interface weka.experiment.Tester: Set the value of Instances.
setInstances(Instances) - Method in class weka.gui.AbstractPerspective: Set instances (if this perspective can use them)
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffPanel: displays the given instances, i.e.
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets the data
setInstances(Instances) - Method in class weka.gui.arffviewer.ArffTableModel: sets the data
setInstances(Instances) - Method in class weka.gui.AttributeListPanel: Sets the instances who's attribute names will be displayed.
setInstances(Instances) - Method in class weka.gui.AttributeSelectionPanel: Sets the instances who's attribute names will be displayed.
setInstances(Instances) - Method in class weka.gui.AttributeSummaryPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.AttributeVisualizationPanel: Sets the instances for use
setInstances(Instances) - Method in class weka.gui.beans.AttributeSummarizer: Set instances for this bean.
setInstances(Instances) - Method in class weka.gui.beans.DataVisualizer: Set instances for this bean.
setInstances(Instances) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Set instances (if the perspective accepts them)
setInstances(Instances) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setInstances(Instances) - Method in class weka.gui.beans.ScatterPlotMatrix: Set instances for this bean.
setInstances(Instances) - Method in class weka.gui.beans.SQLViewerPerspective: Set instances (if the perspective accepts them)
setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Set the training instances
setInstances(Instances) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the training data
setInstances(Instances) - Method in class weka.gui.experiment.ResultsPanel: Sets up the panel with a new set of instances, attempting to guess the correct settings for various columns.
setInstances(Instances) - Method in class weka.gui.explorer.AbstractPlotInstances: Sets the instances that are the basis for the plot instances.
setInstances(Instances) - Method in class weka.gui.explorer.AssociationsPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.AttributeSelectionPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.ClassifierPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.ClustererPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in interface weka.gui.explorer.Explorer.ExplorerPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.PreprocessPanel: Tells the panel to use a new base set of instances.
setInstances(Instances) - Method in class weka.gui.explorer.VisualizePanel
setInstances(Instances) - Method in class weka.gui.InstancesSummaryPanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Set the instances to visualize
setInstances(Instances, Settings) - Method in class weka.gui.knowledgeflow.AttributeSummaryPerspective: Set the instances to visualize
setInstances(Instances) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Set instances (if this perspective can use them)
setInstances(Instances) - Method in class weka.gui.knowledgeflow.ScatterPlotMatrixPerspective: Set the instances to use
setInstances(Instances) - Method in interface weka.gui.Perspective: Set instances (if this perspective can use them)
setInstances(Instances) - Method in class weka.gui.SetInstancesPanel: Updates the set of instances that is currently held by the panel.
setInstances(Instances, boolean) - Method in class weka.gui.SetInstancesPanel: Updates the set of instances that is currently held by the panel.
setInstances(Instances) - Method in class weka.gui.SimpleCLIPanel
setInstances(Instances) - Method in class weka.gui.ViewerDialog: sets the instances to display
setInstances(Instances) - Method in class weka.gui.visualize.AttributePanel: This sets the instances to be drawn into the attribute panel
setInstances(Instances) - Method in class weka.gui.visualize.ClassPanel: Set the instances.
setInstances(Instances) - Method in class weka.gui.visualize.MatrixPanel: This method changes the Instances object of this class to a new one.
setInstances(Instances) - Method in class weka.gui.visualize.Plot2D: Sets the master plot from a set of instances
setInstances(Instances) - Method in class weka.gui.visualize.VisualizePanel: Tells the panel to use a new set of instances.
setInstances(Instances) - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Set the data to output from this step
setInstancesFromDB(InstanceQuery) - Method in class weka.gui.explorer.PreprocessPanel: Loads instances from a database
setInstancesFromDBQ(String, String, String, String) - Method in class weka.gui.explorer.PreprocessPanel: Loads (non-sparse) instances from an SQL query the user provided with the SqlViewerDialog, then loads the instances in a background process.
setInstancesFromDBQ(String, String, String, String, boolean) - Method in class weka.gui.explorer.PreprocessPanel: Loads instances from an SQL query the user provided with the SqlViewerDialog, then loads the instances in a background process.
setInstancesFromFile(AbstractFileLoader) - Method in class weka.gui.explorer.PreprocessPanel: Loads results from a set of instances retrieved with the supplied loader.
setInstancesFromFileQ() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Queries the user for a file to load instances from, then loads the instances in a background process.
setInstancesFromFileQ() - Method in class weka.gui.explorer.PreprocessPanel: Queries the user for a file to load instances from, then loads the instances in a background process.
setInstancesFromFileQ() - Method in class weka.gui.SetInstancesPanel: Queries the user for a file to load instances from, then loads the instances in a background process.
setInstancesFromURL(URL) - Method in class weka.gui.explorer.PreprocessPanel: Loads instances from a URL.
setInstancesFromURLQ() - Method in class weka.gui.explorer.PreprocessPanel: Queries the user for a URL to load instances from, then loads the instances in a background process.
setInstancesFromURLQ() - Method in class weka.gui.SetInstancesPanel: Queries the user for a URL to load instances from, then loads the instances in a background process.
setInstancesIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveRange: Sets the ranges of instances to be selected.
SetInstancesPanel - Class in weka.gui: A panel that displays an instance summary for a set of instances and lets the user open a set of instances from either a file or URL.
SetInstancesPanel() - Constructor for class weka.gui.SetInstancesPanel: Default constructor.
SetInstancesPanel(boolean, boolean, ConverterFileChooser) - Constructor for class weka.gui.SetInstancesPanel: Create the panel.
setInstanceWeight() - Method in class weka.gui.arffviewer.ArffPanel: Allows setting the weight of the instance at the selected row.
setInstanceWeight(int, double) - Method in class weka.gui.arffviewer.ArffSortedTableModel: Sets the weight of the selected instance
setInstanceWeight(int, double) - Method in class weka.gui.arffviewer.ArffTableModel
setInstanceWeight(int, double, boolean) - Method in class weka.gui.arffviewer.ArffTableModel
setInterAnchorDistances(Vector<MiddleOutConstructor.TempNode>, MiddleOutConstructor.TempNode, Vector<double[]>) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the distances of a supplied new anchor to all the rest of the previous anchor points.
setIntercept(double) - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Sets the value of the intercept property.
setInternalCacheSize(int) - Method in class weka.classifiers.functions.supportVector.StringKernel: sets the size of the internal cache for intermediate results.
setInterpolationMethod(INTERPOLATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Sets the value of the interpolationMethod property.
setInterQuartileRange(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the interQuartileRange property.
setInterval(Interval) - Method in class weka.core.pmml.jaxbbindings.DiscretizeBin: Sets the value of the interval property.
setInvalidFreq(Double) - Method in class weka.core.pmml.jaxbbindings.Counts: Sets the value of the invalidFreq property.
setInvalidValueTreatment(INVALIDVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.Apply: Sets the value of the invalidValueTreatment property.
setInvalidValueTreatment(INVALIDVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the invalidValueTreatment property.
setInvert(boolean) - Method in class weka.core.InstanceComparator: Sets whether to invert the matching sense of the attribute range.
setInvert(boolean) - Method in class weka.core.Range: Sets whether the range sense is inverted, i.e.
setInvert(boolean) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Set whether selection is inverted.
setInvertSelection(boolean) - Method in class weka.core.converters.DictionarySaver: Sets whether selected columns should be processed or skipped.
setInvertSelection(boolean) - Method in class weka.core.DictionaryBuilder: Sets whether selected columns should be processed or skipped.
setInvertSelection(boolean) - Method in interface weka.core.DistanceFunction: Sets whether the matching sense of attribute indices is inverted or not.
setInvertSelection(boolean) - Method in class weka.core.FilteredDistance: Sets whether the matching sense of attribute indices is inverted or not.
setInvertSelection(boolean) - Method in class weka.core.NormalizableDistance: Sets whether the matching sense of attribute indices is inverted or not.
setInvertSelection(boolean) - Method in class weka.filters.supervised.attribute.Discretize: Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Set whether selected attributes should be acted on or all other attributes.
setInvertSelection(boolean) - Method in class weka.filters.supervised.instance.Resample: Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).
setInvertSelection(boolean) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Copy: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Sets whether selected columns should be worked on or all the others apart from these.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether selected columns should be processed or skipped.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.MathExpression: Set whether selected columns should be select or unselect.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Set whether selected attributes should be acted on or all other attributes.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Sets whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Sets whether the selection of the indices is inverted or not
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Sets whether selected columns should be worked on or all the others apart from these.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Sets whether selected columns should be worked on or all the others apart from these.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Sets whether selected columns should be worked on or all the others apart from these.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Set whether selected columns should be transformed or not.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RandomSubset: Set whether to invert the selection - i.e.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.Remove: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RemoveByName: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RemoveType: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Sets whether to invert the selection of the attributes.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Set whether selected columns should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Sets whether selected columns should be worked on or all the others apart from these.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.SortLabels: Sets whether selected columns should be processed or skipped.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether selected columns should be processed or skipped.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Set whether selected values should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemovePercentage: Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveRange: Sets if selection is to be inverted.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Set whether selected values should be removed or kept.
setInvertSelection(boolean) - Method in class weka.filters.unsupervised.instance.Resample: Sets whether the selection is inverted (only if instances are drawn WIHTOUT replacement).
setIRClassValue(String) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the class value (label or index) to use with IR metric evaluation of subsets.
setIRClassValue(String) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set the class value (label or index) to use with IR metric evaluation of subsets.
setIRClassValue(String) - Method in class weka.attributeSelection.WrapperSubsetEval: Set the class value (label or index) to use with IR metric evaluation of subsets.
setIsCenterField(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the isCenterField property.
setIsCyclic(String) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the isCyclic property.
setIsIntercept(Boolean) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the isIntercept property.
setIsMultiValued(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the isMultiValued property.
setIsOr(boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Set whether this node is to be OR'ed to the result so far
setIsRecursive(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the isRecursive property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.MiningModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Sets the value of the isScorable property.
setIsScorable(Boolean) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the isScorable property.
setIsTransformed(Boolean) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the isTransformed property.
setItem(int[]) - Method in class weka.associations.ItemSet: Sets an item sets
setItemAt(int, int) - Method in class weka.associations.ItemSet: Sets the index of an attribute value
setItemRef(String) - Method in class weka.core.pmml.jaxbbindings.ItemRef: Sets the value of the itemRef property.
setIterativeClassifier(IterativeClassifier) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the base learner.
setJaccard(Jaccard) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the jaccard property.
setJitter(int) - Method in class weka.gui.visualize.Plot2D: Set level of jitter and repaint the plot using the new jitter value
setKeepDictionarySorted(boolean) - Method in class weka.core.converters.DictionarySaver: Set whether to keep the dictionary sorted alphabetically or not
setKernel(Kernel) - Method in class weka.classifiers.functions.GaussianProcesses: Sets the kernel to use.
setKernel(Kernel) - Method in class weka.classifiers.functions.SMO.BinarySMO: sets the kernel to use
setKernel(Kernel) - Method in class weka.classifiers.functions.SMO: sets the kernel to use
setKernel(Kernel) - Method in class weka.classifiers.functions.SMOreg: sets the kernel to use
setKernel(Kernel) - Method in class weka.classifiers.functions.supportVector.CheckKernel: Set the lernel to test.
setKernel(Kernel) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Sets the kernel to use.
setKernelBandwidth(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Set the kernel bandwidth (number of nearest neighbours to cover)
setKernelBandwidth(String) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the kernel bandwidth
setKernelFactorExpression(String) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Sets the expression for the kernel.
setKernelMatrixFile(File) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Sets the file holding the kernel matrix
setKey(String) - Method in class weka.core.Settings.SettingKey: set the key of this setting
setKeyFieldName(String) - Method in class weka.experiment.AveragingResultProducer: Set the value of KeyFieldName.
setKeys(String) - Method in class weka.core.converters.DatabaseLoader: Sets the key columns of a database table
setKeySpec(String) - Method in class weka.gui.beans.Join: Set the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)
setKeySpec(String) - Method in class weka.knowledgeflow.steps.Join: Set the key specification (in internal format - k11,k12,...,k1nKEY_SPEC_SEPARATORk21,k22,...,k2n)
setKeywords(String) - Method in class weka.experiment.DatabaseUtils: Sets the keywords (comma-separated list) to use.
setKeywordsMaskChar(String) - Method in class weka.experiment.DatabaseUtils: Sets the mask character to append to table or attribute names that are a reserved keyword.
setKind(String) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the kind property.
setKind(String) - Method in class weka.core.pmml.jaxbbindings.Matrix: Sets the value of the kind property.
setKNN(int) - Method in class weka.classifiers.lazy.IBk: Set the number of neighbours the learner is to use.
setKNN(int) - Method in class weka.classifiers.lazy.LWL: Sets the number of neighbours used for kernel bandwidth setting.
setKohonenMap(KohonenMap) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the kohonenMap property.
setKValue(int) - Method in class weka.classifiers.trees.RandomTree: Set the value of K.
setLabel(String) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Sets the value of the label property.
setLabel(String) - Method in class weka.core.pmml.jaxbbindings.Parameter: Sets the value of the label property.
setLabel(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Sets label of the merged class.
setLabel(String) - Method in class weka.gui.beans.BatchClassifierEvent: Set the label for this event.
setLabel(String) - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Set the label for this widget.
setLabel(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Set the label to assign if this rule matches, or empty string if binary flag attribute is being created.
setLabel(String) - Method in class weka.gui.EnvironmentField: Set the label for this widget.
setLabel(String) - Method in class weka.gui.PasswordField: Set the label for this widget.
setLabels(String) - Method in class weka.filters.unsupervised.attribute.AddValues: Sets the comma-separated list of labels.
setLambda(double) - Method in class weka.classifiers.functions.SGD: Set the value of lambda to use
setLambda(double) - Method in class weka.classifiers.functions.SGDText: Set the value of lambda to use
setLambda(double) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets the lambda constant used in the string kernel
setLaunchStartPointsSequentially(boolean) - Method in class weka.knowledgeflow.FlowRunner: Set whether to launch start points sequentially
setLeafPredictionStrategy(SelectedTag) - Method in class weka.classifiers.trees.HoeffdingTree: Set the leaf prediction strategy to use (majority class, naive Bayes or naive Bayes adaptive)
setLearningRate(double) - Method in class weka.classifiers.functions.MultilayerPerceptron: The learning rate can be set using this command.
setLearningRate(double) - Method in class weka.classifiers.functions.SGD: Set the learning rate.
setLearningRate(double) - Method in class weka.classifiers.functions.SGDText: Set the learning rate.
setLeaveOneAttributeOut(boolean) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set whether to evaluate the merit of an attribute based on the impact of leaving it out from the full set instead of considering its worth in isolation
setLeftMargin(Double) - Method in class weka.core.pmml.jaxbbindings.Interval: Sets the value of the leftMargin property.
setLegend(List<String>, double, double) - Method in class weka.gui.knowledgeflow.steps.StripChartInteractiveView: Set the entries for the legend
setLegend(List<String>, double, double) - Method in interface weka.knowledgeflow.steps.StripChart.PlotNotificationListener
setLegendText(Vector<String>) - Method in class weka.gui.beans.ChartEvent: Set the legend text vector
setLength(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextDocument: Sets the value of the length property.
setLength(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Sets the value of the length property.
setLengthLimit(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the lengthLimit property.
setLevel(Level) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Sets the value of the level property.
setLeverage(Float) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the leverage property.
setLHSAttName(String) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Set the lhs attribute name
setLift(Float) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the lift property.
setLift(Double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the lift property.
setLiftData(LiftData) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the liftData property.
setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.ModelLiftGraph: Sets the value of the liftGraph property.
setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.OptimumLiftGraph: Sets the value of the liftGraph property.
setLiftGraph(LiftGraph) - Method in class weka.core.pmml.jaxbbindings.RandomLiftGraph: Sets the value of the liftGraph property.
setLikelihoodThreshold(double) - Method in class weka.classifiers.meta.LogitBoost: Set the value of Precision.
setLinkFunction(LINKFUNCTION) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the linkFunction property.
setLinkParameter(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the linkParameter property.
setLinkType(SelectedTag) - Method in class weka.clusterers.HierarchicalClusterer
setListData(Object[]) - Method in class weka.gui.CheckBoxList: Constructs a CheckBoxListModel from an array of objects and then applies setModel to it.
setListData(Vector) - Method in class weka.gui.CheckBoxList: Constructs a CheckBoxListModel from a Vector and then applies setModel to it.
setLNorm(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set the L-norm to used
setLNorm(double) - Method in class weka.classifiers.functions.SGDText: Set the L-norm to used
setLoadClassifierFileName(String) - Method in class weka.gui.beans.Classifier: Set the name of the classifier to load at execution time.
setLoadClassifierFileName(File) - Method in class weka.knowledgeflow.steps.Classifier: Set the name of the classifier to load at execution time.
setLoadClustererFileName(File) - Method in class weka.knowledgeflow.steps.Clusterer: Set the name of the clusterer to load at execution time.
setLoaded(boolean) - Method in class weka.gui.AbstractPerspective: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in class weka.gui.beans.AttributeSummarizer: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setLoaded(boolean) - Method in class weka.gui.beans.ScatterPlotMatrix: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in class weka.gui.beans.SQLViewerPerspective: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in interface weka.gui.Perspective: Set whether this perspective is "loaded" - i.e.
setLoaded(boolean) - Method in class weka.gui.SimpleCLIPanel
setLoader(Loader) - Method in class weka.gui.beans.Loader: Set the loader to use
setLoader(Loader) - Method in class weka.knowledgeflow.steps.Loader: Convenience method - calls setWrappedAlgorithm()
setLocallyPredictive(boolean) - Method in class weka.attributeSelection.CfsSubsetEval: Include locally predictive attributes
setLocalTermWeights(String) - Method in class weka.core.pmml.jaxbbindings.TextModelNormalization: Sets the value of the localTermWeights property.
setLocalTransformations(LocalTransformations) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the localTransformations property.
setLocalTransformations(LocalTransformations) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the localTransformations property.
setLocationProbs(int, double[]) - Method in class weka.gui.boundaryvisualizer.RemoteResult: Store the classifier's distribution for a particular pixel in the visualization
setLog(Logger) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Set a logger to use.
setLog(Debug.Log) - Method in class weka.core.Debug.Random: the log to use, if it is null then stdout is used
setLog(Logger) - Method in interface weka.core.LogHandler: Set the log to use
setLog(Logger) - Method in interface weka.core.pmml.PMMLModel: Set a logger to use.
setLog(Logger) - Method in class weka.gui.AbstractPerspective: Set a log to use (if required by the perspective)
setLog(Logger) - Method in class weka.gui.beans.AbstractDataSink: Set a log for this bean
setLog(Logger) - Method in class weka.gui.beans.AbstractEvaluator: Set a logger
setLog(Logger) - Method in class weka.gui.beans.AbstractTestSetProducer: Set a logger
setLog(Logger) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Set a log for this bean
setLog(Logger) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Set a logger
setLog(Logger) - Method in class weka.gui.beans.Appender: Set a logger
setLog(Logger) - Method in class weka.gui.beans.Associator: Set a logger
setLog(Logger) - Method in interface weka.gui.beans.BeanCommon: Set a logger
setLog(Logger) - Method in class weka.gui.beans.ClassAssigner
setLog(Logger) - Method in class weka.gui.beans.Classifier: Set a logger
setLog(Logger) - Method in class weka.gui.beans.ClassValuePicker
setLog(Logger) - Method in class weka.gui.beans.Clusterer: Set a logger
setLog(Logger) - Method in class weka.gui.beans.CostBenefitAnalysis: Set a logger
setLog(Logger) - Method in class weka.gui.beans.DataVisualizer: Set a logger
setLog(Logger) - Method in class weka.gui.beans.Filter: Set a logger
setLog(Logger) - Method in class weka.gui.beans.FlowByExpression
setLog(Logger) - Method in class weka.gui.beans.FlowRunner
setLog(Logger) - Method in class weka.gui.beans.ImageSaver
setLog(Logger) - Method in class weka.gui.beans.ImageViewer
setLog(Logger) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Set a logger
setLog(Logger) - Method in class weka.gui.beans.Join: Set a log to use
setLog(Logger) - Method in class weka.gui.beans.Loader: Set a logger
setLog(Logger) - Method in interface weka.gui.beans.LogWriter: Set a logger
setLog(Logger) - Method in class weka.gui.beans.MetaBean: Set a logger
setLog(Logger) - Method in class weka.gui.beans.ModelPerformanceChart: Set a logger
setLog(Logger) - Method in class weka.gui.beans.PredictionAppender: Set a logger
setLog(Logger) - Method in class weka.gui.beans.SerializedModelSaver: Set a log for this bean.
setLog(Logger) - Method in class weka.gui.beans.Sorter: Set a logger
setLog(Logger) - Method in class weka.gui.beans.StripChart: Set a logger
setLog(Logger) - Method in class weka.gui.beans.SubstringLabeler: Set a logger
setLog(Logger) - Method in class weka.gui.beans.SubstringReplacer: Set a logger
setLog(Logger) - Method in class weka.gui.beans.TextSaver
setLog(Logger) - Method in class weka.gui.beans.TextViewer: Set a logger
setLog(Logger) - Method in class weka.gui.explorer.AssociationsPanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.AttributeSelectionPanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.ClassifierPanel: Sets the Logger to receive informational messages.
setLog(Logger) - Method in class weka.gui.explorer.ClustererPanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.DataGeneratorPanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in interface weka.gui.explorer.Explorer.LogHandler: Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.gui.explorer.PreprocessPanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in interface weka.gui.Perspective: Set a log to use (if required by the perspective)
setLog(Logger) - Method in class weka.gui.SimpleCLIPanel
setLog(Logger) - Method in class weka.gui.visualize.VisualizePanel: Sets the Logger to receive informational messages
setLog(Logger) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set the log to use
setLog(Logger) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set the log to use
setLog(Logger) - Method in interface weka.knowledgeflow.FlowLoader: Set a log to use
setLog(Logger) - Method in class weka.knowledgeflow.JSONFlowLoader: Set a log to use
setLog(Logger) - Method in class weka.knowledgeflow.LegacyFlowLoader: Set the log to use
setLog(Logger) - Method in class weka.knowledgeflow.LogManager: Set the log wrap
setLog(Logger) - Method in class weka.knowledgeflow.StepManagerImpl: Set the log to use
setLogger(Logger) - Method in interface weka.knowledgeflow.FlowExecutor: Set a log to use
setLogger(Logger) - Method in class weka.knowledgeflow.FlowRunner: Set the log to use
setLoggingFontSize(int) - Method in class weka.gui.beans.LogPanel: Set the size of the font used in the log message area.
setLoggingFontSize(int) - Method in class weka.gui.LogPanel: Set the size of the font used in the log message area.
setLoggingLevel(LoggingLevel) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Set the logging level to use
setLoggingLevel(LoggingLevel) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set the logging level to use
setLoggingLevel(LoggingLevel) - Method in interface weka.knowledgeflow.FlowExecutor: Set the level to log at
setLoggingLevel(LoggingLevel) - Method in class weka.knowledgeflow.FlowRunner: Set the logging level to use
setLoggingLevel(LoggingLevel) - Method in class weka.knowledgeflow.LogManager: Set the logging level to use
setLoggingLevel(LoggingLevel) - Method in class weka.knowledgeflow.StepManagerImpl: Set the logging level to use
setLoggingLevel(LoggingLevel) - Method in class weka.knowledgeflow.steps.WriteWekaLog: Set the logging level to use
setLogLossDecoding(boolean) - Method in class weka.classifiers.meta.MultiClassClassifier: Sets whether log loss decoding is used for random or exhaustive codes.
setLookAheadIterations(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of LookAheadIterations.
setLookAndFeel(String) - Static method in class weka.gui.LookAndFeel: sets the look and feel to the specified class
setLookAndFeel(String, String, String) - Static method in class weka.gui.LookAndFeel: Set the look and feel from loaded settings
setLookAndFeel() - Static method in class weka.gui.LookAndFeel: sets the look and feel to the one in the props-file or if not set the default one of the system
setLookupCacheSize(int) - Method in class weka.attributeSelection.BestFirst: Set the maximum size of the evaluated subset cache (hashtable).
setLossFunction(SelectedTag) - Method in class weka.classifiers.functions.SGD: Set the loss function to use.
setLossFunction(SelectedTag) - Method in class weka.classifiers.functions.SGDText: Set the loss function to use.
setLower(double) - Method in class weka.core.pmml.jaxbbindings.UniformDistribution: Sets the value of the lower property.
setLowerBoundMinSupport(double) - Method in class weka.associations.Apriori: Set the value of lowerBoundMinSupport.
setLowerBoundMinSupport(double) - Method in class weka.associations.FPGrowth: Set the value of lowerBoundMinSupport.
setLowercaseTokens(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set whether to convert all tokens to lowercase
setLowercaseTokens(boolean) - Method in class weka.classifiers.functions.SGDText: Set whether to convert all tokens to lowercase
setLowerCaseTokens(boolean) - Method in class weka.core.converters.DictionarySaver: Sets whether if the tokens are to be downcased or not.
setLowerCaseTokens(boolean) - Method in class weka.core.DictionaryBuilder: Sets whether if the tokens are to be downcased or not.
setLowerCaseTokens(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether if the tokens are to be downcased or not.
setLowerCaseTokens(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether if the tokens are to be downcased or not.
setLowerSize(int) - Method in class weka.experiment.LearningRateResultProducer: Set the value of LowerSize.
setLowValue(Double) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the lowValue property.
setMacros(MacroDeclarations) - Method in class weka.core.expressionlanguage.parser.Parser: Sets the macro declarations for the program
setMainApplication(GUIApplication) - Method in class weka.gui.AbstractPerspective: Set the main application.
setMainApplication(GUIApplication) - Method in class weka.gui.knowledgeflow.SQLViewerPerspective: Set the main application.
setMainApplication(GUIApplication) - Method in interface weka.gui.Perspective: Set the main application.
setMainApplication(GUIApplication) - Method in class weka.gui.SimpleCLIPanel
setMainApplicationForAllPerspectives() - Method in class weka.gui.PerspectiveManager: Set the main application on all perspectives managed by this manager
setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.AttributeSummarizer: Set a reference to the main KnowledgeFlow perspective - i.e.
setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in interface weka.gui.beans.KnowledgeFlowApp.KFPerspective: Set a reference to the main KnowledgeFlow perspective - i.e.
setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.ScatterPlotMatrix: Set a reference to the main KnowledgeFlow perspective - i.e.
setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.SQLViewerPerspective: Set a reference to the main KnowledgeFlow perspective - i.e.
setMainKFPerspective(MainKFPerspective) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Set the main knowledge flow perspective.
setMainKFPerspective(MainKFPerspective) - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Set the main knowledge flow perspective.
setMakeBinary(boolean) - Method in class weka.filters.supervised.attribute.Discretize: Sets whether binary attributes should be made for discretized ones.
setMakeBinary(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets whether binary attributes should be made for discretized ones.
setMakeResourceIntensive(boolean) - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Set whether downstream steps are to be made resource intensive or not
setManagedStep(Step) - Method in class weka.knowledgeflow.StepManagerImpl: Set the step managed by this manager
setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.Apply: Sets the value of the mapMissingTo property.
setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.Discretize: Sets the value of the mapMissingTo property.
setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.FieldRef: Sets the value of the mapMissingTo property.
setMapMissingTo(String) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the mapMissingTo property.
setMapMissingTo(Double) - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Sets the value of the mapMissingTo property.
setMapMissingTo(Double) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Sets the value of the mapMissingTo property.
setMappedValue(String) - Method in class weka.core.pmml.jaxbbindings.Item: Sets the value of the mappedValue property.
setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the mapValues property.
setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the mapValues property.
setMapValues(MapValues) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the mapValues property.
setMargin(int, double[]) - Method in class weka.classifiers.bayes.net.EditableBayesNet: set marginal distibution for a node
setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
setMarkovBlanketClassifier(boolean) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm
setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.Plot2D: Set the master plot.
setMasterPlot(PlotData2D) - Method in class weka.gui.visualize.VisualizePanel: Set the master plot for the visualize panel
setMatch(String) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Set the string/regex to use for matching
setMatch(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Set the string/regex to use for matching
setMatchAttributeName(String) - Method in class weka.gui.beans.SubstringLabeler
setMatchAttributeName(String) - Method in class weka.knowledgeflow.steps.SubstringLabeler: Set the name of the new attribute that is created to indicate the match
setMatchDetails(String) - Method in class weka.gui.beans.SubstringLabeler: Set internally encoded list of match rules
setMatchDetails(String) - Method in class weka.knowledgeflow.steps.SubstringLabeler: Set internally encoded list of match rules
setMatchMissingValues(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Sets whether missing values are counted as a match.
setMatchReplaceDetails(String) - Method in class weka.gui.beans.SubstringReplacer: Set internally encoded list of match-replace rules
setMatchReplaceDetails(String) - Method in class weka.knowledgeflow.steps.SubstringReplacer: Set internally encoded list of match-replace rules
setMatrix(int, int, int, int, Matrix) - Method in class weka.core.matrix.Matrix: Set a submatrix.
setMatrix(int[], int[], Matrix) - Method in class weka.core.matrix.Matrix: Set a submatrix.
setMatrix(int[], int, int, Matrix) - Method in class weka.core.matrix.Matrix: Set a submatrix.
setMatrix(int, int, int[], Matrix) - Method in class weka.core.matrix.Matrix: Set a submatrix.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Comparisons: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.ConfusionMatrix: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.CorrelationMethods: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.CorrelationValues: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Covariances: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.DocumentTermMatrix: Sets the value of the matrix property.
setMatrix(Matrix) - Method in class weka.core.pmml.jaxbbindings.Predictor: Sets the value of the matrix property.
setMax(Double) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the max property.
setMax(Double) - Method in class weka.core.pmml.jaxbbindings.Time: Sets the value of the max property.
setMax(double) - Method in class weka.gui.beans.ChartEvent: Set the max y value
setMaxBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of maxBoostingIterations.
setMaxCardinality(int) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: sets the cardinality
setMaxCount(double) - Method in class weka.filters.supervised.instance.SpreadSubsample: Sets the value for the max count
setMaxDecimalPlaces(int) - Method in class weka.core.converters.ArffSaver: Set the maximum number of decimal places to print
setMaxDecimalPlaces(int) - Method in class weka.core.converters.CSVSaver: Set the maximum number of decimal places to print
setMaxDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the naximum default.
setMaxDepth(int) - Method in class weka.classifiers.trees.RandomForest: Set the maximum depth of the tree, 0 for unlimited.
setMaxDepth(int) - Method in class weka.classifiers.trees.RandomTree: Set the maximum depth of the tree, 0 for unlimited.
setMaxDepth(int) - Method in class weka.classifiers.trees.REPTree: Set the value of MaxDepth.
setMaximum(Double) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the maximum property.
setMaximum(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the maximum property.
setMaximumAntConsSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumAntConsSeparationTime property.
setMaximumAttributeNames(int) - Method in class weka.attributeSelection.PrincipalComponents: Sets maximum number of attributes to include in transformed attribute names.
setMaximumAttributeNames(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Sets maximum number of attributes to include in transformed attribute names.
setMaximumAttributes(int) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Sets maximum number of PC attributes to retain.
setMaximumItemsetSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumItemsetSeparationTime property.
setMaximumNumberOfAntecedentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumNumberOfAntecedentItems property.
setMaximumNumberOfClusters(int) - Method in class weka.clusterers.EM: Set the maximum number of clusters to consider when cross-validating
setMaximumNumberOfConsequentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumNumberOfConsequentItems property.
setMaximumNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumNumberOfItems property.
setMaximumTotalSequenceTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the maximumTotalSequenceTime property.
setMaximumVariancePercentageAllowed(double) - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Sets the maximum variance attributes are allowed to have before they are deleted by the filter.
setMaxInstancesInLeaf(int) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets the maximum number of instances allowed in a leaf.
setMaxInstancesInLeaf(int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the maximum number of instances allowed in a leaf.
setMaxInstInLeaf(int) - Method in class weka.core.neighboursearch.KDTree: Sets the maximum number of instances in a leaf.
setMaxInstNum(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the upper boundary for instances per cluster.
setMaxInstNum(int) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the upper boundary for instances per cluster.
setMaxIteration(int) - Method in class weka.core.Optimization: Set the maximal number of iterations in searching (Default 200)
setMaxIterations(int) - Method in class weka.classifiers.trees.lmt.LogisticBase: Sets the parameter "maxIterations".
setMaxIterations(int) - Method in class weka.clusterers.EM: Set the maximum number of iterations to perform
setMaxIterations(int) - Method in class weka.clusterers.SimpleKMeans: set the maximum number of iterations to be executed.
setMaxIterations(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the maximum number of cleansing iterations to perform - < 1 means go until fully cleansed
setMaxIts(int) - Method in class weka.classifiers.functions.Logistic: Set the value of MaxIts.
setMaxK(int) - Method in class weka.classifiers.functions.VotedPerceptron: Set the value of maxK.
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Sets the max number of parents
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.global.K2: Sets the max number of parents
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Sets the max number of parents
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.K2: Sets the max number of parents
setMaxNrOfParents(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Sets the max number of parents
setMaxNumberOfItems(int) - Method in class weka.associations.FPGrowth: Set the maximum number of items to include in large items sets.
setMaxNumberOfItemsPerTA(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the maxNumberOfItemsPerTA property.
setMaxNumberOfItemsPerTransaction(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the maxNumberOfItemsPerTransaction property.
setMaxNumberOfTAsPerTAGroup(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the maxNumberOfTAsPerTAGroup property.
setMaxNumCandidateCanopiesToHoldInMemory(int) - Method in class weka.clusterers.Canopy: Set the maximum number of candidate canopies to retain in memory during training.
setMaxNumComponents(int) - Method in class weka.estimators.UnivariateMixtureEstimator: Sets the number of components to use.
setMaxPlots(int) - Method in class weka.gui.beans.AttributeSummarizer: Set the maximum number of plots to display
setMaxRadius(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the upper boundary for the radiuses of the clusters.
setMaxRange(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Sets the upper boundary for the range of x
setMaxRelativeLeafRadius(double) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Sets the maximum relative radius, allowed for a leaf node.
setMaxRows(int) - Method in class weka.gui.sql.QueryPanel: sets the maximum number of rows to display.
setMaxRuleSize(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the maximum number of tests in rules.
setMaxSubsequenceLength(int) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets the maximum length of the subsequence.
setMaxThreshold(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the maximum threshold.
setMaxTime(Double) - Method in class weka.core.pmml.jaxbbindings.BaseCumHazardTables: Sets the value of the maxTime property.
setMaxTime(double) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Sets the value of the maxTime property.
setMDLTheoryWeight(double) - Method in class weka.classifiers.rules.RuleStats: Set the weight of theory in MDL calcualtion
setMean(double) - Method in class weka.core.pmml.jaxbbindings.AnyDistribution: Sets the value of the mean property.
setMean(double) - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution: Sets the value of the mean property.
setMean(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the mean property.
setMean(double) - Method in class weka.core.pmml.jaxbbindings.PoissonDistribution: Sets the value of the mean property.
setMean(Double) - Method in class weka.core.pmml.jaxbbindings.Time: Sets the value of the mean property.
setMean(int, int, double) - Method in class weka.experiment.ResultMatrix: sets the mean at the given position (if the position is valid).
setMeanAbsoluteError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the meanAbsoluteError property.
setMeanError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the meanError property.
setMeanOfSquares(Double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the meanOfSquares property.
setMeanPrec(int) - Method in class weka.experiment.ResultMatrix: sets the precision for the means.
setMeanSquared(boolean) - Method in class weka.classifiers.lazy.IBk: Sets whether the mean squared error is used rather than mean absolute error when doing cross-validation.
setMeanSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the meanSquaredError property.
setMeanWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the mean (0 = optimal).
setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.BallTree: Sets whether to calculate the performance statistics or not.
setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.KDTree: Sets whether to calculate the performance statistics or not.
setMeasurePerformance(boolean) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Sets whether to calculate the performance statistics or not.
setMedian(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the median property.
setMergeValueRange(String) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Sets range of the merge values used.
setMetaClassifier(Classifier) - Method in class weka.classifiers.meta.Stacking: Adds meta classifier
setMetadata(Map<String, String>) - Method in class weka.core.Settings.SettingKey: Set the metadata for this setting
setMetadataElement(String, String) - Method in class weka.core.Settings.SettingKey: Set the value of a piece of metadata for this setting
setMethod(NeuralMethod) - Method in class weka.classifiers.functions.neural.NeuralNode: Set how this node should operate (note that the neural method has no internal state, so the same object can be used by any number of nodes.
setMethod(SelectedTag) - Method in class weka.classifiers.meta.MultiClassClassifier: Sets the method used.
setMethod(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Sets the value of the method property.
setMethodName(String) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Set the transformation method.
setMetricsToDisplay(List<String>) - Method in class weka.classifiers.evaluation.Evaluation: Set a list of the names of metrics to have appear in the output.
setMetricsToDisplay(List<String>) - Method in class weka.classifiers.Evaluation: Set a list of the names of metrics to have appear in the output.
setMetricType(SelectedTag) - Method in class weka.associations.Apriori: Set the metric type for ranking rules
setMetricType(SelectedTag) - Method in class weka.associations.FPGrowth: Set the metric type to use.
setMin(Double) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the min property.
setMin(Double) - Method in class weka.core.pmml.jaxbbindings.Time: Sets the value of the min property.
setMin(double) - Method in class weka.gui.beans.ChartEvent: Set the min y value
setMinAbsoluteCoefficientValue(double) - Method in class weka.classifiers.functions.SGDText: Set the minimum absolute magnitude for model coefficients.
setMinBoxRelWidth(double) - Method in class weka.core.neighboursearch.KDTree: Sets the minimum relative box width.
setMinBucketSize(int) - Method in class weka.classifiers.rules.OneR: Set the value of minBucketSize.
setMinDefault(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the minimum default.
setMinimal(boolean) - Method in class weka.classifiers.functions.LinearRegression: Sets whether to be more memory conservative or being able to output the model as string.
setMinimizeAbsoluteError(boolean) - Method in class weka.classifiers.meta.AdditiveRegression: Sets whether absolute error is to be minimized.
setMinimizeAbsoluteError(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization: Sets whether to min.
setMinimizeExpectedCost(boolean) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Set the value of MinimizeExpectedCost.
setMinimum(Double) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the minimum property.
setMinimum(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the minimum property.
setMinimumAntConsSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumAntConsSeparationTime property.
setMinimumBucketSize(int) - Method in class weka.attributeSelection.OneRAttributeEval: Set the minumum bucket size used by OneR
setMinimumCanopyDensity(double) - Method in class weka.clusterers.Canopy: Set the minimum T2-based density below which a canopy will be pruned during periodic pruning.
setMinimumConfidence(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the minimumConfidence property.
setMinimumConfidence(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumConfidence property.
setMinimumFractionOfWeightInfoGain(double) - Method in class weka.classifiers.trees.HoeffdingTree: Set the minimum fraction of weight required down at least two branches for info gain splitting
setMinimumFrequency(int) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Sets the minimum frequency.
setMinimumItemsetSeparationTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumItemsetSeparationTime property.
setMinimumLift(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumLift property.
setMinimumNumberInstances(int) - Method in class weka.core.Capabilities: sets the minimum number of instances that have to be in the dataset
setMinimumNumberOfAntecedentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumNumberOfAntecedentItems property.
setMinimumNumberOfConsequentItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumNumberOfConsequentItems property.
setMinimumNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumNumberOfItems property.
setMinimumSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the minimumSupport property.
setMinimumSupport(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumSupport property.
setMinimumTotalSequenceTime(Double) - Method in class weka.core.pmml.jaxbbindings.Constraints: Sets the value of the minimumTotalSequenceTime property.
setMiningBuildTask(MiningBuildTask) - Method in class weka.core.pmml.jaxbbindings.PMML: Sets the value of the miningBuildTask property.
setMiningModel(MiningModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the miningModel property.
setMinInstNum(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the lower boundary for instances per cluster.
setMinInstNum(int) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the lower boundary for instances per cluster.
setMinkowski(Minkowski) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the minkowski property.
setMinLogLikelihoodImprovementCV(double) - Method in class weka.clusterers.EM: Set the minimum improvement in cross-validated log likelihood required to consider increasing the number of clusters when cross-validating to find the best number of clusters
setMinLogLikelihoodImprovementIterating(double) - Method in class weka.clusterers.EM: Set the minimum improvement in log likelihood necessary to perform another iteration of the E and M steps.
setMinMaxX(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the minimum and maximum values of the x axis fixed dimension
setMinMaxY(double, double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the minimum and maximum values of the y axis fixed dimension
setMinMetric(double) - Method in class weka.associations.Apriori: Set the value of minConfidence.
setMinMetric(double) - Method in class weka.associations.FPGrowth: Set the value of minConfidence.
setMinNo(double) - Method in class weka.classifiers.rules.JRip: Sets the minimum total weight of the instances in a rule
setMinNum(double) - Method in class weka.classifiers.trees.RandomTree: Set the value of MinNum.
setMinNum(double) - Method in class weka.classifiers.trees.REPTree: Set the value of MinNum.
setMinNumInstances(int) - Method in class weka.classifiers.trees.LMT: Set the value of minNumInstances.
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.M5Base: Set the minimum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.Rule: Set the minumum number of instances to allow at a leaf node
setMinNumInstances(double) - Method in class weka.classifiers.trees.m5.RuleNode: Set the minumum number of instances to allow at a leaf node
setMinNumObj(int) - Method in class weka.classifiers.rules.PART: Set the value of minNumObj.
setMinNumObj(int) - Method in class weka.classifiers.trees.J48: Set the value of minNumObj.
setMinRadius(double) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the lower boundary for the radiuses of the clusters.
setMinRange(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Sets the lower boundary for the range of x
setMinRuleSize(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the minimum number of tests in rules.
setMinStdDev(double) - Method in class weka.clusterers.EM: Set the minimum value for standard deviation when calculating normal density.
setMinStdDev(double) - Method in class weka.clusterers.MakeDensityBasedClusterer: Set the minimum value for standard deviation when calculating normal density.
setMinStdDevPerAtt(double[]) - Method in class weka.clusterers.EM
setMinTermFreq(int) - Method in class weka.core.converters.DictionarySaver: Set the MinTermFreq value.
setMinTermFreq(int) - Method in class weka.core.DictionaryBuilder: Set the MinTermFreq value.
setMinTermFreq(int) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the MinTermFreq value.
setMinThreshold(double) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Set the minimum threshold.
setMinVarianceProp(double) - Method in class weka.classifiers.trees.RandomTree: Set the value of MinVarianceProp.
setMinVarianceProp(double) - Method in class weka.classifiers.trees.REPTree: Set the value of MinVarianceProp.
setMinWordFrequency(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set the minimum word frequency.
setMinWordFrequency(double) - Method in class weka.classifiers.functions.SGDText: Set the minimum word frequency.
setMissing(int) - Method in class weka.core.AbstractInstance: Sets a specific value to be "missing".
setMissing(Attribute) - Method in class weka.core.AbstractInstance: Sets a specific value to be "missing".
setMissing(int) - Method in interface weka.core.Instance: Sets a specific value to be "missing".
setMissing(Attribute) - Method in interface weka.core.Instance: Sets a specific value to be "missing".
setMissingFreq(Double) - Method in class weka.core.pmml.jaxbbindings.Counts: Sets the value of the missingFreq property.
setMissingMerge(boolean) - Method in class weka.attributeSelection.GainRatioAttributeEval: distribute the counts for missing values across observed values
setMissingMerge(boolean) - Method in class weka.attributeSelection.InfoGainAttributeEval: distribute the counts for missing values across observed values
setMissingMerge(boolean) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: distribute the counts for missing values across observed values
setMissingMode(int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Set the missing value mode.
setMissingMode(SelectedTag) - Method in class weka.classifiers.lazy.KStar: Sets the method to use for handling missing values.
setMissingSeparate(boolean) - Method in class weka.attributeSelection.CfsSubsetEval: Treat missing as a separate value
setMissingValue(String) - Method in class weka.core.converters.CSVLoader: Sets the placeholder for missing values.
setMissingValue(String) - Method in class weka.core.converters.CSVSaver: Sets the placeholder for missing values.
setMissingValuePenalty(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the missingValuePenalty property.
setMissingValuePenalty(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the missingValuePenalty property.
setMissingValueReplacement(String) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the missingValueReplacement property.
setMissingValuesReplacer(Filter) - Method in class weka.clusterers.Canopy: Set a ready-to-use missing values replacement filter
setMissingValueStrategy(MISSINGVALUESTRATEGY) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the missingValueStrategy property.
setMissingValueStrategy(MISSINGVALUESTRATEGY) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the missingValueStrategy property.
setMissingValueTreatment(MISSINGVALUETREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the missingValueTreatment property.
setModalValue(String) - Method in class weka.core.pmml.jaxbbindings.DiscrStats: Sets the value of the modalValue property.
setModel(Classifier) - Method in class weka.classifiers.misc.SerializedClassifier: Sets the fully built model to use, if one doesn't want to load a model from a file or already deserialized a model from somewhere else.
setModel(TableModel) - Method in class weka.gui.arffviewer.ArffTable: sets the new model
setModel(ListModel) - Method in class weka.gui.CheckBoxList: sets the model - must be an instance of CheckBoxListModel
setModel(TableModel) - Method in class weka.gui.SortedTableModel: sets the model to use
setModelClass(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the modelClass property.
setModelDF(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the modelDF property.
setModelFile(File) - Method in class weka.classifiers.misc.SerializedClassifier: Sets the file containing the serialized model.
setModelHeader(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Set the structure of the data used to create the model.
setModelLiftGraph(ModelLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the modelLiftGraph property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.BaselineModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.MiningModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.RuleSetModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TimeSeriesModel: Sets the value of the modelName property.
setModelName(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the modelName property.
setModelPath(String) - Method in class weka.classifiers.misc.InputMappedClassifier: Set the path from which to load a model.
setModelStats(ModelStats) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the modelStats property.
setModelStats(ModelStats) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the modelStats property.
setModelType(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the modelType property.
setModelType(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the modelType property.
setModePanel(SetupModePanel) - Method in class weka.gui.experiment.AbstractSetupPanel: Sets the panel used to switch between simple and advanced modes.
setModePanel(SetupModePanel) - Method in class weka.gui.experiment.SetupPanel: Sets the panel used to switch between simple and advanced modes.
setModePanel(SetupModePanel) - Method in class weka.gui.experiment.SimpleSetupPanel: Sets the panel used to switch between simple and advanced modes.
setModificationText(String) - Method in class weka.filters.RenameRelation: Set the modification text to apply
setModificationText(String) - Method in class weka.knowledgeflow.steps.AlterRelationName: Set the modification text to apply
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.AssociatorCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Set a listener interested in whether we've modified the ImageSaver that we're customizing
setModifiedListener(BeanCustomizer.ModifyListener) - Method in interface weka.gui.beans.BeanCustomizer: Set a listener to be notified about the modified status of this object
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassAssignerCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassifierCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClassValuePickerCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ClustererCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.DataVisualizerCustomizer: Set a listener interested in whether we've modified the ImageSaver that we're customizing
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.FilterCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.FlowByExpressionCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ImageSaverCustomizer: Set a listener interested in whether we've modified the ImageSaver that we're customizing
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.JoinCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.LoaderCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Set a listener interested in whether we've modified the ImageSaver that we're customizing
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.NoteCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.PredictionAppenderCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SaverCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SerializedModelSaverCustomizer
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SorterCustomizer: The modify listener interested in any chages we might make
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SubstringLabelerCustomizer: Set a listener interested in knowing if the object being edited has changed.
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.SubstringReplacerCustomizer: Set a listener interested in knowing if the object being edited has changed.
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.beans.TextSaverCustomizer: Set a listener interested in whether we've modified the TextSaver that we're customizing
setModifiedListener(BeanCustomizer.ModifyListener) - Method in class weka.gui.filters.AddUserFieldsCustomizer: Set an object that is interested in knowing when we make a change to the object that we're editing
setModifiedStatus(Object, boolean) - Method in interface weka.gui.beans.BeanCustomizer.ModifyListener: Tell the listener about the modified status of the source object.
setModifiedStatus(Object, boolean) - Method in class weka.gui.beans.KnowledgeFlowApp: Tells us about the modified status of a particular object - typically a customizer that is editing a flow component.
setModifyHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Sets whether the header will be modified when selecting on nominal attributes.
setModifyHeader(boolean) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Sets whether the header will be modified when selecting on nominal attributes.
setModType(RenameRelation.ModType) - Method in class weka.filters.RenameRelation: Set the modification type to apply
setModType(AlterRelationName.ModType) - Method in class weka.knowledgeflow.steps.AlterRelationName: Set the modification type to apply
setMomentum(double) - Method in class weka.classifiers.functions.MultilayerPerceptron: The momentum can be set using this command.
setMultiInstance(boolean) - Method in class weka.core.TestInstances: sets whether multi-instance data should be generated (with a fixed data structure)
setMultiLineComment(boolean) - Method in class weka.gui.scripting.SyntaxDocument: Sets whether to enable multi-line comments.
setMultiLineCommentEnd(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the string that is the end of a multi-line comment.
setMultiLineCommentStart(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the string that is the start of a multi-line comment.
setMultipleModelMethod(MULTIPLEMODELMETHOD) - Method in class weka.core.pmml.jaxbbindings.Segmentation: Sets the value of the multipleModelMethod property.
setMustRunSingleThreaded(boolean) - Method in class weka.knowledgeflow.StepTask: Set whether this StepTask must run single threaded - i.e.
setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ArrayType: Sets the value of the n property.
setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.INTSparseArray: Sets the value of the n property.
setN(BigInteger) - Method in class weka.core.pmml.jaxbbindings.REALSparseArray: Sets the value of the n property.
setNaiveBayesModel(NaiveBayesModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the naiveBayesModel property.
setNaiveBayesPredictionThreshold(double) - Method in class weka.classifiers.trees.HoeffdingTree: Set the number of instances (weight) a leaf should observe before allowing naive Bayes to make predictions
setName(String) - Method in class weka.core.pmml.jaxbbindings.Application: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Characteristic: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Extension: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.NumericPredictor: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Parameter: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.ParameterField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Partition: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Predictor: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.PredictorTerm: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.Taxonomy: Sets the value of the name property.
setName(String) - Method in class weka.core.pmml.jaxbbindings.TextDocument: Sets the value of the name property.
setName(String) - Method in class weka.filters.unsupervised.attribute.AddExpression: Set the name for the new attribute.
setName(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Set the name of the new attribute
setName(String) - Method in class weka.gui.visualize.VisualizePanel: Set a name for this plot
setName(String) - Method in class weka.knowledgeflow.steps.BaseStep: Set the name of this step
setName(String) - Method in interface weka.knowledgeflow.steps.Step: Set the name for this step
setNbCols(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Matrix: Sets the value of the nbCols property.
setNbCorrect(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet: Sets the value of the nbCorrect property.
setNbCorrect(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the nbCorrect property.
setNbRows(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Matrix: Sets the value of the nbRows property.
setNearestNeighborModel(NearestNeighborModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the nearestNeighborModel property.
setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.IBk: Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
setNearestNeighbourSearchAlgorithm(NearestNeighbourSearch) - Method in class weka.classifiers.lazy.LWL: Sets the nearestNeighbourSearch algorithm to be used for finding nearest neighbour(s).
setNegated(boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Set whether this node is negated
setNegativeTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC: Sets the value of the negativeTargetFieldDisplayValue property.
setNegativeTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC: Sets the value of the negativeTargetFieldValue property.
setNeuralNetwork(NeuralNetwork) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the neuralNetwork property.
setNewAttributeName(String) - Method in class weka.gui.beans.SubstringLabelerRules: Set the name to use for the new attribute that is added
setNGramMaxSize(int) - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Sets the max size of the Ngram.
setNGramMaxSize(int) - Method in class weka.core.tokenizers.NGramTokenizer: Sets the max size of the Ngram.
setNGramMinSize(int) - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Sets the min size of the Ngram.
setNGramMinSize(int) - Method in class weka.core.tokenizers.NGramTokenizer: Sets the min size of the Ngram.
setNoClass(boolean) - Method in class weka.core.TestInstances: whether to have no class, e.g., for clusterers; otherwise the class attribute index is set to last
setNode(Node) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the node property.
setNodeName(int, String) - Method in class weka.classifiers.bayes.net.EditableBayesNet: change the name of a node
setNodesEdges(ArrayList<GraphNode>, ArrayList<GraphEdge>) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Sets the nodes and edges for this LayoutEngine.
setNodesEdges(ArrayList<GraphNode>, ArrayList<GraphEdge>) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method sets the nodes and edges vectors of the LayoutEngine
setNodeSize(int, int) - Method in class weka.gui.graphvisualizer.HierarchicalBCEngine: Sets the size of a node.
setNodeSize(int, int) - Method in interface weka.gui.graphvisualizer.LayoutEngine: This method sets the allowed size of the node
setNodeSplitter(KDTreeNodeSplitter) - Method in class weka.core.neighboursearch.KDTree: Sets the splitting method to use to split the nodes of the KDTree.
setNodeWidthNormalization(boolean) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Sets whether if a nodes region is normalized or not.
setNoHeaderRow(boolean) - Method in class weka.core.converters.CSVSaver: Set whether to not write the header row
setNoHeaderRowPresent(boolean) - Method in class weka.core.converters.CSVLoader: Set whether there is no header row in the data.
setNoise(double) - Method in class weka.classifiers.functions.GaussianProcesses: Set the level of Gaussian Noise.
setNoisePercent(double) - Method in class weka.datagenerators.classifiers.classification.LED24: Sets the noise percentage.
setNoiseRate(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Sets the gaussian noise rate.
setNoiseVariance(double) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Sets the noise variance
setNominalAttributes(String) - Method in class weka.core.converters.CSVLoader: Sets the attribute range to be forced to type nominal.
setNominalBinary(boolean) - Method in class weka.gui.beans.SubstringLabeler: Set whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.
setNominalBinary(boolean) - Method in class weka.gui.beans.SubstringLabelerRules: Set whether to create a nominal binary attribute in the case when the user has not supplied an explicit label to use for each rule.
setNominalBinary(boolean) - Method in class weka.knowledgeflow.steps.SubstringLabeler: Set whether the new attribute created should be a nominal binary attribute rather than a numeric binary attribute.
setNominalCols(Range) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Sets which attributes are nominal.
setNominalConversionThreshold(int) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: Set the minimum number of values a nominal attribute must have in order to be transformed.
setNominalIndices(String) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Sets which attributes are nominal
setNominalIndices(String) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Set which nominal labels are to be included in the selection.
setNominalIndicesArr(int[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Set which values of a nominal attribute are to be used for selection.
setNominalLabels(String) - Method in class weka.filters.unsupervised.attribute.Add: Set the labels for nominal attribute creation.
setNominalLabelSpecs(Object[]) - Method in class weka.core.converters.CSVLoader: Set label specifications for nominal attributes.
setNominalStringReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Set the nominal/string replacement value
setNominalToBinaryFilter(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNonEmpty(String) - Method in class weka.core.TestOptions
setNoPruning(boolean) - Method in class weka.classifiers.trees.REPTree: Set the value of NoPruning.
setNoReplacement(boolean) - Method in class weka.filters.supervised.instance.Resample: Sets whether instances are drawn with or with out replacement.
setNoReplacement(boolean) - Method in class weka.filters.unsupervised.instance.Resample: Sets whether instances are drawn with or with out replacement.
setNorm(double) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set the norm of the instances
setNorm(double) - Method in class weka.classifiers.functions.SGDText: Set the norm of the instances
setNorm(double) - Method in class weka.core.pmml.jaxbbindings.LinearNorm: Sets the value of the norm property.
setNormalizationMethod(NNNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the normalizationMethod property.
setNormalizationMethod(NNNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the normalizationMethod property.
setNormalizationMethod(REGRESSIONNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the normalizationMethod property.
setNormalizationMethod(REGRESSIONNORMALIZATIONMETHOD) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the normalizationMethod property.
setNormalizationScheme(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the normalizationScheme property.
setNormalize(boolean) - Method in class weka.core.DictionaryBuilder: Set whether word frequencies for a document should be normalized
setNormalizeAttributes(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNormalizedCountTable(COUNTTABLETYPE) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the normalizedCountTable property.
setNormalizeDimWidths(boolean) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Should we normalize the widths(ranges) of the dimensions (attributes) before selecting the widest one.
setNormalizeDocLength(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set whether to normalize the length of each document
setNormalizeDocLength(boolean) - Method in class weka.classifiers.functions.SGDText: Set whether to normalize the length of each document
setNormalizeDocLength(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether if the word frequencies for a document (instance) should be normalized or not.
setNormalizeDocLength(SelectedTag) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether if the word frequencies for a document (instance) should be normalized or not.
setNormalizeNodeWidth(boolean) - Method in class weka.core.neighboursearch.KDTree: Sets the flag for normalizing the widths of a KDTree Node by the width of the dimension in the universe.
setNormalizeNumericClass(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron
setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the normContinuous property.
setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the normContinuous property.
setNormContinuous(NormContinuous) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the normContinuous property.
setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the normDiscrete property.
setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the normDiscrete property.
setNormDiscrete(NormDiscrete) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the normDiscrete property.
setNoSizeDetermination(boolean) - Method in class weka.experiment.ClassifierSplitEvaluator: Sets whether the size determination (train/test/classifer) is skipped.
setNoSizeDetermination(boolean) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Sets whether the size determination (train/test/clusterer) is skipped.
setNoSizeDetermination(boolean) - Method in class weka.experiment.RegressionSplitEvaluator: Sets whether the size determination (train/test/classifer) is skipped.
setNotCapabilities(Capabilities) - Method in class weka.core.FindWithCapabilities: Uses the given "not to have" Capabilities for the search.
setNotes(String) - Method in class weka.experiment.Experiment: Set the user notes.
setNotes(String) - Method in class weka.experiment.RemoteExperiment: Set the user notes.
setNoteText(String) - Method in class weka.gui.beans.Note: Set the text to display
setNoteText(String) - Method in class weka.knowledgeflow.steps.Note: Set the text of the note
setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets whether the notification of changes is enabled
setNotificationEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel: sets whether the notification of changes is enabled
setNoTrueChildStrategy(NOTRUECHILDSTRATEGY) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the noTrueChildStrategy property.
setNoTrueChildStrategy(NOTRUECHILDSTRATEGY) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the noTrueChildStrategy property.
setNrOfGoodOperations(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Sets the number of "good operations"
setNrOfLookAheadSteps(int) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Sets the number of look-ahead steps
setNumAllConds(double) - Method in class weka.classifiers.rules.RuleStats: Set the number of all conditions that could appear in a rule in this RuleStats object, if the number set is smaller than 0 (typically -1), then it calcualtes based on the data store
setNumArcs(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Sets the number of arcs for the bayesian net
setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Sets the number of attributes the dataset should have.
setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Sets the number of attributes the dataset should have.
setNumAttributes(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the number of attributes the dataset should have.
setNumAttributes(int) - Method in class weka.datagenerators.ClusterGenerator: Sets the number of attributes the dataset should have.
setNumAttributes(double) - Method in class weka.filters.unsupervised.attribute.RandomSubset: Set the number of attributes.
setNumberOfAttributes(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Sets the value of the numberOfAttributes property.
setNumberOfAttributes(int) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets the number of attributes (dimensions) the data should be reduced to
setNumberOfClusters(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ClusteringModel: Sets the value of the numberOfClusters property.
setNumberOfCoefficients(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Coefficients: Sets the value of the numberOfCoefficients property.
setNumberOfDocuments(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the numberOfDocuments property.
setNumberOfFields(BigInteger) - Method in class weka.core.pmml.jaxbbindings.DataDictionary: Sets the value of the numberOfFields property.
setNumberOfFields(BigInteger) - Method in class weka.core.pmml.jaxbbindings.VectorFields: Sets the value of the numberOfFields property.
setNumberOfInputs(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralInputs: Sets the value of the numberOfInputs property.
setNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the numberOfItems property.
setNumberOfItems(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Itemset: Sets the value of the numberOfItems property.
setNumberOfItemsets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the numberOfItemsets property.
setNumberOfLayers(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the numberOfLayers property.
setNumberOfNeighbors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the numberOfNeighbors property.
setNumberOfNeurons(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the numberOfNeurons property.
setNumberOfOutputs(BigInteger) - Method in class weka.core.pmml.jaxbbindings.NeuralOutputs: Sets the value of the numberOfOutputs property.
setNumberOfRules(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the numberOfRules property.
setNumberOfSets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the numberOfSets property.
setNumberOfSets(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the numberOfSets property.
setNumberOfSupportVectors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SupportVectors: Sets the value of the numberOfSupportVectors property.
setNumberOfTerms(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TextModel: Sets the value of the numberOfTerms property.
setNumberOfTransactionGroups(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the numberOfTransactionGroups property.
setNumberOfTransactions(BigInteger) - Method in class weka.core.pmml.jaxbbindings.AssociationModel: Sets the value of the numberOfTransactions property.
setNumberOfTransactions(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceModel: Sets the value of the numberOfTransactions property.
setNumberOfVectors(BigInteger) - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Sets the value of the numberOfVectors property.
setNumBins(int) - Method in class weka.classifiers.meta.RegressionByDiscretization: Sets the number of bins to divide each selected numeric attribute into
setNumBins(int) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
setNumBins(int) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Sets the number of bins
setNumBoostingIterations(int) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of numBoostingIterations.
setNumBoostingIterations(int) - Method in class weka.classifiers.trees.LMT: Set the value of numBoostingIterations.
setNumBootstrapRuns(int) - Method in class weka.estimators.UnivariateMixtureEstimator: Sets the number of Bootstrap runs.
setNumCentroids(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Sets the number of centroids to use.
setNumClasses(int) - Method in class weka.core.TestInstances: sets the number of classes
setNumClasses(int) - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Sets the number of classes the dataset should have.
setNumClasses(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the number of classes the dataset should have.
setNumClusters(int) - Method in class weka.clusterers.Canopy
setNumClusters(int) - Method in class weka.clusterers.EM: Set the number of clusters (-1 to select by CV).
setNumClusters(int) - Method in class weka.clusterers.FarthestFirst: set the number of clusters to generate
setNumClusters(int) - Method in class weka.clusterers.HierarchicalClusterer
setNumClusters(int) - Method in class weka.clusterers.MakeDensityBasedClusterer: Set the number of clusters to generate.
setNumClusters(int) - Method in interface weka.clusterers.NumberOfClustersRequestable: Set the number of clusters to generate
setNumClusters(int) - Method in class weka.clusterers.SimpleKMeans: set the number of clusters to generate.
setNumClusters(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the number of clusters the dataset should have.
setNumComponents(int) - Method in class weka.estimators.UnivariateMixtureEstimator: Sets the number of components to use.
setNumCycles(int) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the the number of cycles.
setNumDate(int) - Method in class weka.core.CheckScheme: sets the number of data attributes
setNumDate(int) - Method in class weka.core.TestInstances: sets the number of date attributes
setNumDecimalPlaces(int) - Method in class weka.classifiers.AbstractClassifier: Set the number of decimal places.
setNumDecimalPlaces(int) - Method in class weka.classifiers.trees.m5.Rule: Set the number of decimal places.
setNumDecimalPlaces(int) - Method in class weka.classifiers.trees.RandomForest: Set the number of decimal places.
setNumDecimals(int) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the number of digits to output after the decimal point.
setNumeric(boolean) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Sets if the new Attribute is to be numeric.
setNumericAttributes(String) - Method in class weka.core.converters.CSVLoader: Sets the attribute range to be forced to type numeric
setNumericInfo(NumericInfo) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Sets the value of the numericInfo property.
setNumericInfo(NumericInfo) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the numericInfo property.
setNumericReplacementValue(String) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Set the numeric replacement value
setNumExamples(int) - Method in class weka.datagenerators.ClassificationGenerator: Sets the number of examples, given by option.
setNumExamples(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Sets the number of examples, given by option.
setNumExamples(int) - Method in class weka.datagenerators.RegressionGenerator: Sets the number of examples, given by option.
setNumExecutionSlots(int) - Method in class weka.attributeSelection.GreedyStepwise: Sets the number of threads
setNumExecutionSlots(int) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Set the number of execution slots (threads) to use for building the members of the ensemble.
setNumExecutionSlots(int) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Set the number of execution slots (threads) to use for building the members of the ensemble.
setNumExecutionSlots(int) - Method in class weka.clusterers.EM: Set the degree of parallelism to use.
setNumExecutionSlots(int) - Method in class weka.clusterers.SimpleKMeans: Set the degree of parallelism to use.
setNumFeatures(int) - Method in class weka.classifiers.trees.RandomForest: Set the number of features to use in random selection.
setNumFolds(int) - Method in class weka.classifiers.functions.SMO: Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.meta.CVParameterSelection: Sets the number of folds for the cross-validation.
setNumFolds(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of NumFolds.
setNumFolds(int) - Method in class weka.classifiers.meta.MultiScheme: Sets the number of folds for cross-validation.
setNumFolds(int) - Method in class weka.classifiers.meta.Stacking: Sets the number of folds for the cross-validation.
setNumFolds(int) - Method in class weka.classifiers.rules.PART: Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.trees.J48: Set the value of numFolds.
setNumFolds(int) - Method in class weka.classifiers.trees.RandomTree: Set the value of NumFolds.
setNumFolds(int) - Method in class weka.classifiers.trees.REPTree: Set the value of NumFolds.
setNumFolds(int) - Method in class weka.clusterers.EM: Set the number of folds to use when cross-validating to find the best number of clusters.
setNumFolds(int) - Method in class weka.experiment.CrossValidationResultProducer: Set the value of NumFolds.
setNumFolds(int) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Sets the number of folds the dataset is split into.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Sets the number of folds the dataset is split into.
setNumFolds(int) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the number of cross-validation folds to use - < 2 means no cross-validation.
setNumFolds(String) - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Set the number of folds to create
setNumInstances(int) - Method in class weka.core.CheckScheme: Sets the number of instances to use in the datasets (some classifiers might require more instances).
setNumInstances(int) - Method in class weka.core.TestInstances: sets the number of instances to produce
setNumInstances(Random) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the real number of instances for this cluster.
setNumInstances(int) - Method in class weka.estimators.CheckEstimator: Sets the number of instances to use in the datasets (some estimators might require more instances).
setNumInstancesRelational(int) - Method in class weka.core.CheckScheme: sets the number of instances in relational/bag attributes to produce
setNumInstancesRelational(int) - Method in class weka.core.TestInstances: sets the number of instances in relational/bag attributes to produce
setNumIntervals(int) - Method in class weka.filters.supervised.instance.ClassBalancer: Sets the number of discretization intervals to use.
setNumIrrelevant(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the number of irrelevant attributes.
setNumIterations(int) - Method in class weka.classifiers.functions.VotedPerceptron: Set the value of NumIterations.
setNumIterations(int) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Sets the number of bagging iterations
setNumKMeansRuns(int) - Method in class weka.clusterers.EM: Set the number of runs of SimpleKMeans to perform.
setNumLocationsPerPixel(String) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the number of locations/samples per pixel
setNumNeighbours(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Set the number of nearest neighbours
setNumNominal(int) - Method in class weka.core.CheckScheme: sets the number of nominal attributes
setNumNominal(int) - Method in class weka.core.TestInstances: sets the number of nominal attributes
setNumNominalValues(int) - Method in class weka.core.TestInstances: sets the number of values for nominal attributes
setNumNumeric(int) - Method in class weka.core.CheckScheme: sets the number of numeric attributes
setNumNumeric(int) - Method in class weka.core.TestInstances: sets the number of numeric attributes
setNumNumeric(int) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the number of numerical attributes.
setNumOfPredictors(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the numOfPredictors property.
setNumOfRecords(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the numOfRecords property.
setNumOfRecordsWeighted(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the numOfRecordsWeighted property.
setNumRelational(int) - Method in class weka.core.CheckScheme: sets the number of relational attributes
setNumRelational(int) - Method in class weka.core.TestInstances: sets the number of relational attributes
setNumRelationalDate(int) - Method in class weka.core.TestInstances: sets the number of date attributes in a relational attribute
setNumRelationalNominal(int) - Method in class weka.core.TestInstances: sets the number of nominal attributes in a relational attribute
setNumRelationalNominalValues(int) - Method in class weka.core.TestInstances: sets the number of values for nominal attributes in a relational attribute
setNumRelationalNumeric(int) - Method in class weka.core.TestInstances: sets the number of numeric attributes in a relational attribute
setNumRelationalString(int) - Method in class weka.core.TestInstances: sets the number of string attributes in a relational attribute
setNumRules(int) - Method in class weka.associations.Apriori: Set the value of numRules.
setNumRulesToFind(int) - Method in class weka.associations.FPGrowth: Set the desired number of rules to find.
setNumRuns(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of NumRuns.
setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the number of points to uniformly sample from a region (fixed dimensions).
setNumSamplesPerRegion(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the number of points to uniformly sample from a region (fixed dimensions).
setNumString(int) - Method in class weka.core.CheckScheme: sets the number of string attributes
setNumString(int) - Method in class weka.core.TestInstances: sets the number of string attributes
setNumThreads(int) - Method in class weka.attributeSelection.CfsSubsetEval: Sets the number of threads
setNumThreads(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Sets the number of threads
setNumThreads(int) - Method in class weka.classifiers.meta.LogitBoost: Sets the number of threads
setNumToEvaluateInParallel(int) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the number of attributes to evaluate in parallel
setNumToSelect(int) - Method in class weka.attributeSelection.GreedyStepwise: Specify the number of attributes to select from the ranked list (if generating a ranking).
setNumToSelect(int) - Method in interface weka.attributeSelection.RankedOutputSearch: Specify the number of attributes to select from the ranked list.
setNumToSelect(int) - Method in class weka.attributeSelection.Ranker: Specify the number of attributes to select from the ranked list.
setNumValues(int) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Sets how many values are retained
setObject(Object) - Method in class weka.core.CheckGOE: Set the object to work on..
setObject(Object) - Method in class weka.gui.beans.AssociatorCustomizer: Set the classifier object to be edited
setObject(Object) - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Set the model performance chart object to customize
setObject(Object) - Method in class weka.gui.beans.ClassAssignerCustomizer: Set the bean to be edited
setObject(Object) - Method in class weka.gui.beans.ClassifierCustomizer: Set the classifier object to be edited
setObject(Object) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer: Set the ClassifierPerformanceEvaluator to be customized
setObject(Object) - Method in class weka.gui.beans.ClassValuePickerCustomizer: Set the bean to be edited
setObject(Object) - Method in class weka.gui.beans.ClustererCustomizer: Set the Clusterer object to be edited
setObject(Object) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer: Set the object to be edited
setObject(Object) - Method in class weka.gui.beans.DataVisualizerCustomizer: Set the model performance chart object to customize
setObject(Object) - Method in class weka.gui.beans.FilterCustomizer: Set the filter bean to be edited
setObject(Object) - Method in class weka.gui.beans.FlowByExpressionCustomizer
setObject(Object) - Method in class weka.gui.beans.ImageSaverCustomizer: Set the ImageSaver object to customize.
setObject(Object) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer: Set the object to be edited
setObject(Object) - Method in class weka.gui.beans.JoinCustomizer
setObject(Object) - Method in class weka.gui.beans.LoaderCustomizer: Set the loader to be customized
setObject(Object) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Set the model performance chart object to customize
setObject(Object) - Method in class weka.gui.beans.NoteCustomizer
setObject(Object) - Method in class weka.gui.beans.PredictionAppenderCustomizer: Set the object to be edited
setObject(Object) - Method in class weka.gui.beans.SaverCustomizer: Set the saver to be customized
setObject(Object) - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Set the model saver to be customized
setObject(Object) - Method in class weka.gui.beans.SorterCustomizer: Set the object to edit
setObject(Object) - Method in class weka.gui.beans.StripChartCustomizer: Set the StripChart object to be customized
setObject(Object) - Method in class weka.gui.beans.SubstringLabelerCustomizer: Set the SubstringLabeler to edit
setObject(Object) - Method in class weka.gui.beans.SubstringReplacerCustomizer: Set the SubstringReplacer to edit
setObject(Object) - Method in class weka.gui.beans.TextSaverCustomizer: Set the TextSaver object to customize.
setObject(Object) - Method in class weka.gui.beans.TrainTestSplitMakerCustomizer: Set the TrainTestSplitMaker to be customized
setObject(Object) - Method in class weka.gui.filters.AddUserFieldsCustomizer: Set the filter to edit.
setOccurrence(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the occurrence property.
setOccurrence(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the occurrence property.
setOffDiagDefault(Double) - Method in class weka.core.pmml.jaxbbindings.Matrix: Sets the value of the offDiagDefault property.
setOffDiskReportingFrequency(int) - Method in class weka.associations.FPGrowth: Set how often to report some progress when the data is being read incrementally off of the disk rather than loaded into memory.
setOffscreenAdditionalOpts(String) - Method in class weka.gui.beans.DataVisualizer: Set the additional options for the offscreen renderer
setOffscreenAdditionalOpts(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the additional options for the offscreen renderer
setOffscreenAdditionalOpts(String) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Set the additional options for the offscreen renderer
setOffscreenAdditionalOpts(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the additional options for the offscreen renderer
setOffscreenAdditionalOpts(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the additional options for the offscreen renderer
setOffscreenHeight(String) - Method in class weka.gui.beans.DataVisualizer: Set the height (in pixels) of the offscreen image to generate
setOffscreenHeight(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the height (in pixels) of the offscreen image to generate
setOffscreenHeight(String) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Set the height (in pixels) of the offscreen image to generate
setOffscreenHeight(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the height (in pixels) of the offscreen image to generate
setOffscreenHeight(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the height (in pixels) of the offscreen image to generate
setOffscreenRendererName(String) - Method in class weka.gui.beans.DataVisualizer: Set the name of the renderer to use for offscreen chart rendering operations
setOffscreenRendererName(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the name of the renderer to use for offscreen chart rendering operations
setOffscreenRendererName(String) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Set the name of the renderer to use for offscreen chart rendering operations
setOffscreenRendererName(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the name of the renderer to use for offscreen chart rendering operations
setOffscreenRendererName(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the name of the renderer to use for offscreen chart rendering operations
setOffscreenWidth(String) - Method in class weka.gui.beans.DataVisualizer: Set the width (in pixels) of the offscreen image to generate.
setOffscreenWidth(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the width (in pixels) of the offscreen image to generate.
setOffscreenWidth(String) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Set the width (in pixels) of the offscreen image to generate.
setOffscreenWidth(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the width (in pixels) of the offscreen image to generate.
setOffscreenWidth(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the width (in pixels) of the offscreen image to generate.
setOffscreenXAxis(String) - Method in class weka.gui.beans.DataVisualizer: Set the name of the attribute for the x-axis in offscreen plots.
setOffscreenXAxis(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the name of the attribute for the x-axis in offscreen plots.
setOffscreenXAxis(String) - Method in class weka.knowledgeflow.steps.AttributeSummarizer: Set the name of the attribute for the x-axis in offscreen plots.
setOffscreenXAxis(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the name of the attribute for the x-axis in offscreen plots.
setOffscreenXAxis(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the name of the attribute for the x-axis in offscreen plots.
setOffscreenYAxis(String) - Method in class weka.gui.beans.DataVisualizer: Set the name of the attribute for the y-axis in offscreen plots.
setOffscreenYAxis(String) - Method in class weka.gui.beans.ModelPerformanceChart: Set the name of the attribute for the y-axis in offscreen plots.
setOffscreenYAxis(String) - Method in class weka.knowledgeflow.steps.DataVisualizer: Set the name of the attribute for the y-axis in offscreen plots.
setOffscreenYAxis(String) - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Set the name of the attribute for the y-axis in offscreen plots.
setOffset(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Sets the value of the offset property.
setOffsetValue(Double) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the offsetValue property.
setOffsetVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the offsetVariable property.
setOkButtonText(String) - Method in class weka.gui.GenericObjectEditor.GOEPanel: Allows customization of the action label on the dialog.
setOmega(double) - Method in class weka.classifiers.functions.supportVector.Puk: Sets the omega value.
setOn(boolean) - Method in class weka.gui.visualize.ClassPanel: Enables the panel
setOnDemandDirectory(File) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Sets the directory that will be searched for cost files when loading on demand.
setOnDemandDirectory(File) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Sets the directory that will be searched for cost files when loading on demand.
setOperator(String) - Method in class weka.core.pmml.jaxbbindings.SetPredicate: Sets the value of the operator property.
setOperator(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Sets the value of the operator property.
setOperator(FlowByExpression.ExpressionClause.ExpressionType) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Set the operator
setOptimalColumnWidth(int) - Method in class weka.gui.JTableHelper: sets the optimal column width for the given column
setOptimalColumnWidth(JTable, int) - Static method in class weka.gui.JTableHelper: sets the optimal column width for the given column
setOptimalColumnWidth() - Method in class weka.gui.JTableHelper: sets the optimal column width for all columns
setOptimalColumnWidth(JTable) - Static method in class weka.gui.JTableHelper: sets the optimal column width for alls column if the given table
setOptimalColWidth() - Method in class weka.gui.arffviewer.ArffPanel: calculates the optimal column width for the current column
setOptimalColWidths() - Method in class weka.gui.arffviewer.ArffPanel: calculates the optimal column widths for all columns
setOptimalColWidths() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the optimal column width for all columns
setOptimalHeaderWidth(int) - Method in class weka.gui.JTableHelper: sets the optimal header width for the given column
setOptimalHeaderWidth(JTable, int) - Static method in class weka.gui.JTableHelper: sets the optimal header width for the given column
setOptimalHeaderWidth() - Method in class weka.gui.JTableHelper: sets the optimal header width for all columns
setOptimalHeaderWidth(JTable) - Static method in class weka.gui.JTableHelper: sets the optimal header width for alls column if the given table
setOptimizations(int) - Method in class weka.classifiers.rules.JRip: Sets the number of optimization runs
setOptimumLiftGraph(OptimumLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the optimumLiftGraph property.
setOptionHandler(OptionHandler) - Method in class weka.core.CheckOptionHandler: Set the OptionHandler to work on..
setOptions(String[]) - Method in class weka.associations.AbstractAssociator: Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.Apriori: Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.CheckAssociator: Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.FilteredAssociator: Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.FPGrowth: Parses a given list of options.
setOptions(String[]) - Method in class weka.associations.SingleAssociatorEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ASEvaluation: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ASSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.BestFirst: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.CfsSubsetEval: Parses and sets a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.CheckAttributeSelection: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ClassifierAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ClassifierSubsetEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.CorrelationAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GainRatioAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.GreedyStepwise: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.InfoGainAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.OneRAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.PrincipalComponents: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.Ranker: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.ReliefFAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.attributeSelection.WrapperSubsetEval: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.AbstractClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.BayesNet: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.NaiveBayes: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.ci.ICSSearchAlgorithm: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.fixed.FromFile: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.HillClimber: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.K2: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.global.TAN: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.HillClimber: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.K2: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.LAGDHillClimber: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.local.TAN: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.BVDecompose: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.CheckClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.CheckSource: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.evaluation.output.prediction.CSV: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.classifiers.functions.GaussianProcesses: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.LinearRegression: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.Logistic: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.MultilayerPerceptron: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SGD: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SGDText: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLinearRegression: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SimpleLogistic: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SMO: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.SMOreg: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.CachedKernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.CheckKernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.Kernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.PolyKernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.Puk: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegSMO: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.supportVector.StringKernel: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.functions.VotedPerceptron: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.IteratedSingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.IBk: Parses a given list of options.
setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute: Sets the options.
setOptions(int, int, int) - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Set options.
setOptions(String[]) - Method in class weka.classifiers.lazy.KStar: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.lazy.LWL: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AdaBoostM1: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AdditiveRegression: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Bagging: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.CostSensitiveClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.CVParameterSelection: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.FilteredClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.LogitBoost: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MultiClassClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.MultiScheme: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.RandomSubSpace: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.RegressionByDiscretization: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Stacking: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.Vote: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.misc.InputMappedClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.misc.SerializedClassifier: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.MultipleClassifiersCombiner: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.ParallelIteratedSingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.ParallelMultipleClassifiersCombiner: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableClassifier: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.DecisionTable: Parses the options for this object.
setOptions(String[]) - Method in class weka.classifiers.rules.JRip: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.OneR: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.rules.PART: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.SingleClassifierEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.HoeffdingTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.J48: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.LMT: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.m5.M5Base: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.M5P: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomForest: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.RandomTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.classifiers.trees.REPTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.AbstractClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.Canopy: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.CheckClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.Cobweb: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.EM: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.FarthestFirst: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.FilteredClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.HierarchicalClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.MakeDensityBasedClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.RandomizableClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.SimpleKMeans: Parses a given list of options.
setOptions(String[]) - Method in class weka.clusterers.SingleClustererEnhancer: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.Check: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.CheckGOE: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.CheckOptionHandler: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.CheckScheme: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.AbstractFileSaver: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.ArffSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.C45Saver: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.CSVLoader
setOptions(String[]) - Method in class weka.core.converters.CSVSaver: Valid options are:
setOptions(String[]) - Method in class weka.core.converters.DatabaseLoader: Sets the options.
setOptions(String[]) - Method in class weka.core.converters.DatabaseSaver: Sets the options.
setOptions(String[]) - Method in class weka.core.converters.JSONSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.LibSVMSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.MatlabSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.SVMLightSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.converters.TextDirectoryLoader: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.converters.XRFFSaver: Parses the options for this object.
setOptions(String[]) - Method in class weka.core.DictionaryBuilder: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.FilteredDistance: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.FindWithCapabilities: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.Javadoc: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.ListOptions: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.MinkowskiDistance: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.BallTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.BallTreeConstructor: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.balltrees.TopDownConstructor: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.CoverTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.KDTree: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.LinearNNSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.NormalizableDistance: Parses a given list of options.
setOptions(String[], Object, Class<?>) - Static method in class weka.core.Option: Sets options on the target object.
setOptions(String[]) - Method in interface weka.core.OptionHandler: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.OptionHandlerJavadoc: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.stemmers.SnowballStemmer: Parses the options.
setOptions(String[]) - Method in class weka.core.stopwords.AbstractFileBasedStopwords: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.stopwords.AbstractStopwords: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.stopwords.MultiStopwords: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.TechnicalInformationHandlerJavadoc: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.TestInstances: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.tokenizers.CharacterDelimitedTokenizer: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.tokenizers.NGramTokenizer: Parses a given list of options.
setOptions(String[]) - Method in class weka.core.tokenizers.Tokenizer: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.datagenerators.ClassificationGenerator: Sets the options.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.Agrawal: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.LED24: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.RandomRBF: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.classification.RDG1: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.regression.Expression: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.classifiers.regression.MexicanHat: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.clusterers.SubspaceCluster: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.ClusterGenerator: Sets the options.
setOptions(String[]) - Method in class weka.datagenerators.DataGenerator: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.datagenerators.RegressionGenerator: Sets the options.
setOptions(String[]) - Method in class weka.estimators.CheckEstimator: Parses a given list of options.
setOptions(String[]) - Method in class weka.estimators.Estimator: Parses a given list of options.
setOptions(String[]) - Method in class weka.estimators.UnivariateMixtureEstimator: Sets options based on the given array of strings.
setOptions(String[]) - Method in class weka.experiment.AveragingResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.ClassifierSplitEvaluator: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CrossValidationResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.CSVResultListener: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.DatabaseResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.Experiment: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.ExplicitTestsetResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.InstanceQuery: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.LearningRateResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.PairedTTester: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.RandomSplitResultProducer: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.RegressionSplitEvaluator: Parses a given list of options.
setOptions(String[]) - Method in class weka.experiment.ResultMatrix: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.filters.CheckSource: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.Filter: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.MultiFilter: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.AddClassification: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.AttributeSelection: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.ClassOrder: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.Discretize: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.NominalToBinary: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.attribute.PartitionMembership: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.instance.Resample: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.instance.SpreadSubsample: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AbstractTimeSeries: Parses a given list of options controlling the behaviour of this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Add: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddCluster: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddExpression: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddID: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddNoise: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddUserFields: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.AddValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.CartesianProduct: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ChangeDateFormat: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ClassAssigner: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ClusterMembership: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Copy: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.DateToNumeric: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Discretize: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.FirstOrder: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MathExpression: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeManyValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NominalToString: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Normalize: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericCleaner: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericToBinary: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericToDate: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericToNominal: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.NumericTransform: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.OrdinalToNumeric: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PotentialClassIgnorer: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Parses a list of options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RandomSubset: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Remove: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveByName: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveType: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RemoveUseless: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.Reorder: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingWithUserConstant: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SortLabels: Parses the options for this object.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToNominal: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.attribute.SwapValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Randomize: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemovePercentage: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveRange: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.Resample: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.ReservoirSample: Parses a given list of options.
setOptions(String[]) - Method in class weka.filters.unsupervised.instance.SubsetByExpression: Parses a given list of options.
setOptions(String[]) - Method in class weka.gui.explorer.AbstractPlotInstances: Sets the OptionHandler's options using the given list.
setOptions(String[]) - Method in class weka.gui.Main: Parses the options for this object.
setOptions(String[]) - Method in class weka.gui.scripting.Script: Parses a given list of options.
setOptionsForHierarchy(String[], Object, Class<?>) - Static method in class weka.core.Option: Sets options on the target object.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DefineFunction: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.DerivedField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.ParameterField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the optype property.
setOptype(OPTYPE) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the optype property.
setOrder(double) - Method in class weka.core.MinkowskiDistance: Sets the order.
setOrig(double) - Method in class weka.core.pmml.jaxbbindings.LinearNorm: Sets the value of the orig property.
setOriginalCoords(Vector<Point>) - Method in class weka.gui.beans.MetaBean: sets the vector containing the original coordinates (instances of class Point) for the inputs
setOutlierFactor(double) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Sets the factor for determining the thresholds for outliers.
setOutliers(OUTLIERTREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the outliers property.
setOutliers(OUTLIERTREATMENTMETHOD) - Method in class weka.core.pmml.jaxbbindings.NormContinuous: Sets the value of the outliers property.
setOutput(Output) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the output property.
setOutput(Output) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the output property.
setOutput(PrintWriter) - Method in class weka.datagenerators.DataGenerator: Sets the print writer.
setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.LinearRegression: Set whether to output additional statistics (such as std.
setOutputAdditionalStats(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegression: Set whether to output additional statistics (such as std.
setOutputClassification(boolean) - Method in class weka.filters.supervised.attribute.AddClassification: Set whether the classification of the classifier is output.
setOutputColumn(String) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the outputColumn property.
setOutputConfusionMatrix(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
setOutputDetailedInfo(boolean) - Method in class weka.attributeSelection.CorrelationAttributeEval: Set whether to output per-value correlation for nominal attributes
setOutputDirectory(File) - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Set the directory to save to
setOutputDistribution(boolean) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets whether to output the class distribution or not.
setOutputDistribution(boolean) - Method in class weka.filters.supervised.attribute.AddClassification: Set whether the Distribution of the classifier is output.
setOutputEntropyMetrics(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
setOutputErrorFlag(boolean) - Method in class weka.filters.supervised.attribute.AddClassification: Set whether the classification of the classifier is output.
setOutputFile(File) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets the output file to write to.
setOutputFile(File) - Method in class weka.classifiers.evaluation.output.prediction.InMemory: Ignored, as it does not generate any output.
setOutputFile(File) - Method in class weka.experiment.CrossValidationResultProducer: Set the value of OutputFile.
setOutputFile(File) - Method in class weka.experiment.CSVResultListener: Set the value of OutputFile.
setOutputFile(File) - Method in class weka.experiment.ExplicitTestsetResultProducer: Set the value of OutputFile.
setOutputFile(File) - Method in class weka.experiment.RandomSplitResultProducer: Set the value of OutputFile.
setOutputFilename(boolean) - Method in class weka.core.converters.TextDirectoryLoader: Sets whether the filename will be stored as an extra attribute.
setOutputFileName(String) - Method in class weka.experiment.CSVResultListener: Set the value of OutputFileName.
setOutputFilename(String) - Method in class weka.gui.GenericPropertiesCreator: sets the file to output the properties for the GEO to
setOutputFormat(int) - Method in class weka.core.Debug.Clock: sets the format of the output
setOutputFormatFromDialog() - Method in class weka.gui.experiment.ResultsPanel: displays the Dialog for the output format and sets the chosen settings, if the user approves.
setOutputItemSets(boolean) - Method in class weka.associations.Apriori: Sets whether itemsets are output as well
setOutputNeuron(String) - Method in class weka.core.pmml.jaxbbindings.NeuralOutput: Sets the value of the outputNeuron property.
setOutputOffsetMultiplier(boolean) - Method in class weka.filters.unsupervised.attribute.InterquartileRange: Set whether an additional attribute "Offset" is generated per Outlier/ExtremeValue attribute pair that lists the multiplier the value is off the median: value = median + 'multiplier' * IQR.
setOutputOutOfBagComplexityStatistics(boolean) - Method in class weka.classifiers.meta.Bagging: Sets whether complexity statistics are output when OOB estimation is performed.
setOutputPerClassInfoRetrievalStats(boolean) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Set whether to output per-class information retrieval statistics (nominal class only).
setOutputPerClassInfoRetrievalStats(boolean) - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Set whether to output per-class information retrieval statistics (nominal class only).
setOutputPerClassStats(boolean) - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
setOutputProbsForSVM(boolean) - Method in class weka.classifiers.functions.SGDText: Set whether to fit a logistic regression (itself trained using SGD) to the outputs of the SVM (if an SVM is being learned).
setOutputs(Vector<Object>) - Method in class weka.gui.beans.MetaBean
setOutputTypes(String) - Method in class weka.core.Debug.DBO: Switches the outputs on that are requested from the option O
setOutputWordCounts(boolean) - Method in class weka.core.DictionaryBuilder: Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
setOutputWordCounts(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
setOutputWordCounts(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether output instances contain 0 or 1 indicating word presence, or word counts.
setOverwriteWarning(boolean) - Method in class weka.gui.ConverterFileChooser: Whether a warning is popped up if the file that is to be saved already exists (only save dialog).
setOwner(CapabilitiesHandler) - Method in class weka.core.Capabilities: sets the owner of this capabilities object
setOwner(SimpleCLIPanel) - Method in class weka.gui.simplecli.AbstractCommand: Sets the owner.
setP(double) - Method in class weka.classifiers.BVDecomposeSegCVSub: Set the proportion of instances that are common between two training sets used to train a classifier.
setPackage(Package) - Method in class weka.core.packageManagement.PackageConstraint: Set the package that this constraint applies to.
setPackageHome(File) - Method in class weka.core.packageManagement.PackageManager: Set the location (directory) of installed packages.
setPackageManager(PackageManager) - Method in class weka.core.packageManagement.DefaultPackage: Set the package manager for this package
setPackageMetaData(Map<?, ?>) - Method in class weka.core.packageManagement.Package: Set the meta data for this package.
setPackageMetaDataElement(Object, Object) - Method in class weka.core.packageManagement.DefaultPackage: Adds a key, value pair to the meta data map.
setPackageMetaDataElement(Object, Object) - Method in class weka.core.packageManagement.Package: Adds a key, value pair to the meta data map.
setPackageRepositoryURL(URL) - Method in class weka.core.packageManagement.PackageManager: Set the URL to the repository of package meta data.
setPaint(Paint) - Method in class weka.gui.visualize.PostscriptGraphics
setPaintMode() - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
setPanelHeight(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the height of the visualization
setPanelWidth(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the width of the visualization
setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInArithmetic: Set the structure of the parameters that are expected as input by this function.
setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInMath: Set the structure of the parameters that are expected as input by this function.
setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.BuiltInString: Set the structure of the parameters that are expected as input by this function.
setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.DefineFunction: Set the structure of the parameters that are expected as input by this function.
setParameterDefs(ArrayList<Attribute>) - Method in class weka.core.pmml.Function: Set the structure of the parameters that are expected as input by this function.
setParameterName(String) - Method in class weka.core.pmml.jaxbbindings.PCell: Sets the value of the parameterName property.
setParameterName(String) - Method in class weka.core.pmml.jaxbbindings.PPCell: Sets the value of the parameterName property.
SetParent(int, int) - Method in class weka.classifiers.bayes.net.ParentSet: sets index parent of parent specified by index
setParent(ClusterGenerator) - Method in class weka.datagenerators.ClusterDefinition: sets the parent datagenerator this cluster belongs to
setParent(Container) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the new parent frame
setParent(Edge) - Method in class weka.gui.treevisualizer.Node: Set the value of parent.
setParentField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the parentField property.
setParentFrame(JFrame) - Method in class weka.gui.SetInstancesPanel: Sets the frame, this panel resides in.
setParentLevelField(String) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the parentLevelField property.
setParentSeparator(MarginCalculator.JunctionTreeSeparator) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
setParentWindow(Window) - Method in class weka.gui.beans.AssociatorCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.AttributeSummarizerCustomizer: Set the parent window of this dialog
setParentWindow(Window) - Method in class weka.gui.beans.ClassAssignerCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ClassifierCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ClassifierPerformanceEvaluatorCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ClassValuePickerCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ClustererCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.CrossValidationFoldMakerCustomizer
setParentWindow(Window) - Method in interface weka.gui.beans.CustomizerCloseRequester: A reference to the parent is passed in
setParentWindow(Window) - Method in class weka.gui.beans.DataVisualizerCustomizer: Set the parent window of this dialog
setParentWindow(Window) - Method in class weka.gui.beans.FilterCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.FlowByExpressionCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ImageSaverCustomizer: Set the parent window of this dialog
setParentWindow(Window) - Method in class weka.gui.beans.IncrementalClassifierEvaluatorCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.JoinCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.LoaderCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.ModelPerformanceChartCustomizer: Set the parent window of this dialog
setParentWindow(Window) - Method in class weka.gui.beans.NoteCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.PredictionAppenderCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.SaverCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.SerializedModelSaverCustomizer
setParentWindow(Window) - Method in class weka.gui.beans.SorterCustomizer: Set the parent window for this dialog
setParentWindow(Window) - Method in class weka.gui.beans.SubstringLabelerCustomizer: Set a reference to the parent window/dialog containing this panel
setParentWindow(Window) - Method in class weka.gui.beans.SubstringReplacerCustomizer: Set a reference to the parent window/dialog containing this panel
setParentWindow(Window) - Method in class weka.gui.beans.TextSaverCustomizer: Set the parent window of this dialog
setParentWindow(Window) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Set the parent window for this viewer
setParentWindow(Window) - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Set the parent window for this viewer
setPartialScore(Double) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the partialScore property.
setPartition(Partition) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the partition property.
setPartition(Partition) - Method in class weka.core.pmml.jaxbbindings.TargetValue: Sets the value of the partition property.
setPartitionGenerator(PartitionGenerator) - Method in class weka.filters.supervised.attribute.PartitionMembership: Set the generator for use in filtering
setPassword(String) - Method in interface weka.core.converters.DatabaseConverter
setPassword(String) - Method in class weka.core.converters.DatabaseLoader: Sets user password for the database
setPassword(String) - Method in class weka.core.converters.DatabaseSaver: Sets the database password.
setPassword(String) - Method in class weka.experiment.DatabaseUtils: Set the database password.
setPassword(String) - Method in class weka.gui.sql.ConnectionPanel: sets the Password.
setPasteBuffer(StringBuffer) - Method in class weka.gui.beans.KnowledgeFlowApp: Set the contents of the "paste" buffer and enable the paste from cliboard toolbar button
setPattern(SelectedTag) - Method in class weka.datagenerators.clusterers.BIRCHCluster: Sets the pattern type.
setPayloadElement(String, Object) - Method in class weka.knowledgeflow.Data: Set a payload element to encapsulate in this Data object.
setPCol(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the pCol property.
setPercent(int) - Method in class weka.filters.unsupervised.attribute.AddNoise: Sets the size of noise data, as a percentage of the original set.
setPercent(double) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets the percent the attributes (dimensions) of the data should be reduced to
setPercent() - Method in class weka.gui.visualize.MatrixPanel: Calculates the percentage to resample
setPercentage(double) - Method in class weka.filters.unsupervised.instance.RemovePercentage: Sets the percentage of intances to select.
setPercentCompleted(int) - Method in class weka.gui.boundaryvisualizer.RemoteResult: Set the progress for this row so far
setPeriod(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the period property.
setPeriodicPruning(int) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set how often to prune the dictionary
setPeriodicPruning(int) - Method in class weka.classifiers.functions.SGDText: Set how often to prune the dictionary
setPeriodicPruning(long) - Method in class weka.core.converters.DictionarySaver: Sets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
setPeriodicPruning(long) - Method in class weka.core.DictionaryBuilder: Sets the rate (number of instances) at which the dictionary is periodically pruned
setPeriodicPruning(double) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets the rate at which the dictionary is periodically pruned, as a percentage of the dataset size.
setPeriodicPruningRate(int) - Method in class weka.clusterers.Canopy: Set the how often to prune low density canopies during training
setPerspectiveName(String) - Method in class weka.knowledgeflow.steps.SendToPerspective
setPerspectivesToolbarAlwaysHidden(boolean) - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Set whether the perspectives toolbar should always be hidden
setPerspectivesToolbarVisibleOnStartup(boolean) - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Set whether the perspectives toolbar should be visible in the GUI at application startup
setPerspectiveToolbarAlwaysHidden(Settings) - Method in class weka.gui.PerspectiveManager: Set whether the perspectives toolbar should always be hidden.
setPerspectiveToolBarIsVisible(boolean) - Method in class weka.gui.PerspectiveManager
setPerturbationFraction(double) - Method in class weka.datagenerators.classifiers.classification.Agrawal: Sets the perturbation fraction.
setPhase(BigInteger) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the phase property.
setPhi(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Sets the value of the phi property.
setPickList(List<String>) - Method in class weka.core.Settings.SettingKey: Set the optional pick list for the setting
setPivot(Instance) - Method in class weka.core.neighboursearch.balltrees.BallNode: Sets the pivot/centre of this nodes ball.
setPixHeight(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the height of a pixel
setPixWidth(double) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the width of a pixel
setPlotBackgroundColour(Color) - Method in class weka.gui.visualize.MatrixPanel: Set the background colour for the cells in the matrix
setPlotCompanion(Plot2DCompanion) - Method in class weka.gui.visualize.Plot2D: Set a companion class.
setPlotList(ArrayList<PlotData2D>) - Method in class weka.gui.visualize.LegendPanel: Set the list of plots to generate legend entries for
setPlotName(String) - Method in class weka.gui.visualize.PlotData2D: Set the name of this plot
setPlotNameHTML(String) - Method in class weka.gui.visualize.PlotData2D: Set the plot name for use in a tool tip text.
setPlotShapes(ArrayList<Integer>) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Set the vector of plot shapes to use;
setPlotSize(int) - Method in class weka.gui.visualize.MatrixPanel: Set the plot size
setPlotSizes(ArrayList<Object>) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Set the vector of plot sizes to use
setPlotTrainingData(boolean) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set whether to superimpose the training data plot
setPlotTrainingData(boolean) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set whether to superimpose the training data points on the plot or not
setPlus(int, double) - Method in class weka.core.matrix.DoubleVector: Adds a value to an element
setPMMLVersion(Document) - Method in class weka.classifiers.pmml.consumer.PMMLClassifier: Set the version of PMML used for this model.
setPMMLVersion(Document) - Method in interface weka.core.pmml.PMMLModel: Set the version of the PMML.
setPoints(MiddleOutConstructor.TempNode, int, int, int[]) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the points of an anchor node.
setPointSize(int) - Method in class weka.gui.visualize.MatrixPanel: Set the point size for the plots
setPointSizeProportionalToMargin(boolean) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Set whether the point size should be proportional to the prediction margin (classification only).
setPoissonDistribution(PoissonDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate: Sets the value of the poissonDistribution property.
setPoissonDistribution(PoissonDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the poissonDistribution property.
setPoolSize(int) - Method in class weka.attributeSelection.CfsSubsetEval: Sets the number of threads
setPoolSize(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Sets the number of threads
setPoolSize(int) - Method in class weka.classifiers.meta.LogitBoost: Sets the number of threads
setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setPopulationSize(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setPopup(JPopupMenu) - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: sets the JPopupMenu to display again after closing the dialog.
setPosition(int, int, int) - Method in class weka.classifiers.bayes.net.EditableBayesNet: set position of node
setPosition(int, int, int, ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: Set position of node.
setPositiveIndex(int) - Method in class weka.associations.FPGrowth: Set the index of the attribute value to consider as positive for binary attributes in normal dense instances.
setPositiveTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC: Sets the value of the positiveTargetFieldDisplayValue property.
setPositiveTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.ROC: Sets the value of the positiveTargetFieldValue property.
setPostProcessor(CheckScheme.PostProcessor) - Method in class weka.core.CheckScheme: sets the PostProcessor to use
setPostProcessor(CheckEstimator.PostProcessor) - Method in class weka.estimators.CheckEstimator: sets the PostProcessor to use
setPParameter(double) - Method in class weka.core.pmml.jaxbbindings.Minkowski: Sets the value of the pParameter property.
setPreBuiltClassifiers(File[]) - Method in class weka.classifiers.meta.Vote: Set the paths to pre-built serialized classifiers to load and include in the ensemble
setPrecision(Double) - Method in class weka.core.pmml.jaxbbindings.VerificationField: Sets the value of the precision property.
setPreComputeCorrelationMatrix(boolean) - Method in class weka.attributeSelection.CfsSubsetEval: Set whether to pre-compute the full correlation matrix at the outset, rather than computing individual correlations lazily (as needed) during the search.
SetPredicate - Class in weka.core.pmml.jaxbbindings: Java class for SetPredicate element declaration.
SetPredicate() - Constructor for class weka.core.pmml.jaxbbindings.SetPredicate
setPredictionIntervals(double[][]) - Method in class weka.classifiers.evaluation.NumericPrediction: Sets the prediction intervals for this prediction.
setPredictorName(String) - Method in class weka.core.pmml.jaxbbindings.PPCell: Sets the value of the predictorName property.
setPredTargetColumn(boolean) - Method in class weka.experiment.ClassifierSplitEvaluator: Set the flag for prediction and target output.
setPreferredScrollableViewportSize(Dimension) - Method in class weka.gui.AttributeSelectionPanel
setPrefix(String) - Method in class weka.gui.beans.SerializedModelSaver: Set the prefix to prepend to the model file names.
setPreprocessing(Filter) - Method in class weka.filters.unsupervised.attribute.KernelFilter: Sets the filter to use for preprocessing (use the AllFilter for no preprocessing)
setPreserveInstancesOrder(boolean) - Method in class weka.clusterers.SimpleKMeans: Sets whether order of instances must be preserved.
setPreserveOrder(boolean) - Method in class weka.gui.beans.CrossValidationFoldMaker: Sets whether the order of the incoming instances is to be preserved under cross-validation (no randomization or stratification is done in this case).
setPreserveOrder(boolean) - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Set whether to preserve the order of the input instances when creatinbg the folds
setPreserveOrder(boolean) - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Set whether to preserve the order of the instances or not
setPreserveOrderInPercentageSplitEvaluation(boolean) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of PreserveOrderInPercentageSplitEvaluation.
setPrintClassifiers(boolean) - Method in class weka.classifiers.meta.Bagging: Set whether to print the individual ensemble classifiers in the output
setPrintColNames(boolean) - Method in class weka.experiment.ResultMatrix: sets whether the column names or numbers instead are printed.
setPrintLeafModels(boolean) - Method in class weka.classifiers.trees.HoeffdingTree
setPrintNewick(boolean) - Method in class weka.clusterers.HierarchicalClusterer
setPrintRowNames(boolean) - Method in class weka.experiment.ResultMatrix: sets whether the row names or numbers instead are printed deactivating automatically sets m_EnumerateColNames to TRUE.
setPriorProbability(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.TargetValue: Sets the value of the priorProbability property.
setPriors(Instances) - Method in class weka.classifiers.evaluation.Evaluation: Sets the class prior probabilities.
setPriors(Instances) - Method in class weka.classifiers.Evaluation: Sets the class prior probabilities.
setProbability(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Sets the value of the probability property.
setProbability(double) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Set the probability to use.
setProducer(String) - Method in class weka.associations.AssociationRules: Set a textual description of the scheme that produced these rules.
setProlog(boolean) - Method in class weka.core.OptionHandlerJavadoc: sets whether to add the "Valid options are..." prolog
setProlog(boolean) - Method in class weka.core.TechnicalInformationHandlerJavadoc: sets whether to add the "Valid options are..." prolog
SetPropertiesFromEnvironment - Class in weka.knowledgeflow.steps: Step that accesses property values stored in the flow environment and attempts to set them on the algorithm-based step that it is connected to.
SetPropertiesFromEnvironment() - Constructor for class weka.knowledgeflow.steps.SetPropertiesFromEnvironment
setProperty(String) - Method in class weka.core.pmml.jaxbbindings.Value: Sets the value of the property property.
setProperty(String, String) - Method in class weka.core.ProtectedProperties: Overrides a method to prevent the properties from being modified.
setPropertyArray(Object) - Method in class weka.experiment.Experiment: Sets the array of values to set the custom property to.
setPropertyArray(Object) - Method in class weka.experiment.RemoteExperiment: Sets the array of values to set the custom property to.
setPropertyGroupingCategory(String) - Method in class weka.gui.PropertySheetPanel
setPropertyPath(PropertyNode[]) - Method in class weka.experiment.Experiment: Sets the path of properties taken to get to the custom property to iterate over.
setPropertyPath(PropertyNode[]) - Method in class weka.experiment.RemoteExperiment: Sets the path of properties taken to get to the custom property to iterate over.
setPropsInternalRep(String) - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
setPRow(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the pRow property.
setProxy(Proxy) - Method in class weka.core.packageManagement.PackageManager: Set a proxy to use for accessing the internet (default is no proxy).
setProxyAuthentication(URL) - Method in class weka.core.packageManagement.PackageManager: Sets an new default Authenticator that will return the values set through setProxyUsername() and setProxyPassword() (if applicable).
setProxyPassword(String) - Method in class weka.core.packageManagement.PackageManager: Set the password for authentication with the proxy.
setProxyUsername(String) - Method in class weka.core.packageManagement.PackageManager: Set the user name for authentication with the proxy.
setPruningMethod(SelectedTag) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets the method used to for pruning.
setPValue(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the pValue property.
setPValueAlpha(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the pValueAlpha property.
setPValueFinal(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the pValueFinal property.
setPValueInitial(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the pValueInitial property.
setQuality(float) - Method in class weka.gui.visualize.JPEGWriter: sets the quality the JPEG is saved in.
setQuantileLimit(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.Quantile: Sets the value of the quantileLimit property.
setQuantileValue(double) - Method in class weka.core.pmml.jaxbbindings.Quantile: Sets the value of the quantileValue property.
setQuery(String) - Method in class weka.core.converters.DatabaseLoader: Sets the query to execute against the database
setQuery(String) - Method in class weka.experiment.InstanceQuery: Set the query to execute against the database
setQuery(String) - Method in class weka.gui.sql.QueryPanel: sets the query in the textarea.
setQueryPanel(QueryPanel) - Method in class weka.gui.sql.ResultPanel: sets the QueryPanel to use for displaying the query
setQuoteDelimiters(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the quote delimiter characters to use.
setQuoteEscape(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the character to use for escaping a quote character.
setRadius(double) - Method in class weka.core.neighboursearch.balltrees.BallNode: Sets the radius of the node's ball.
setRaiseExceptionOnCommandFailure(boolean) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set to raise an exception when a command fails completely (i.e.
setRandom(Random) - Method in class weka.datagenerators.DataGenerator: Sets the random generator.
setRandomizeData(boolean) - Method in class weka.experiment.ExplicitTestsetResultProducer: Set to true if dataset is to be randomized.
setRandomizeData(boolean) - Method in class weka.experiment.RandomSplitResultProducer: Set to true if dataset is to be randomized
setRandomLiftGraph(RandomLiftGraph) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the randomLiftGraph property.
setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.global.K2: Set random order flag
setRandomOrder(boolean) - Method in class weka.classifiers.bayes.net.search.local.K2: Set random order flag
setRandomSeed(int) - Method in class weka.classifiers.functions.SMO: Set the value of randomSeed.
setRandomSeed(int) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Sets the seed for random number generator.
setRandomSeed(int) - Method in class weka.filters.supervised.instance.Resample: Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.supervised.instance.SpreadSubsample: Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.unsupervised.attribute.AddNoise: Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Randomize: Set the random number generator seed value.
setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.Resample: Sets the random number seed.
setRandomSeed(int) - Method in class weka.filters.unsupervised.instance.ReservoirSample: Sets the random number seed.
setRandomWidthFactor(double) - Method in class weka.classifiers.meta.MultiClassClassifier: Sets the multiplier when generating random codes.
setRange(String) - Method in class weka.core.InstanceComparator: Sets the attribute range to use for comparison.
setRangeConstraint(String, VersionPackageConstraint.VersionComparison, String, VersionPackageConstraint.VersionComparison) - Method in class weka.core.packageManagement.VersionRangePackageConstraint: Set the range bounds and constraints.
setRanges(String) - Method in class weka.core.Range: Sets the ranges from a string representation.
setRanges(Range[]) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Sets the list of possible Ranges to choose from.
setRank(BigInteger) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the rank property.
setRankBasis(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the rankBasis property.
setRanking(boolean) - Method in class weka.attributeSelection.AttributeSelection: produce a ranking (if possible with the set search and evaluator)
setRanking(int[][]) - Method in class weka.experiment.ResultMatrix: sets the ranking data based on the wins.
setRankingQuality(Double) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the rankingQuality property.
setRankOrder(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the rankOrder property.
setRawOutput(boolean) - Method in class weka.experiment.CrossValidationResultProducer: Set to true if raw split evaluator output is to be saved
setRawOutput(boolean) - Method in class weka.experiment.ExplicitTestsetResultProducer: Set to true if raw split evaluator output is to be saved.
setRawOutput(boolean) - Method in class weka.experiment.RandomSplitResultProducer: Set to true if raw split evaluator output is to be saved
setReadable(String) - Method in class weka.core.Tag: Sets the string description of the Tag.
setReadIncrementally(boolean) - Method in class weka.gui.SetInstancesPanel: Sets whether or not instances should be read incrementally by the Loader.
setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffPanel: sets whether the model is read-only
setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets whether the model is read-only
setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffTable: sets whether the model is read-only
setReadOnly(boolean) - Method in class weka.gui.arffviewer.ArffTableModel: sets whether the model is read-only
setREALSparseArray(REALSparseArray) - Method in class weka.core.pmml.jaxbbindings.VectorInstance: Sets the value of the realSparseArray property.
setReasonCode(String) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the reasonCode property.
setReasonCode(String) - Method in class weka.core.pmml.jaxbbindings.Characteristic: Sets the value of the reasonCode property.
setReasonCodeAlgorithm(String) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the reasonCodeAlgorithm property.
setRecordCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Sets the value of the recordCount property.
setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.Node: Sets the value of the recordCount property.
setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.RuleSet: Sets the value of the recordCount property.
setRecordCount(double) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Sets the value of the recordCount property.
setRecordCount(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the recordCount property.
setRecordCount(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the recordCount property.
setReducedErrorPruning(boolean) - Method in class weka.classifiers.rules.PART: Set the value of reducedErrorPruning.
setReducedErrorPruning(boolean) - Method in class weka.classifiers.trees.J48: Set the value of reducedErrorPruning.
setReduceNumberOfDistanceCalcsViaCanopies(boolean) - Method in class weka.clusterers.SimpleKMeans: Set whether to use canopies to reduce the number of distance computations required
setRefer(String) - Method in class weka.gui.treevisualizer.Node: Set the value of refer.
SetReference - Class in weka.core.pmml.jaxbbindings: Java class for SetReference element declaration.
SetReference() - Constructor for class weka.core.pmml.jaxbbindings.SetReference
setReferencePoint(Double) - Method in class weka.core.pmml.jaxbbindings.Parameter: Sets the value of the referencePoint property.
setRefreshFreq(int) - Method in class weka.gui.beans.StripChart: Set how often (in x axis points) to refresh the display
setRefreshFreq(int) - Method in class weka.knowledgeflow.steps.StripChart: Set how often (in x axis points) to refresh the display
setRefreshWidth(int) - Method in class weka.gui.beans.StripChart: Set how many pixels to shift the plot by every time a point is plotted
setRefreshWidth(int) - Method in class weka.knowledgeflow.steps.StripChart: Set how many pixels to shift the plot by every time a point is plotted
setRegex(boolean) - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Set whether this is a regular expression match or not
setRegex(boolean) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Set whether this is a regular expression match or not
setRegexMatch(String) - Method in class weka.filters.RenameRelation: Set the match string for regex modifications
setRegexMatch(String) - Method in class weka.knowledgeflow.steps.AlterRelationName: Set the match string for regex modifications
setRegOptimizer(RegOptimizer) - Method in class weka.classifiers.functions.SMOreg: sets the learning algorithm
setRegressionModel(RegressionModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the regressionModel property.
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.Rule: Set the value of regressionTree.
setRegressionTree(boolean) - Method in class weka.classifiers.trees.m5.RuleNode: Set the value of regressionTree.
setRelation(String) - Method in class weka.core.TestInstances: sets the name of the relation
setRelationalClassFormat(Instances) - Method in class weka.core.TestInstances: sets the structure for the relational class attribute
setRelationalFormat(int, Instances) - Method in class weka.core.TestInstances: sets the structure for the bags for the relational attribute
setRelationFind(String) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the regular expression to use on the relation name.
setRelationForTableName(boolean) - Method in class weka.core.converters.DatabaseSaver: En/Dis-ables that the relation name is used for the name of the table (default enabled).
setRelationName(String) - Method in class weka.core.Instances: Sets the relation's name.
setRelationName(String) - Method in class weka.datagenerators.DataGenerator: Sets the relation name the dataset should have.
setRelationNameForFilename(boolean) - Method in class weka.gui.beans.Saver: Set whether to use the relation name as the primary part of the filename.
setRelationNameForFilename(boolean) - Method in class weka.knowledgeflow.steps.Saver: Set whether to use the relation name as the primary part of the filename.
setRelationReplace(String) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the replacement string to use on the relation name.
setRemoteHosts(DefaultListModel) - Method in class weka.experiment.RemoteExperiment: Set the list of remote host names
setRemoteHosts(Vector<String>) - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Set a list of host names of machines to distribute processing to
setRemoveAllMissingCols(boolean) - Method in class weka.associations.Apriori: Remove columns containing all missing values.
setRemoveClassColumn(boolean) - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Set whether the class column should be removed from the data.
setRemoveFilter(Remove) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities
setRemoveFilterName(boolean) - Method in class weka.experiment.ResultMatrix: sets whether to remove the filter classname from the dataset name.
setRemoveOldClass(boolean) - Method in class weka.filters.supervised.attribute.AddClassification: Set whether the old class attribute is removed.
setRemoveUnused(boolean) - Method in class weka.filters.unsupervised.attribute.PartitionedMultiFilter: Sets whether unused attributes (ones that are not covered by any of the ranges) are removed from the output.
setRenderingHint(RenderingHints.Key, Object) - Method in class weka.gui.visualize.PostscriptGraphics
setRenderingHints(Map<?, ?>) - Method in class weka.gui.visualize.PostscriptGraphics
setRenderingListener(BoundaryPlotter.RenderingUpdateListener) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set a listener to receive rendering updates
setReplace(String) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Sets the regular expression to replace matching attribute names with.
setReplace(String) - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Set the replace string
setReplaceAll(boolean) - Method in class weka.filters.RenameRelation: Set whether to replace all regular expression matches, or just the first.
setReplaceAll(boolean) - Method in class weka.filters.unsupervised.attribute.RenameAttribute: Sets whether to replace all occurrences or just the first one.
setReplaceAll(boolean) - Method in class weka.knowledgeflow.steps.AlterRelationName: Set whether to replace all regular expression matches, or just the first.
setReplaceMissingValues(boolean) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets either to use replace missing values filter or not
setRepresentCopiesUsingWeights(boolean) - Method in class weka.classifiers.meta.Bagging: Set whether copies of instances are represented using weights rather than explicitly.
setRepresentCopiesUsingWeights(boolean) - Method in class weka.classifiers.trees.RandomForest: This method only accepts true as its argument
setRescaleConstant(Double) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the rescaleConstant property.
setRescaleFactor(Double) - Method in class weka.core.pmml.jaxbbindings.Target: Sets the value of the rescaleFactor property.
setReset(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: This sets the network up to be able to reset itself with the current settings and the learning rate at half of what it is currently.
setReset(boolean) - Method in class weka.gui.beans.ChartEvent: Set the reset flag
setResetIncrementalClassifier(boolean) - Method in class weka.gui.beans.Classifier: Set whether to reset (by calling buildClassifier()) an incremental classifier, and thus discarding any previously learned model, before processing the first instance in the incoming stream.
setResetIncrementalClassifier(boolean) - Method in class weka.knowledgeflow.steps.Classifier: Set whether to reset an incremental classifier at the start of an incoming instance stream
setResetValue(Double) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the resetValue property.
setResourceIntensive(boolean) - Method in class weka.knowledgeflow.StepTask: Set whether this StepTask is resource intensive (cpu/memory) or not.
setResult(T) - Method in class weka.knowledgeflow.ExecutionResult: Set the result generated by the StepTask
setResultKeyFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setResultListener(ResultListener) - Method in class weka.experiment.AveragingResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.CrossValidationResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.DatabaseResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.Experiment: Sets the result listener where results will be sent.
setResultListener(ResultListener) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.LearningRateResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.RandomSplitResultProducer: Sets the object to send results of each run to.
setResultListener(ResultListener) - Method in class weka.experiment.RemoteExperiment: Sets the result listener where results will be sent.
setResultListener(ResultListener) - Method in interface weka.experiment.ResultProducer: Sets the object to send results of each run to.
setResultMatrix(ResultMatrix) - Method in class weka.experiment.PairedTTester: Sets the matrix to use to produce the output.
setResultMatrix(ResultMatrix) - Method in interface weka.experiment.Tester: Sets the matrix to use to produce the output.
setResultMatrix(ResultMatrix) - Method in class weka.gui.experiment.OutputFormatDialog: Sets the matrix to use as initial selected output format.
setResultProducer(ResultProducer) - Method in class weka.experiment.AveragingResultProducer: Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.DatabaseResultProducer: Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.Experiment: Set the result producer used for the current experiment.
setResultProducer(ResultProducer) - Method in class weka.experiment.LearningRateResultProducer: Set the ResultProducer.
setResultProducer(ResultProducer) - Method in class weka.experiment.RemoteExperiment: Set the result producer used for the current experiment.
setResultsetKeyColumns(Range) - Method in class weka.experiment.PairedTTester: Set the value of ResultsetKeyColumns.
setResultsetKeyColumns(Range) - Method in interface weka.experiment.Tester: Set the value of ResultsetKeyColumns.
setResultsPanel(ResultsPanel) - Method in class weka.gui.experiment.RunPanel: Sets the pointer to the results panel.
setResume(boolean) - Method in class weka.classifiers.functions.MultilayerPerceptron: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setResume(boolean) - Method in interface weka.classifiers.IterativeClassifier: If called with argument true then the classifier will be able to be trained further (with more iterations) at a later date.
setResume(boolean) - Method in class weka.classifiers.meta.AdaBoostM1: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setResume(boolean) - Method in class weka.classifiers.meta.AdditiveRegression: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setResume(boolean) - Method in class weka.classifiers.meta.FilteredClassifier: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setResume(boolean) - Method in class weka.classifiers.meta.LogitBoost: If called with argument true, then the next time done() is called the model is effectively "frozen" and no further iterations can be performed
setRetainStringVals(boolean) - Method in class weka.core.converters.ArffLoader: Set whether to retain the values of string attributes in memory (in the header) when reading incrementally.
setRetainStringValues(boolean) - Method in class weka.core.converters.ArffLoader.ArffReader: Set whether to retain the values of string attributes in memory (in the header) when reading incrementally.
setRetrieval(int) - Method in class weka.core.converters.AbstractLoader: Sets the retrieval mode.
setRetrieval(int) - Method in class weka.core.converters.AbstractSaver: Sets the retrieval mode.
setRetrieval(int) - Method in interface weka.core.converters.Loader: Sets the retrieval mode.
setRetrieval(int) - Method in interface weka.core.converters.Saver: Sets the retrieval mode
setRHSIsAnAttribute(boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Set whether the RHS is an attribute rather than a constant
setRHSOperand(String) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause: Set the rhs operand
setRidge(double) - Method in class weka.classifiers.functions.LinearRegression: Set the value of Ridge.
setRidge(double) - Method in class weka.classifiers.functions.Logistic: Sets the ridge in the log-likelihood.
setRidge(double) - Method in class weka.estimators.MultivariateGaussianEstimator: Set the value of Ridge.
setRightMargin(Double) - Method in class weka.core.pmml.jaxbbindings.Interval: Sets the value of the rightMargin property.
setRMSE(Double) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Sets the value of the rmse property.
setROC(ROC) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the roc property.
setROCGraph(ROCGraph) - Method in class weka.core.pmml.jaxbbindings.ROC: Sets the value of the rocGraph property.
setROCString(String) - Method in class weka.gui.visualize.ThresholdVisualizePanel: Set the string with ROC area
setRoot(boolean) - Method in class weka.gui.treevisualizer.Node: Set the value of root.
setRootMeanSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the rootMeanSquaredError property.
setRootNode(String) - Method in class weka.core.xml.XMLDocument: sets the root node to use in the XML output.
setRow(int, double[]) - Method in class weka.core.Matrix: Deprecated.

Sets a row of the matrix to the given row.
setRow(BigInteger) - Method in class weka.core.pmml.jaxbbindings.MatCell: Sets the value of the row property.
setRowHidden(int, boolean) - Method in class weka.experiment.ResultMatrix: sets the hidden status of the row (if the index is valid).
setRowName(int, String) - Method in class weka.experiment.ResultMatrix: sets the name of the row (if the index is valid).
setRowNameWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the row names (0 = optimal).
setRowNumber(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the row number for this sub task
setRowOrder(int[]) - Method in class weka.experiment.ResultMatrix: sets the ordering of the rows, null means default.
setRsource(String) - Method in class weka.gui.treevisualizer.Edge: Set the value of rsource.
setRSquared(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the rSquared property.
setRtarget(String) - Method in class weka.gui.treevisualizer.Edge: Set the value of rtarget.
setRuleFeature(RULEFEATURE) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the ruleFeature property.
setRules(List<AssociationRule>) - Method in class weka.associations.AssociationRules: Set the rules to use.
setRules(List<AssociationRule>) - Method in class weka.associations.FilteredAssociationRules: Set the rules to use.
setRuleset(ArrayList<Rule>) - Method in class weka.classifiers.rules.RuleStats: Set the ruleset of the stats, overwriting the old one if any
setRuleSetModel(RuleSetModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the ruleSetModel property.
setRulesMustContain(String) - Method in class weka.associations.FPGrowth: Set the comma separated list of items that rules must contain in order to be output.
setRunColumn(int) - Method in class weka.experiment.PairedTTester: Set the value of RunColumn.
setRunColumn(int) - Method in interface weka.experiment.Tester: Set the value of RunColumn.
setRunLower(int) - Method in class weka.experiment.Experiment: Set the lower run number for the experiment.
setRunLower(int) - Method in class weka.experiment.RemoteExperiment: Set the lower run number for the experiment.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Sets the m_nRuns.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Sets the number of runs
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Sets the m_nRuns.
setRuns(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Sets the number of runs
setRunUpper(int) - Method in class weka.experiment.Experiment: Set the upper run number for the experiment.
setRunUpper(int) - Method in class weka.experiment.RemoteExperiment: Set the upper run number for the experiment.
setSample(Double) - Method in class weka.core.pmml.jaxbbindings.COUNTTABLETYPE: Sets the value of the sample property.
setSamplePeriod(int) - Method in class weka.gui.beans.StreamThroughput: Set the sampling period (in milliseconds) to compute througput over
setSampleSize(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Set the number of instances to sample for attribute estimation
setSampleSize(int) - Method in class weka.filters.unsupervised.instance.ReservoirSample: Sets the size of the subsample.
setSampleSizePercent(double) - Method in class weka.filters.supervised.instance.Resample: Sets the size of the subsample, as a percentage of the original set.
setSampleSizePercent(double) - Method in class weka.filters.unsupervised.instance.Resample: Sets the size of the subsample, as a percentage of the original set.
setSaveBinaryDictionary(boolean) - Method in class weka.core.converters.DictionarySaver: Set whether to save the dictionary as a binary serialized dictionary, rather than a plain text one
setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintableComponent: sets the title for the save dialog.
setSaveDialogTitle(String) - Method in interface weka.gui.visualize.PrintableHandler: sets the title for the save dialog
setSaveDialogTitle(String) - Method in class weka.gui.visualize.PrintablePanel: sets the title for the save dialog
setSaveDictionaryInBinaryForm(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set whether to save the dictionary in binary serialized form rather than as plain text
setSaveForVisualization(boolean) - Method in class weka.gui.explorer.ClassifierErrorsPlotInstances: Sets whether the instances are saved for visualization or only evaluation of the prediction is to happen.
setSaveInstanceData(boolean) - Method in class weka.classifiers.trees.J48: Set whether instance data is to be saved.
setSaveInstanceData(boolean) - Method in class weka.clusterers.Cobweb: Set the value of saveInstances.
setSaveInstances(boolean) - Method in class weka.classifiers.trees.M5P: Set whether to save instance data at each node in the tree for visualization purposes
setSaver(Saver) - Method in class weka.knowledgeflow.steps.Saver: Set the saver instance that is wrapped by this step.
setSaverTemplate(Saver) - Method in class weka.gui.beans.Saver: Set the loader to use
setScale(double) - Method in class weka.filters.unsupervised.attribute.Normalize: Sets the scaling factor.
setScale(double, double) - Method in class weka.gui.visualize.JComponentWriter: sets the scale factor - is ignored since we always create a screenshot!
setScale(double, double) - Method in class weka.gui.visualize.PrintableComponent: sets the scale factor.
setScale(double, double) - Method in interface weka.gui.visualize.PrintableHandler: sets the scale factor
setScale(double, double) - Method in class weka.gui.visualize.PrintablePanel: sets the scale factor
setScaleWidthToFit(boolean) - Method in class weka.gui.DocumentPrinting: Sets whether to scale the width to fit.
setScalingEnabled(boolean) - Method in class weka.gui.visualize.JComponentWriter: sets whether to enable scaling
setScore(String) - Method in class weka.core.pmml.jaxbbindings.Node: Sets the value of the score property.
setScore(String) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the score property.
setScorecard(Scorecard) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the scorecard property.
setScoreType(SelectedTag) - Method in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: set quality measure to be used in searching for networks.
setSearch(ASSearch) - Method in class weka.attributeSelection.AttributeSelection: set the search method
setSearch(ASSearch) - Method in class weka.attributeSelection.CheckAttributeSelection: Set the search method to test.
setSearch(ASSearch) - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Sets the search method
setSearch(ASSearch) - Method in class weka.classifiers.rules.DecisionTable: Sets the search method to use
setSearch(ASSearch) - Method in class weka.filters.supervised.attribute.AttributeSelection: Set search class
setSearchAlgorithm(SearchAlgorithm) - Method in class weka.classifiers.bayes.BayesNet: Set the SearchAlgorithm used in searching for network structures.
setSearchBackwards(boolean) - Method in class weka.attributeSelection.GreedyStepwise: Set whether to search backwards instead of forwards
setSearchMethod(NearestNeighbourSearch) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Sets the search method
setSearchStrategy(ASSearch) - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Set the search strategy wrapped by this step (calls setWrappedAlgorithm)
setSearchString(String) - Method in class weka.gui.arffviewer.ArffTable: sets the search string to look for in the table, NULL or "" disables the search
setSearchTermination(int) - Method in class weka.attributeSelection.BestFirst: Set the numnber of non-improving nodes to consider before terminating search.
setSeasonalityExpoSmooth(SeasonalityExpoSmooth) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Sets the value of the seasonalityExpoSmooth property.
setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.MergeTwoValues: Sets index of the second value used.
setSecondValueIndex(String) - Method in class weka.filters.unsupervised.attribute.SwapValues: Sets index of the second value used.
setSeed(int) - Method in class weka.attributeSelection.AttributeSelection: set the seed for use in cross validation
setSeed(int) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the seed to use for cross validation
setSeed(int) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set the random seed used to randomize the data before performing a percentage split
setSeed(int) - Method in class weka.attributeSelection.OneRAttributeEval: Set the random number seed for cross validation
setSeed(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Set the random number seed for randomly sampling instances.
setSeed(int) - Method in class weka.attributeSelection.WrapperSubsetEval: Set the seed to use for cross validation
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.RepeatedHillClimber: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.RepeatedHillClimber: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.BVDecompose: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.BVDecomposeSegCVSub: Sets the random number seed
setSeed(int) - Method in class weka.classifiers.evaluation.EvaluationUtils: Sets the seed for randomization during cross-validation
setSeed(int) - Method in class weka.classifiers.functions.MultilayerPerceptron: This seeds the random number generator, that is used when a random number is needed for the network.
setSeed(int) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Sets the seed value for the random number generator
setSeed(int) - Method in class weka.classifiers.functions.VotedPerceptron: Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.meta.MultiScheme: Sets the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableClassifier: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableIteratedSingleClassifierEnhancer: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableMultipleClassifiersCombiner: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableParallelMultipleClassifiersCombiner: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.RandomizableSingleClassifierEnhancer: Set the seed for random number generation.
setSeed(long) - Method in class weka.classifiers.rules.JRip: Sets the seed value to use in randomizing the data
setSeed(int) - Method in class weka.classifiers.rules.PART: Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.trees.J48: Set the value of Seed.
setSeed(int) - Method in class weka.classifiers.trees.RandomForest: Sets the seed for the random number generator.
setSeed(int) - Method in class weka.classifiers.trees.RandomTree: Set the seed for random number generation.
setSeed(int) - Method in class weka.classifiers.trees.REPTree: Set the value of Seed.
setSeed(int) - Method in class weka.clusterers.RandomizableClusterer: Set the seed for random number generation.
setSeed(int) - Method in class weka.clusterers.RandomizableDensityBasedClusterer: Set the seed for random number generation.
setSeed(int) - Method in class weka.clusterers.RandomizableSingleClustererEnhancer: Set the seed for random number generation.
setSeed(long) - Method in class weka.core.Debug.Random: Sets the seed of this random number generator using a single long seed.
setSeed(int) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Sets the seed for random number generator (that is used for selecting the first anchor point randomly).
setSeed(int) - Method in interface weka.core.Randomizable: Set the seed for random number generation.
setSeed(int) - Method in class weka.core.TestInstances: sets the seed value for the random number generator
setSeed(int) - Method in class weka.datagenerators.classifiers.classification.BayesNet: Sets the random number seed.
setSeed(int) - Method in class weka.datagenerators.DataGenerator: Sets the random number seed.
setSeed(int) - Method in class weka.estimators.UnivariateMixtureEstimator: Set the seed for random number generation.
setSeed(int) - Method in class weka.filters.MultiFilter: Set the seed for random number generation.
setSeed(long) - Method in class weka.filters.supervised.attribute.ClassOrder: Set randomization seed
setSeed(int) - Method in class weka.filters.supervised.instance.Resample
setSeed(int) - Method in class weka.filters.supervised.instance.SpreadSubsample
setSeed(long) - Method in class weka.filters.supervised.instance.StratifiedRemoveFolds: Sets the random number seed for shuffling the dataset.
setSeed(int) - Method in class weka.filters.unsupervised.attribute.AddNoise
setSeed(int) - Method in class weka.filters.unsupervised.attribute.RandomProjection: Sets the random seed of the random number generator
setSeed(int) - Method in class weka.filters.unsupervised.attribute.RandomSubset: Set the seed value for the random number generator.
setSeed(int) - Method in class weka.filters.unsupervised.attribute.ReplaceWithMissingValue: Set the random number generator seed value.
setSeed(int) - Method in class weka.filters.unsupervised.instance.Randomize
setSeed(long) - Method in class weka.filters.unsupervised.instance.RemoveFolds: Sets the random number seed for shuffling the dataset.
setSeed(int) - Method in class weka.filters.unsupervised.instance.Resample
setSeed(int) - Method in class weka.filters.unsupervised.instance.ReservoirSample
setSeed(int) - Method in class weka.gui.beans.CrossValidationFoldMaker: Set the seed
setSeed(int) - Method in class weka.gui.beans.TrainTestSplitMaker: Set the random seed
setSeed(int) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Set a seed for random number generation (if needed).
setSeed(int) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Initializes a new random number generator using the supplied seed.
setSeed(String) - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Set the random seed to use
setSeed(String) - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Set the random seed to use
setSegmentId(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the segmentId property.
setSelectedAttributes(String) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
setSelectedAttributes(boolean[]) - Method in class weka.gui.AttributeSelectionPanel: Set the selected attributes in the widget.
setSelectedBeans(Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setSelectedBeans(int, Vector<Object>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setSelectedColumn(int) - Method in class weka.gui.arffviewer.ArffTable: sets the selected column
setSelectedEnumValue(String) - Method in class weka.core.EnumHelper: Set the selected/wrapped enum value (as obtained by calling toString() on the enum value)
setSelectedListValue(String) - Method in class weka.gui.ResultHistoryPanel: Set the selected list entry.
setSelectedRange(String) - Method in class weka.core.DictionaryBuilder: Set the value of m_SelectedRange.
setSelectedRange(String) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Set the value of m_SelectedRange.
setSeperator(String) - Method in class weka.gui.HierarchyPropertyParser: Set the seperator between levels.
setSeqId(String) - Method in class weka.core.pmml.jaxbbindings.SequenceReference: Sets the value of the seqId property.
setSequenceModel(SequenceModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the sequenceModel property.
setSequenceReference(SequenceReference) - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence: Sets the value of the sequenceReference property.
setSequenceReference(SequenceReference) - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence: Sets the value of the sequenceReference property.
setSerializedClassifierFile(File) - Method in class weka.filters.supervised.attribute.AddClassification: Sets the file pointing to a serialized, trained classifier.
setSerializedClustererFile(File) - Method in class weka.filters.unsupervised.attribute.AddCluster: Sets the file pointing to a serialized, built clusterer.
setSetId(String) - Method in class weka.core.pmml.jaxbbindings.SetReference: Sets the value of the setId property.
setSetReference(SetReference) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the setReference property.
setSetting(String, Settings.SettingKey, Object) - Method in class weka.core.Settings: Set a value for a setting.
setSettings(Settings) - Method in class weka.knowledgeflow.BaseExecutionEnvironment
setSettings(Settings) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Set knowledge flow settings for this execution environment
setSettings(Settings) - Method in interface weka.knowledgeflow.FlowExecutor: Convenience method for applying settings - implementers should delegate the the execution environment
setSettings(Settings) - Method in class weka.knowledgeflow.FlowRunner: Set the settings to use when executing the Flow
setShape(int) - Method in class weka.gui.treevisualizer.Node: Set the value of shape.
setShapes(ArrayList<ArrayList<Double>>) - Method in class weka.gui.visualize.VisualizePanel: This will set the shapes for the instances.
setShapeSize(int[]) - Method in class weka.gui.visualize.PlotData2D: Set the shape sizes for the plot data
setShapeSize(ArrayList<Object>) - Method in class weka.gui.visualize.PlotData2D: Set the shape sizes for the plot data
setShapeType(int[]) - Method in class weka.gui.visualize.PlotData2D: Set the shape type for the plot data
setShapeType(ArrayList<Integer>) - Method in class weka.gui.visualize.PlotData2D: Set the shape type for the plot data
setShowAndOr(boolean) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Set whether to show the combination operator in the textual description
setShowAttBars(boolean) - Method in class weka.gui.visualize.VisualizePanel: Set whether the attribute bars should be shown or not.
setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffPanel: Sets whether to display the attribute index in the header.
setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: Sets whether to display the attribute index in the header.
setShowAttributeIndex(boolean) - Method in class weka.gui.arffviewer.ArffTableModel: Sets whether to display the attribute index in the header.
setShowAverage(boolean) - Method in class weka.experiment.ResultMatrix: sets whether to display the average per column or not.
setShowClassPanel(boolean) - Method in class weka.gui.visualize.VisualizePanel: Set whether the class panel should be shown or not.
setShowGlobalInfoToolTips(boolean) - Static method in class weka.gui.GenericObjectEditor
setShowLeafTipText(boolean) - Method in class weka.gui.knowledgeflow.StepTree: Turn on or off tool tip text popups for the steps in the tree
setShowStdDev(boolean) - Method in class weka.experiment.ResultMatrix: sets whether to display the std deviations or not.
setShowStdDev(boolean) - Method in class weka.experiment.ResultMatrixSignificance: sets whether to display the std deviations or not - always false!
setShowStdDevs(boolean) - Method in class weka.experiment.PairedTTester: Set whether standard deviations are displayed or not.
setShowStdDevs(boolean) - Method in interface weka.experiment.Tester: Set whether standard deviations are displayed or not.
setShowTipTexts(boolean) - Method in class weka.gui.knowledgeflow.StepTreeLeafDetails: Set whether to show tip text or not
setShowZeroInstancesAsUnknown(boolean) - Method in class weka.gui.InstancesSummaryPanel: Set whether to show zero instances as unknown (i.e.
setShrinkage(double) - Method in class weka.classifiers.meta.AdditiveRegression: Set the shrinkage parameter
setShrinkage(double) - Method in class weka.classifiers.meta.LogitBoost: Set the value of Shrinkage.
setSigma(int) - Method in class weka.attributeSelection.ReliefFAttributeEval: Sets the sigma value.
setSigma(double) - Method in class weka.classifiers.functions.supportVector.Puk: Sets the sigma value.
setSignificance(int, int, int) - Method in class weka.experiment.ResultMatrix: sets the significance at the given position (if the position is valid).
setSignificanceLevel(double) - Method in class weka.associations.Apriori: Set the value of significanceLevel.
setSignificanceLevel(double) - Method in class weka.experiment.PairedTTester: Set the value of SignificanceLevel.
setSignificanceLevel(double) - Method in interface weka.experiment.Tester: Set the value of SignificanceLevel.
setSignificanceLevel(double) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Sets the significance level.
setSignificanceWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the significance (0 = optimal).
setSilent(boolean) - Method in class weka.core.AllJavadoc: sets whether to suppress output in the console
setSilent(boolean) - Method in class weka.core.Check: Set slient mode, i.e., no output at all to stdout
setSilent(boolean) - Method in class weka.core.Javadoc: sets whether to suppress output in the console
setSilent(boolean) - Method in class weka.estimators.CheckEstimator: Set slient mode, i.e., no output at all to stdout
setSimilarityScale(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringField: Sets the value of the similarityScale property.
setSimilarityType(String) - Method in class weka.core.pmml.jaxbbindings.TextModelSimiliarity: Sets the value of the similarityType property.
setSimpleMatching(SimpleMatching) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the simpleMatching property.
setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the simplePredicate property.
setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Sets the value of the simplePredicate property.
setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the simplePredicate property.
setSimplePredicate(SimplePredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the simplePredicate property.
setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the simpleSetPredicate property.
setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Sets the value of the simpleSetPredicate property.
setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the simpleSetPredicate property.
setSimpleSetPredicate(SimpleSetPredicate) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the simpleSetPredicate property.
setSIndex(int) - Method in class weka.gui.visualize.VisualizePanel: Set the shape for creating splits.
setSingle(String) - Method in class weka.gui.ResultHistoryPanel: Sets the single-click display to view the named result.
setSingleIndex(String) - Method in class weka.core.SingleIndex: Sets the index from a string representation.
setSingleLineCommentStart(String) - Method in class weka.gui.scripting.SyntaxDocument: Sets the string that is the start of a single-line comment.
setSize(int) - Method in class weka.core.matrix.DoubleVector: Sets the size of the vector
setSize(int) - Method in class weka.core.matrix.IntVector: Sets the size of the vector.
setSize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.Cluster: Sets the value of the size property.
setSize(Double) - Method in class weka.core.pmml.jaxbbindings.Partition: Sets the value of the size property.
setSize(int, int) - Method in class weka.experiment.ResultMatrix: clears the content of the matrix and sets the new size.
setSkipIdentical(boolean) - Method in class weka.core.neighboursearch.LinearNNSearch: Sets the property to skip identical instances (with distance zero from the target) from the set of neighbours returned.
setSmoothedValue(Double) - Method in class weka.core.pmml.jaxbbindings.Level: Sets the value of the smoothedValue property.
setSmoothedValue(Double) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Sets the value of the smoothedValue property.
setSmoothing(boolean) - Method in class weka.classifiers.trees.m5.Rule: Smooth predictions
setSMOReg(SMOreg) - Method in class weka.classifiers.functions.supportVector.RegOptimizer: sets the parent SVM
setSort(boolean) - Method in class weka.filters.unsupervised.attribute.AddValues: Sets whether the labels are sorted.
setSortColumn(int) - Method in class weka.experiment.PairedTTester: Set the column to sort on, -1 means the default sorting.
setSortColumn(int) - Method in interface weka.experiment.Tester: Set the column to sort on, -1 means the default sorting.
setSortDetails(String) - Method in class weka.gui.beans.Sorter: Set the sort rules to use
setSortDetails(String) - Method in class weka.knowledgeflow.steps.Sorter: Set the sort rules to use
setSortDictionary(boolean) - Method in class weka.core.DictionaryBuilder: Set whether to keep the dictionary sorted alphabetically as it is built.
setSortType(SelectedTag) - Method in class weka.filters.unsupervised.attribute.SortLabels: Sets the sort type to be used.
setSource(File) - Method in class weka.core.converters.AbstractFileLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(File) - Method in class weka.core.converters.AbstractLoader: Default implementation throws an IOException.
setSource(InputStream) - Method in class weka.core.converters.AbstractLoader: Default implementation throws an IOException.
setSource(URL) - Method in class weka.core.converters.ArffLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.ArffLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(File) - Method in class weka.core.converters.C45Loader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(InputStream) - Method in class weka.core.converters.CSVLoader: Resets the Loader object and sets the source of the data set to be the supplied Stream object.
setSource(File) - Method in class weka.core.converters.CSVLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(String, String, String) - Method in class weka.core.converters.DatabaseLoader: Sets the database url, user and pw
setSource(String) - Method in class weka.core.converters.DatabaseLoader: Sets the database url
setSource() - Method in class weka.core.converters.DatabaseLoader: Sets the database url using the DatabaseUtils file
setSource(File) - Method in class weka.core.converters.JSONLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(URL) - Method in class weka.core.converters.JSONLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.JSONLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(URL) - Method in class weka.core.converters.LibSVMLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.LibSVMLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(File) - Method in interface weka.core.converters.Loader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(InputStream) - Method in interface weka.core.converters.Loader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(URL) - Method in class weka.core.converters.MatlabLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.MatlabLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(InputStream) - Method in class weka.core.converters.SerializedInstancesLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(URL) - Method in class weka.core.converters.SVMLightLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.SVMLightLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(File) - Method in class weka.core.converters.TextDirectoryLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(File) - Method in class weka.core.converters.XRFFLoader: Resets the Loader object and sets the source of the data set to be the supplied File object.
setSource(URL) - Method in class weka.core.converters.XRFFLoader: Resets the Loader object and sets the source of the data set to be the supplied url.
setSource(InputStream) - Method in class weka.core.converters.XRFFLoader: Resets the Loader object and sets the source of the data set to be the supplied InputStream.
setSource(Package) - Method in class weka.core.packageManagement.Dependency: Set the source package.
setSource(Node) - Method in class weka.gui.treevisualizer.Edge: Set the value of source.
setSourceCode(Classifier) - Method in class weka.classifiers.CheckSource: Sets the class to test.
setSourceCode(Filter) - Method in class weka.filters.CheckSource: Sets the class to test.
setSourceStep(Step) - Method in class weka.knowledgeflow.Data: Set the source step of producing this Data object
setSparseData(boolean) - Method in class weka.core.converters.DatabaseLoader: Sets whether data should be encoded as sparse instances
setSparseData(boolean) - Method in class weka.experiment.InstanceQuery: Sets whether data should be encoded as sparse instances
setSplitByDataSet(boolean) - Method in class weka.experiment.RemoteExperiment: Set whether sub experiments are to be created on the basis of data set.
setSplitByProperty(boolean) - Method in class weka.experiment.RemoteExperiment: Set whether sub experiments are to be created on the basis of property.
setSplitCharacteristic(String) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the splitCharacteristic property.
setSplitCharacteristic(String) - Method in class weka.core.pmml.jaxbbindings.TreeModel: Sets the value of the splitCharacteristic property.
setSplitConfidence(double) - Method in class weka.classifiers.trees.HoeffdingTree: Set the allowable error in a split decision.
setSplitCriterion(SelectedTag) - Method in class weka.classifiers.trees.HoeffdingTree: Set the split criterion to use (either Gini or info gain).
setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.CrossValidationResultProducer: Set the SplitEvaluator.
setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.ExplicitTestsetResultProducer: Set the SplitEvaluator.
setSplitEvaluator(SplitEvaluator) - Method in class weka.experiment.RandomSplitResultProducer: Set the SplitEvaluator.
setSplitOnResiduals(boolean) - Method in class weka.classifiers.trees.LMT: Set the value of splitOnResiduals.
setSplitPercent(String) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set the split percentage to use
setSplitPercentage(double) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of SplitPercentage.
setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Sets split point to greatest value in given data smaller or equal to old split point.
setSplitPoint(Instances) - Method in class weka.classifiers.trees.j48.C45Split: Sets split point to greatest value in given data smaller or equal to old split point.
setSplitPoint(double) - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Split point to be used for selection on numeric attribute.
setSpreadAttributeWeight(boolean) - Method in class weka.filters.supervised.attribute.ClassConditionalProbabilities: If true, when generating attributes, spread weight of old attribute across new attributes.
setSpreadAttributeWeight(boolean) - Method in class weka.filters.supervised.attribute.Discretize: If true, when generating binary attributes, spread weight of old attribute across new attributes.
setSpreadAttributeWeight(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary: If true, when generating binary attributes, spread weight of old attribute across new attributes.
setSpreadAttributeWeight(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: If true, when generating binary attributes, spread weight of old attribute across new attributes.
setSpreadAttributeWeight(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: If true, when generating binary attributes, spread weight of old attribute across new attributes.
setSpreadInitialCount(boolean) - Method in class weka.classifiers.trees.REPTree: Set the value of SpreadInitialCount.
setSqlWhere(String) - Method in class weka.core.pmml.jaxbbindings.Aggregate: Sets the value of the sqlWhere property.
setSquaredEuclidean(SquaredEuclidean) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the squaredEuclidean property.
setSSB(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Sets the value of the ssb property.
setSSE(Double) - Method in class weka.core.pmml.jaxbbindings.ClusteringModelQuality: Sets the value of the sse property.
setStandardDeviation(Double) - Method in class weka.core.pmml.jaxbbindings.NumericInfo: Sets the value of the standardDeviation property.
setStandardDeviation(Double) - Method in class weka.core.pmml.jaxbbindings.Time: Sets the value of the standardDeviation property.
setStandardError(Double) - Method in class weka.core.pmml.jaxbbindings.TimeValue: Sets the value of the standardError property.
setStartEndIndices(int, int) - Method in class weka.core.neighboursearch.balltrees.BallNode: Sets the the start and end index of the portion of the master index array that is assigned to this node.
setStartSequentially(boolean) - Method in class weka.gui.beans.FlowRunner: Set whether to launch Startable beans one after the other or all in parallel.
setStartSet(String) - Method in class weka.attributeSelection.BestFirst: Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.GreedyStepwise: Sets a starting set of attributes for the search.
setStartSet(String) - Method in class weka.attributeSelection.Ranker: Sets a starting set of attributes for the search.
setStartSet(String) - Method in interface weka.attributeSelection.StartSetHandler: Sets a starting set of attributes for the search.
setStartTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Sets the value of the startTime property.
setStartTimeVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the startTimeVariable property.
setStatic() - Method in class weka.gui.beans.BeanVisual: Deprecated.
setStaticArgs(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the arguments for the static command
setStaticCmd(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the static command to be executed
setStaticWorkingDir(String) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set the working directory for the static command
setStats(Stats) - Method in class weka.core.expressionlanguage.weka.StatsHelper: Sets the corresponding Stats object
setStatus(int) - Method in class weka.gui.beans.IncrementalClassifierEvent: Set the status
setStatus(int) - Method in class weka.gui.beans.InstanceEvent: Set the status
setStatusFrequency(int) - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Set how often progress is reported to the status bar.
setStatusFrequency(int) - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Set how often progress is reported to the status bar.
setStatusMessage(String) - Method in class weka.experiment.TaskStatusInfo: Set the status message.
setStatusVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the statusVariable property.
setStdDev(int, int, double) - Method in class weka.experiment.ResultMatrix: sets the std deviation at the given position (if the position is valid).
setStdDevPrec(int) - Method in class weka.experiment.ResultMatrix: sets the precision for the standard deviation.
setStdDevWidth(int) - Method in class weka.experiment.ResultMatrix: sets the width for the std dev (0 = optimal).
setStdError(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the stdError property.
setStemmer(Stemmer) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStemmer(Stemmer) - Method in class weka.classifiers.functions.SGDText: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStemmer(Stemmer) - Method in class weka.core.converters.DictionarySaver: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStemmer(Stemmer) - Method in class weka.core.DictionaryBuilder: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStemmer(String) - Method in class weka.core.stemmers.SnowballStemmer: sets the stemmer with the given name, e.g., "porter".
setStemmer(Stemmer) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStemmer(Stemmer) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: the stemming algorithm to use, null means no stemming at all (i.e., the NullStemmer is used).
setStep(Step) - Method in class weka.gui.knowledgeflow.BaseInteractiveViewer: Set the step that owns this viewer.
setStep(Step) - Method in interface weka.gui.knowledgeflow.StepInteractiveViewer: Set the step that owns this viewer.
setStepIsResourceIntensive(boolean) - Method in interface weka.knowledgeflow.StepManager: Mark the step managed by this step manager as resource intensive
setStepIsResourceIntensive(boolean) - Method in class weka.knowledgeflow.StepManagerImpl: Set whether the managed step is resource (cpu/memory) intensive or not
setStepIsResourceIntensive(boolean) - Method in class weka.knowledgeflow.steps.BaseStep: Set whether this step is resource intensive (cpu/memory) or not.
setStepManager(StepManagerImpl) - Method in class weka.gui.knowledgeflow.NoteVisual: Set the StepManagerImpl for the step covered by this visual
setStepManager(StepManagerImpl) - Method in class weka.gui.knowledgeflow.StepVisual: Set the step manager for this visual
setStepManager(StepManager) - Method in class weka.knowledgeflow.steps.BaseStep: Set the step manager for this step
setStepManager(StepManager) - Method in interface weka.knowledgeflow.steps.Step: Set the step manager to use with this step.
setStepMustRunSingleThreaded(boolean) - Method in interface weka.knowledgeflow.StepManager: Marked the step managed by this step manager as one that must run single-threaded.
setStepMustRunSingleThreaded(boolean) - Method in class weka.knowledgeflow.StepManagerImpl: Set whether the managed step must run single-threaded.
setStepMustRunSingleThreaded(boolean) - Method in class weka.knowledgeflow.steps.BaseStep: Set whether this step must run single threaded.
setStepName(String) - Method in class weka.gui.knowledgeflow.StepVisual: Convenience method for setting the name of the step that this visual wraps
setStepProperty(String, Object) - Method in class weka.knowledgeflow.StepManagerImpl: Set a property for this step
setStepSize(int) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of StepSize.
setStepsize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Sets the value of the stepsize property.
setStepSize(int) - Method in class weka.experiment.LearningRateResultProducer: Set the value of StepSize.
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.ASEvaluatorStepEditorDialog: Set the step to edit in this dialog
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.ClassAssignerStepEditorDialog: Set the step being edited
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.ClassifierPerformanceEvaluatorStepEditorDialog: Set the step to edit
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.ClassValuePickerStepEditorDialog: Set the step to edit
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.LoaderStepEditorDialog: Set the step to edit in this editor
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.SaverStepEditorDialog: Set the step to edit
setStepToEdit(Step) - Method in class weka.gui.knowledgeflow.steps.SendToPerspectiveStepEditorDialog: Sets the step to edit and configures the dialog
setStepToWaitFor(String) - Method in class weka.knowledgeflow.steps.Block: Set the step to wait for
setStepVisual(StepVisual) - Method in class weka.knowledgeflow.StepManagerImpl: Set the step visual to use when running in a graphical environment
setStopRequested(boolean) - Method in class weka.knowledgeflow.StepManagerImpl: Set the status of the stop requested flag
setStopwords(File) - Method in class weka.core.stopwords.AbstractFileBasedStopwords: Sets the file containing the stopwords, null or a directory unset the stopwords.
setStopwords(StopwordsHandler[]) - Method in class weka.core.stopwords.MultiStopwords: Sets the stopwords algorithms.
setStopwordsHandler(StopwordsHandler) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Sets the stopwords handler to use.
setStopwordsHandler(StopwordsHandler) - Method in class weka.classifiers.functions.SGDText: Sets the stopwords handler to use.
setStopwordsHandler(StopwordsHandler) - Method in class weka.core.converters.DictionarySaver: Sets the stopwords handler to use.
setStopwordsHandler(StopwordsHandler) - Method in class weka.core.DictionaryBuilder: Sets the stopwords handler to use.
setStopwordsHandler(StopwordsHandler) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets the stopwords handler to use.
setStopwordsHandler(StopwordsHandler) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets the stopwords handler to use.
setStoreOutOfBagPredictions(boolean) - Method in class weka.classifiers.meta.Bagging: Set whether the out of bag predictions are stored.
setString(String, String) - Method in class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer: Sets the value of a string variable
setStringAttributes(String) - Method in class weka.core.converters.CSVLoader: Sets the attribute range to be forced to type string.
setStringValue(String) - Method in class weka.core.Attribute: Clear the map and list of values and set them to contain just the supplied value
setStroke(Stroke) - Method in class weka.gui.visualize.PostscriptGraphics
setStructure(Instances) - Method in class weka.core.converters.AbstractSaver: Sets the strcuture of the instances for the first step of incremental saving.
setStructure(Instances) - Method in class weka.gui.beans.IncrementalClassifierEvent: Set the instances structure
setStructure(Instances) - Method in class weka.gui.beans.InstanceEvent: Set the instances structure
setSubFlow(Vector<Object>) - Method in class weka.gui.beans.MetaBean
setSubFlowPreview(ImageIcon) - Method in class weka.gui.beans.MetaBean
setSubjectIDVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the subjectIDVariable property.
setSubsequenceLength(int) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets the length of the subsequence.
setSubSpaceSize(double) - Method in class weka.classifiers.meta.RandomSubSpace: Sets the size of each subSpace, as a percentage of the training set size.
setSubtreeRaising(boolean) - Method in class weka.classifiers.trees.J48: Set the value of subtreeRaising.
setSummary(int[][], int[][]) - Method in class weka.experiment.ResultMatrix: sets the non-significant and significant wins of the resultsets.
setSumOfSquares(double) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the sumOfSquares property.
setSumSquaredError(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the sumSquaredError property.
setSumSquaredRegression(Double) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the sumSquaredRegression property.
setSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.AssociationRule: Sets the value of the support property.
setSupport(BigDecimal) - Method in class weka.core.pmml.jaxbbindings.Itemset: Sets the value of the support property.
setSupport(Double) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the support property.
setSupport(double) - Method in class weka.core.pmml.jaxbbindings.SequenceRule: Sets the value of the support property.
setSupportVectorMachineModel(SupportVectorMachineModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the supportVectorMachineModel property.
setSupportVectors(SupportVectors) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Sets the value of the supportVectors property.
setSuppressErrorMessage(boolean) - Method in class weka.classifiers.functions.SimpleLinearRegression: Turn off the error message that is reported when no useful attribute is found.
setSuppressMappingReport(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier: Set whether to suppress output the report of model to input mappings.
setSuppressOutput(boolean) - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Sets whether to the regular output is suppressed in case the output is stored in a file.
setSuppressWarnings(boolean) - Method in class weka.core.xml.XMLSerialization: Set whether to suppress warning messages or not
setSvmRepresentation(SVMREPRESENTATION) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the svmRepresentation property.
setT1(double) - Method in class weka.clusterers.Canopy: Set the T1 distance.
setT2(double) - Method in class weka.clusterers.Canopy: Set the T2 distance to use.
setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.ChildParent: Sets the value of the tableLocator property.
setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.MapValues: Sets the value of the tableLocator property.
setTableLocator(TableLocator) - Method in class weka.core.pmml.jaxbbindings.TrainingInstances: Sets the value of the tableLocator property.
setTableName(String) - Method in class weka.core.converters.DatabaseSaver: Sets the table's name.
setTabs(int) - Method in class weka.gui.scripting.SyntaxDocument: sets the number of characters per tab.
setTabTitle(String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setTabTitle(int, String) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setTabuList(int) - Method in class weka.classifiers.bayes.net.search.global.TabuSearch: Sets the Tabu List length.
setTabuList(int) - Method in class weka.classifiers.bayes.net.search.local.TabuSearch: Sets the Tabu List length.
setTanimoto(Tanimoto) - Method in class weka.core.pmml.jaxbbindings.ComparisonMeasure: Sets the value of the tanimoto property.
setTarget(PackageConstraint) - Method in class weka.core.packageManagement.Dependency: Set the target package constraint.
setTarget(String) - Method in class weka.core.pmml.jaxbbindings.Anova: Sets the value of the target property.
setTarget(Object) - Method in class weka.gui.PropertySheetPanel: Sets a new target object for customisation.
setTarget(Node) - Method in class weka.gui.treevisualizer.Edge: Set the value of target.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.MultivariateStats: Sets the value of the targetCategory property.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PCell: Sets the value of the targetCategory property.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the targetCategory property.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.PPCell: Sets the value of the targetCategory property.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.RegressionTable: Sets the value of the targetCategory property.
setTargetCategory(String) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Sets the value of the targetCategory property.
setTargetField(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the targetField property.
setTargetField(String) - Method in class weka.core.pmml.jaxbbindings.PredictiveModelQuality: Sets the value of the targetField property.
setTargetFieldDisplayValue(String) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the targetFieldDisplayValue property.
setTargetFieldName(String) - Method in class weka.core.pmml.jaxbbindings.RegressionModel: Sets the value of the targetFieldName property.
setTargetFieldValue(String) - Method in class weka.core.pmml.jaxbbindings.LiftData: Sets the value of the targetFieldValue property.
setTargetReferenceCategory(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the targetReferenceCategory property.
setTargets(Targets) - Method in class weka.core.pmml.jaxbbindings.DecisionTree: Sets the value of the targets property.
setTargets(Targets) - Method in class weka.core.pmml.jaxbbindings.Regression: Sets the value of the targets property.
setTargetValueCounts(TargetValueCounts) - Method in class weka.core.pmml.jaxbbindings.BayesOutput: Sets the value of the targetValueCounts property.
setTargetValueCounts(TargetValueCounts) - Method in class weka.core.pmml.jaxbbindings.PairCounts: Sets the value of the targetValueCounts property.
setTargetVariableName(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the targetVariableName property.
setTaskResult(Object) - Method in class weka.experiment.TaskStatusInfo: Set the returnable result for this task..
setTaxonomy(String) - Method in class weka.core.pmml.jaxbbindings.DataField: Sets the value of the taxonomy property.
setTaxonomy(Taxonomy) - Method in class weka.core.pmml.jaxbbindings.TextDictionary: Sets the value of the taxonomy property.
setTCol(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the tCol property.
setTempDirectory(String) - Method in class weka.gui.beans.Sorter: Set the directory to use for temporary files during incremental operation
setTempDirectory(File) - Method in class weka.knowledgeflow.steps.Sorter: Set the directory to use for temporary files during incremental operation
setTestBaseFromDialog() - Method in class weka.gui.experiment.ResultsPanel
setTestEvaluator(boolean) - Method in class weka.attributeSelection.CheckAttributeSelection: Sets whether the evaluator or the search method is being tested.
setTestSet(DataSetEvent) - Method in class weka.gui.beans.BatchClassifierEvent: Set the test set
setTestsetDir(File) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the directory to use for the test sets.
setTestsetPrefix(String) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the prefix to use for the test sets.
setTestsetSuffix(String) - Method in class weka.experiment.ExplicitTestsetResultProducer: Sets the suffix to use for the test sets.
setTestStatistic(BASELINETESTSTATISTIC) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the testStatistic property.
setTestStructure(Instances) - Method in class weka.classifiers.misc.InputMappedClassifier: Set the test structure (if known in advance) that we are likely to see.
setText(String) - Method in class weka.gui.beans.BeanVisual: Set the label for the visual.
setText(String) - Method in class weka.gui.beans.EnvironmentField: Deprecated.

Set the text to display in the editable combo box.
setText(String) - Method in class weka.gui.EnvironmentField: Set the text to display in the editable combo box.
setText(String) - Method in class weka.gui.PasswordField
setTextModel(TextModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the textModel property.
setTextNotificationListener(TextViewer.TextNotificationListener) - Method in class weka.knowledgeflow.steps.TextViewer: Set the listener to be notified about new textual results
setTFTransform(boolean) - Method in class weka.core.DictionaryBuilder: Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
setTFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
setTFTransform(boolean) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets whether if the word frequencies should be transformed into log(1+fij) where fij is the frequency of word i in document(instance) j.
setThreshold(double) - Method in class weka.attributeSelection.ClassifierAttributeEval: Set the value of the threshold for repeating cross validation
setThreshold(double) - Method in class weka.attributeSelection.GreedyStepwise: Set the threshold by which the AttributeSelection module can discard attributes.
setThreshold(double) - Method in interface weka.attributeSelection.RankedOutputSearch: Sets a threshold by which attributes can be discarded from the ranking.
setThreshold(double) - Method in class weka.attributeSelection.Ranker: Set the threshold by which the AttributeSelection module can discard attributes.
setThreshold(double) - Method in class weka.attributeSelection.WrapperSubsetEval: Set the value of the threshold for repeating cross validation
setThreshold(double) - Method in class weka.core.pmml.jaxbbindings.NaiveBayesModel: Sets the value of the threshold property.
setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NearestNeighborModel: Sets the value of the threshold property.
setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the threshold property.
setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the threshold property.
setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachine: Sets the value of the threshold property.
setThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.SupportVectorMachineModel: Sets the value of the threshold property.
setThreshold(double) - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Sets the threshold for the max error when predicting a numeric class.
setTime(Time) - Method in class weka.core.pmml.jaxbbindings.AntecedentSequence: Sets the value of the time property.
setTime(double) - Method in class weka.core.pmml.jaxbbindings.BaselineCell: Sets the value of the time property.
setTime(Time) - Method in class weka.core.pmml.jaxbbindings.ConsequentSequence: Sets the value of the time property.
setTime(Time) - Method in class weka.core.pmml.jaxbbindings.Sequence: Sets the value of the time property.
setTime(Double) - Method in class weka.core.pmml.jaxbbindings.TimeValue: Sets the value of the time property.
setTimeAnchor(TimeAnchor) - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Sets the value of the timeAnchor property.
setTimes(int, double) - Method in class weka.core.matrix.DoubleVector: Multiplies a value to an element
setTimeSeriesModel(TimeSeriesModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the timeSeriesModel property.
setTimestamp(Timestamp) - Method in class weka.core.pmml.jaxbbindings.Header: Sets the value of the timestamp property.
setTimestamp(Timestamp) - Method in class weka.core.pmml.jaxbbindings.TimeValue: Sets the value of the timestamp property.
SettingKey() - Constructor for class weka.core.Settings.SettingKey: Construct a new empty setting key
SettingKey(String, String, String) - Constructor for class weka.core.Settings.SettingKey: Construct a new SettingKey with the given key, description and tool tip text
SettingKey(String, String, String, List<String>) - Constructor for class weka.core.Settings.SettingKey: Construct a new SettingKey with the given key, description, tool tip and pick list
Settings - Class in weka.core: Maintains a collection of settings.
Settings(String, String) - Constructor for class weka.core.Settings: Construct a new Settings object to be stored in the supplied store under the given ID/name
Settings.SettingKey - Class in weka.core: Class implementing a key for a setting.
settingsChanged() - Method in class weka.gui.AbstractGUIApplication: Called when settings are changed by the user
settingsChanged() - Method in class weka.gui.AbstractPerspective: Called when the user alters settings.
settingsChanged() - Method in class weka.gui.explorer.AssociationsPanel
settingsChanged() - Method in class weka.gui.explorer.AttributeSelectionPanel
settingsChanged() - Method in class weka.gui.explorer.ClassifierPanel
settingsChanged() - Method in class weka.gui.explorer.ClustererPanel
settingsChanged() - Method in class weka.gui.explorer.PreprocessPanel
settingsChanged() - Method in class weka.gui.explorer.VisualizePanel
settingsChanged() - Method in interface weka.gui.GUIApplication: Called when settings are changed by the user
settingsChanged() - Method in class weka.gui.knowledgeflow.KnowledgeFlowApp: Apply (changed) settings
settingsChanged() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Called when the user alters settings.
settingsChanged() - Method in interface weka.gui.Perspective: Called when the user alters settings.
settingsChanged() - Method in class weka.gui.SimpleCLIPanel
settingsChanged() - Method in class weka.gui.WorkbenchApp: Called when the user changes settings
SettingsEditor - Class in weka.gui: Provides a panel for editing application and perspective settings
SettingsEditor(Settings, GUIApplication) - Constructor for class weka.gui.SettingsEditor
SettingsEditor.SingleSettingsEditor - Class in weka.gui
setTokenizer(Tokenizer) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: the tokenizer algorithm to use.
setTokenizer(Tokenizer) - Method in class weka.classifiers.functions.SGDText: the tokenizer algorithm to use.
setTokenizer(Tokenizer) - Method in class weka.core.converters.DictionarySaver: the tokenizer algorithm to use.
setTokenizer(Tokenizer) - Method in class weka.core.DictionaryBuilder: the tokenizer algorithm to use.
setTokenizer(Tokenizer) - Method in class weka.filters.unsupervised.attribute.FixedDictionaryStringToWordVector: the tokenizer algorithm to use.
setTokenizer(Tokenizer) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: the tokenizer algorithm to use.
setTolerance(double) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: sets the tolerance
setToleranceParameter(double) - Method in class weka.classifiers.functions.SMO: Set the value of tolerance parameter.
setToolTip(String) - Method in class weka.core.Settings.SettingKey: Set the tool tip text for this setting
setToolTipText(String) - Method in class weka.gui.GenericObjectEditor.GOETreeNode: Set the tool tip for this node
setTop(double) - Method in class weka.gui.treevisualizer.Node: Set the value of top.
setTotalFreq(double) - Method in class weka.core.pmml.jaxbbindings.Counts: Sets the value of the totalFreq property.
setTotalSquaresSum(Double) - Method in class weka.core.pmml.jaxbbindings.ContStats: Sets the value of the totalSquaresSum property.
setTotalValuesSum(Double) - Method in class weka.core.pmml.jaxbbindings.ContStats: Sets the value of the totalValuesSum property.
setTrainingData(Instances) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the training data to use
setTrainingTime(int) - Method in class weka.classifiers.functions.MultilayerPerceptron: Set the number of training epochs to perform.
setTrainIterations(int) - Method in class weka.classifiers.BVDecompose: Sets the maximum number of boost iterations
setTrainPercent(double) - Method in class weka.experiment.RandomSplitResultProducer: Set the value of TrainPercent.
setTrainPercent(double) - Method in class weka.gui.beans.TrainTestSplitMaker: Set the percentage of data to be in the training portion of the split
setTrainPercent(String) - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Set the training percentage
setTrainPoolSize(int) - Method in class weka.classifiers.BVDecompose: Set the number of instances in the training pool.
setTrainSet(DataSetEvent) - Method in class weka.gui.beans.BatchClassifierEvent: Set the training set
setTrainSize(int) - Method in class weka.classifiers.BVDecomposeSegCVSub: Set the training size.
setTransactionsMustContain(String) - Method in class weka.associations.FPGrowth: Set the comma separated list of items that transactions must contain in order to be considered for large item sets and rules.
setTransform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
setTransformAllValues(boolean) - Method in class weka.filters.supervised.attribute.NominalToBinary: Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.
setTransformAllValues(boolean) - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Sets whether all nominal values are transformed into new attributes, not just if there are more than 2.
setTransformation(String) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Sets the value of the transformation property.
setTransformationDictionary(TransformationDictionary) - Method in class weka.core.pmml.jaxbbindings.PMML: Sets the value of the transformationDictionary property.
setTransformBackToOriginal(boolean) - Method in class weka.attributeSelection.PrincipalComponents: Sets whether the data should be transformed back to the original space
setTranslation(double) - Method in class weka.filters.unsupervised.attribute.Normalize: Sets the translation.
setTreatMissingValuesAsZero(boolean) - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Set whether missing values should be treated in the same way as zeros
setTreatXValFoldsSeparately(boolean) - Method in class weka.knowledgeflow.steps.ASEvaluator: Set whether to output separate results for each fold of a cross-validation, rather than averaging over folds.
setTreatZeroAsMissing(boolean) - Method in class weka.associations.Apriori: Sets whether zeros (i.e.
setTreeModel(TreeModel) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the treeModel property.
setTrend(String) - Method in class weka.core.pmml.jaxbbindings.TrendExpoSmooth: Sets the value of the trend property.
setTrendExpoSmooth(TrendExpoSmooth) - Method in class weka.core.pmml.jaxbbindings.ExponentialSmoothing: Sets the value of the trendExpoSmooth property.
setTrialsValue(BigInteger) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the trialsValue property.
setTrialsVariable(String) - Method in class weka.core.pmml.jaxbbindings.GeneralRegressionModel: Sets the value of the trialsVariable property.
setTrim(boolean) - Method in class weka.classifiers.misc.InputMappedClassifier: Set whether to trim white space from each end of names before matching.
setTRow(String) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the tRow property.
setTrue(True) - Method in class weka.core.pmml.jaxbbindings.Attribute: Sets the value of the true property.
setTrue(True) - Method in class weka.core.pmml.jaxbbindings.CompoundRule: Sets the value of the true property.
setTrue(True) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the true property.
setTrue(True) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the true property.
setTrueNegative(double) - Method in class weka.classifiers.evaluation.TwoClassStats: Sets the number of negative instances predicted as negative
setTruePositive(double) - Method in class weka.classifiers.evaluation.TwoClassStats: Sets the number of positive instances predicted as positive
setTrueStepName(String) - Method in class weka.gui.beans.FlowByExpression: Set the name of the connected step to send "true" instances to
setTrueStepName(String) - Method in class weka.knowledgeflow.steps.FlowByExpression: Set the name of the connected step to send "true" instances to
setTruncate(boolean) - Method in class weka.core.converters.DatabaseSaver: Set whether to truncate (i.e.
setTStart(double) - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing: Sets the m_fTStart.
setTStart(double) - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing: Sets the m_fTStart.
setTValue(Double) - Method in class weka.core.pmml.jaxbbindings.MultivariateStat: Sets the value of the tValue property.
setType(int) - Method in class weka.classifiers.functions.neural.NeuralConnection
setType(String) - Method in class weka.core.pmml.jaxbbindings.AnovaRow: Sets the value of the type property.
setType(String) - Method in class weka.core.pmml.jaxbbindings.ArrayType: Sets the value of the type property.
setType(String) - Method in class weka.core.pmml.jaxbbindings.PCovMatrix: Sets the value of the type property.
setType(String) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the type property.
setType(TIMEANCHOR2) - Method in class weka.core.pmml.jaxbbindings.TimeAnchor: Sets the value of the type property.
setType(VALIDTIMESPEC) - Method in class weka.core.pmml.jaxbbindings.TimeCycle: Sets the value of the type property.
setType(TIMEEXCEPTIONTYPE) - Method in class weka.core.pmml.jaxbbindings.TimeException: Sets the value of the type property.
setType(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Set the type of the new attribute
setUndoBuffer(Stack<File>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setUndoBuffer(int, Stack<File>) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setUndoEnabled(boolean) - Method in interface weka.core.Undoable: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffPanel: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sets whether undo support is enabled
setUndoEnabled(boolean) - Method in class weka.gui.arffviewer.ArffTableModel: sets whether undo support is enabled
setUniformDistribution(UniformDistribution) - Method in class weka.core.pmml.jaxbbindings.Alternate: Sets the value of the uniformDistribution property.
setUniformDistribution(UniformDistribution) - Method in class weka.core.pmml.jaxbbindings.Baseline: Sets the value of the uniformDistribution property.
setUnit(String) - Method in class weka.core.pmml.jaxbbindings.SeasonalityExpoSmooth: Sets the value of the unit property.
setUnpruned(boolean) - Method in class weka.classifiers.rules.PART: Set the value of unpruned.
setUnpruned(boolean) - Method in class weka.classifiers.trees.J48: Set the value of unpruned.
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.M5Base: Use unpruned tree/rules
setUnpruned(boolean) - Method in class weka.classifiers.trees.m5.Rule: Use unpruned tree/rules
setup(Instances) - Method in class weka.core.DictionaryBuilder
setUp() - Method in class weka.gui.explorer.AbstractPlotInstances: Performs checks, sets up the structure for the plot instances.
setupAttribLists() - Method in class weka.gui.visualize.MatrixPanel: Sets up the UI's attributes lists
setUpBoundaryPanel() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Sets up the BoundaryPanel object so that it is ready for plotting.
setUpComboBoxes(Instances) - Method in class weka.gui.visualize.ThresholdVisualizePanel: This overloads VisualizePanel's setUpComboBoxes to add ActionListeners to watch for when the X/Y Axis comboboxes are changed.
setUpComboBoxes(Instances) - Method in class weka.gui.visualize.VisualizePanel: initializes the comboboxes based on the data
setUpdateIncrementalClassifier(boolean) - Method in class weka.gui.beans.Classifier: Set whether an incremental classifier will be updated on the incoming instance stream.
setUpdateIncrementalClassifier(boolean) - Method in class weka.knowledgeflow.steps.Classifier: Set whether to update an incremental classifier on an incoming instance stream
setUpdateWeightsOnly(boolean) - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Sets whether only weights should be udpated.
setupEval(Evaluation, Classifier, Instances, CostMatrix, ClassifierErrorsPlotInstances, AbstractOutput, boolean) - Static method in class weka.gui.explorer.ClassifierPanel: Configures an evaluation object with respect to a classifier, cost matrix, output and plotting.
setupEval(Evaluation, Classifier, Instances, CostMatrix, ClassifierErrorsPlotInstances, AbstractOutput, boolean, boolean) - Static method in class weka.gui.explorer.ClassifierPanel: Configures an evaluation object with respect to a classifier, cost matrix, output and plotting.
setUpFile() - Method in class weka.gui.beans.LoaderCustomizer
setUpFile() - Method in class weka.gui.beans.SaverCustomizer: Sets up dialog for saving instances in a file
setUpFile() - Method in class weka.gui.beans.SerializedModelSaverCustomizer: Sets up dialog for saving models to a file
SetupModePanel - Class in weka.gui.experiment: This panel switches between simple and advanced experiment setup panels.
SetupModePanel() - Constructor for class weka.gui.experiment.SetupModePanel: Creates the setup panel with no initial experiment.
SetupPanel - Class in weka.gui.experiment: This panel controls the configuration of an experiment.
SetupPanel(Experiment) - Constructor for class weka.gui.experiment.SetupPanel: Creates the setup panel with the supplied initial experiment.
SetupPanel() - Constructor for class weka.gui.experiment.SetupPanel: Creates the setup panel with no initial experiment.
setUpper(double) - Method in class weka.core.pmml.jaxbbindings.UniformDistribution: Sets the value of the upper property.
setUpper(int) - Method in class weka.core.Range: Sets the value of "last".
setUpper(int) - Method in class weka.core.SingleIndex: Sets the value of "last".
setUpperBoundMinSupport(double) - Method in class weka.associations.Apriori: Set the value of upperBoundMinSupport.
setUpperBoundMinSupport(double) - Method in class weka.associations.FPGrowth: Set the value of upperBoundMinSupport.
setUpperSize(int) - Method in class weka.experiment.LearningRateResultProducer: Set the value of UpperSize.
setURL(String) - Method in class weka.core.converters.ArffLoader: Set the url to load from
setUrl(String) - Method in interface weka.core.converters.DatabaseConverter
setUrl(String) - Method in class weka.core.converters.DatabaseLoader: Sets the database URL
setUrl(String) - Method in class weka.core.converters.DatabaseSaver: Sets the database URL.
setURL(String) - Method in class weka.core.converters.JSONLoader: Set the url to load from.
setURL(String) - Method in class weka.core.converters.LibSVMLoader: Set the url to load from.
setURL(String) - Method in class weka.core.converters.MatlabLoader: Set the url to load from.
setURL(String) - Method in class weka.core.converters.SVMLightLoader: Set the url to load from.
setURL(String) - Method in interface weka.core.converters.URLSourcedLoader: Set the url to load from
setURL(String) - Method in class weka.core.converters.XRFFLoader: Set the url to load from
setURL(String) - Method in class weka.gui.sql.ConnectionPanel: sets the URL.
setUsage(TIMESERIESUSAGE) - Method in class weka.core.pmml.jaxbbindings.TimeSeries: Sets the value of the usage property.
setUsageType(FIELDUSAGETYPE) - Method in class weka.core.pmml.jaxbbindings.MiningField: Sets the value of the usageType property.
setUseADTree(boolean) - Method in class weka.classifiers.bayes.BayesNet: Set whether ADTree structure is used or not
setUseAIC(boolean) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of useAIC.
setUseAIC(boolean) - Method in class weka.classifiers.trees.lmt.LogisticBase: Set the value of useAIC.
setUseAIC(boolean) - Method in class weka.classifiers.trees.LMT: Set the value of useAIC.
setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.global.HillClimber: set use the arc reversal operation
setUseArcReversal(boolean) - Method in class weka.classifiers.bayes.net.search.local.HillClimber: set use the arc reversal operation
setUseAverage(boolean) - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Set the value of UseAverage.
setUseBetterEncoding(boolean) - Method in class weka.filters.supervised.attribute.Discretize: Sets whether better encoding is to be used for MDL.
setUseBinNumbers(boolean) - Method in class weka.filters.supervised.attribute.Discretize: Sets whether bin numbers rather than ranges should be used for discretized attributes.
setUseBinNumbers(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: Sets whether bin numbers rather than ranges should be used for discretized attributes.
setUseBlanks(boolean) - Method in class weka.gui.scripting.SyntaxDocument: Sets whether to use blanks instead of tabs.
setUseConjugateGradientDescent(boolean) - Method in class weka.classifiers.functions.Logistic: Sets whether conjugate gradient descent is used.
setUseCpuTime(boolean) - Method in class weka.core.Debug.Clock: enables/disables the use of CPU time (if measurement of CPU time is available).
setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseCrossOver(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseCrossValidation(boolean) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of useCrossValidation.
setUseCustomDimensions(boolean) - Method in class weka.gui.visualize.JComponentWriter: sets whether to use custom dimensions for the image
setUseDouble(boolean) - Method in class weka.core.converters.MatlabSaver: Sets whether to use double or single precision.
setUseDynamic(boolean) - Method in class weka.knowledgeflow.steps.ExecuteProcess: Set whether to execute dynamic commands
setUseEnvironmentPropertyEditors(boolean) - Method in class weka.gui.PropertySheetPanel: Set whether to use environment property editors for string and file properties
setUseEqualFrequency(boolean) - Method in class weka.classifiers.meta.RegressionByDiscretization: Set the value of UseEqualFrequency.
setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.Discretize: Set the value of UseEqualFrequency.
setUseEqualFrequency(boolean) - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Set the value of UseEqualFrequency.
setUseEstimatedPriors(boolean) - Method in class weka.classifiers.meta.LogitBoost: Set resampling mode
setUseIBk(boolean) - Method in class weka.classifiers.rules.DecisionTable: Sets whether IBk should be used instead of the majority class
setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Sets the UseK2Prior.
setUseK2Prior(boolean) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Sets the UseK2Prior.
setUseKernelEstimator(boolean) - Method in class weka.classifiers.bayes.NaiveBayes: Sets if kernel estimator is to be used.
setUseKononenko(boolean) - Method in class weka.filters.supervised.attribute.Discretize: Sets whether Kononenko's MDL criterion is to be used.
setUseLaplace(boolean) - Method in class weka.classifiers.trees.J48: Set the value of useLaplace.
setUseLeastValues(boolean) - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Sets whether to use values with least or most instances
setUseLowerOrder(boolean) - Method in class weka.classifiers.functions.supportVector.PolyKernel: Sets whether to use lower-order terms.
setUseMDLcorrection(boolean) - Method in class weka.classifiers.rules.PART: Set the value of useMDLcorrection.
setUseMDLcorrection(boolean) - Method in class weka.classifiers.trees.J48: Set the value of useMDLcorrection.
setUseMissing(boolean) - Method in class weka.filters.unsupervised.attribute.AddNoise: Sets the flag if missing values are treated as extra values.
setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseMutation(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseNormalization(boolean) - Method in class weka.classifiers.functions.supportVector.StringKernel: Sets whether to use normalization.
setUseNormalizedEntropy(boolean) - Method in class weka.estimators.UnivariateMixtureEstimator
setUseORForMustContainList(boolean) - Method in class weka.associations.FPGrowth: Set whether to use OR rather than AND when considering must contain lists.
setUsePairwiseCoupling(boolean) - Method in class weka.classifiers.meta.MultiClassClassifier: Set whether to use pairwise coupling with 1-vs-1 classification to improve probability estimates.
setUsePercentageSplit(boolean) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set whether to perform a percentage split on the training data for evaluation
setUseProb(boolean) - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
setUsePropertyIterator(boolean) - Method in class weka.experiment.Experiment: Sets whether the custom property iterator should be used.
setUsePropertyIterator(boolean) - Method in class weka.experiment.RemoteExperiment: Sets whether the custom property iterator should be used.
setUsePruning(boolean) - Method in class weka.classifiers.rules.JRip: Sets whether pruning is performed
setUseQRDecomposition(boolean) - Method in class weka.classifiers.functions.LinearRegression: Set whether to use QR decomposition.
setUser(String) - Method in interface weka.core.converters.DatabaseConverter
setUser(String) - Method in class weka.core.converters.DatabaseLoader: Sets the database user
setUser(String) - Method in class weka.core.converters.DatabaseSaver: Sets the database user.
setUser(String) - Method in class weka.gui.sql.ConnectionPanel: sets the User.
setUseReasonCodes(Boolean) - Method in class weka.core.pmml.jaxbbindings.Scorecard: Sets the value of the useReasonCodes property.
setUseRelativePath(boolean) - Method in class weka.core.converters.AbstractFileLoader: Set whether to use relative rather than absolute paths
setUseRelativePath(boolean) - Method in class weka.core.converters.AbstractFileSaver: Set whether to use relative rather than absolute paths
setUseRelativePath(boolean) - Method in interface weka.core.converters.FileSourcedConverter: Set whether to use relative rather than absolute paths
setUseRelativePath(boolean) - Method in class weka.gui.beans.SerializedModelSaver: Set whether to use relative paths for the directory.
setUseResampling(boolean) - Method in class weka.classifiers.meta.AdaBoostM1: Set resampling mode
setUseResampling(boolean) - Method in class weka.classifiers.meta.LogitBoost: Set resampling mode
setUsername(String) - Method in class weka.experiment.DatabaseUtils: Set the database username.
setUserOptions(String[]) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: sets the option the user supplied for the kernel
setUserOptions(String[]) - Method in class weka.core.CheckOptionHandler: Sets the user-supplied options (creates a copy)
setUserVisiblePerspectives(LinkedList<String>) - Method in class weka.gui.PerspectiveManager.SelectedPerspectivePreferences: Set a list of perspectives that should be visible
setUseShortIdentifiers(boolean) - Method in class weka.filters.supervised.attribute.MergeNominalValues: Set whether to output short identifiers for merged values.
setUseShortIDs(boolean) - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Sets whether short IDs are to be used.
setUseStars(boolean) - Method in class weka.core.AllJavadoc: sets whether to prefix the Javadoc with "*"
setUseStars(boolean) - Method in class weka.core.Javadoc: sets whether to prefix the Javadoc with "*"
setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayes: Set whether supervised discretization is to be used.
setUseSupervisedDiscretization(boolean) - Method in class weka.classifiers.bayes.NaiveBayesUpdateable: Set whether supervised discretization is to be used.
setUseTab(boolean) - Method in class weka.classifiers.evaluation.output.prediction.CSV: Sets whether to use tab instead of comma as separator.
setUseTabs(boolean) - Method in class weka.core.converters.MatlabSaver: Sets whether to use tabs instead of blanks.
setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
setUseTournamentSelection(boolean) - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
setUseTraining(boolean) - Method in class weka.attributeSelection.ClassifierSubsetEval: Set if training data is to be used instead of hold out/test data
setUseTree(boolean) - Method in class weka.classifiers.trees.m5.Rule: Use an m5 tree rather than generate rules
setUseUnsmoothed(boolean) - Method in class weka.classifiers.trees.m5.M5Base: Use unsmoothed predictions
setUseVariant1(boolean) - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Sets whether to use variant 1
setUseWordFrequencies(boolean) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Set whether to use word frequencies rather than binary bag of words representation.
setUseWordFrequencies(boolean) - Method in class weka.classifiers.functions.SGDText: Set whether to use word frequencies rather than binary bag of words representation.
setValidating(boolean) - Method in class weka.core.xml.XMLDocument: sets whether to use a validating parser or not.
Note: this does clear the current DOM document!
setValidating(boolean) - Method in class weka.core.xml.XMLOptions: sets whether to use a validating parser or not.
setValidationSetSize(int) - Method in class weka.classifiers.functions.MultilayerPerceptron: This will set the size of the validation set.
setValidationThreshold(int) - Method in class weka.classifiers.functions.MultilayerPerceptron: This sets the threshold to use for when validation testing is being done.
setValue(int, String) - Method in class weka.core.AbstractInstance: Sets a value of a nominal or string attribute to the given value.
setValue(Attribute, double) - Method in class weka.core.AbstractInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(Attribute, String) - Method in class weka.core.AbstractInstance: Sets a value of an nominal or string attribute to the given value.
setValue(int, double) - Method in class weka.core.BinarySparseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(int, double) - Method in class weka.core.DenseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(boolean) - Method in class weka.core.expressionlanguage.common.Primitives.BooleanVariable
setValue(double) - Method in class weka.core.expressionlanguage.common.Primitives.DoubleVariable
setValue(String) - Method in class weka.core.expressionlanguage.common.Primitives.StringVariable
setValue(int, double) - Method in interface weka.core.Instance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(int, String) - Method in interface weka.core.Instance: Sets a value of a nominal or string attribute to the given value.
setValue(Attribute, double) - Method in interface weka.core.Instance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(Attribute, String) - Method in interface weka.core.Instance: Sets a value of an nominal or string attribute to the given value.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.BaselineStratum: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.CategoricalPredictor: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Category: Sets the value of the value property.
setValue(Double) - Method in class weka.core.pmml.jaxbbindings.Coefficient: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Constant: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Decision: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Extension: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.FieldValue: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.FieldValueCount: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Item: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.MatCell: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.NormDiscrete: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.OutputField: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.PairCounts: Sets the value of the value property.
setValue(double) - Method in class weka.core.pmml.jaxbbindings.PCovCell: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.PPCell: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.ResultField: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.ScoreDistribution: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.SimplePredicate: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValue: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.TargetValueCount: Sets the value of the value property.
setValue(double) - Method in class weka.core.pmml.jaxbbindings.TimeValue: Sets the value of the value property.
setValue(String) - Method in class weka.core.pmml.jaxbbindings.Value: Sets the value of the value property.
setValue(Object, PropertyPath.Path, Object) - Static method in class weka.core.PropertyPath: set the given value specified by the given path in the object
setValue(Object, String, Object) - Static method in class weka.core.PropertyPath: set the given value specified by the given path in the object
setValue(int, double) - Method in class weka.core.SparseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValue(TechnicalInformation.Field, String) - Method in class weka.core.TechnicalInformation: sets the value for the given field, overwrites any previously existing one.
setValue(String) - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Set the value of the new attribute.
setValue(Object) - Method in class weka.gui.beans.EnvironmentField: Deprecated.
setValue(Object) - Method in class weka.gui.ColorEditor: Set the current color
setValue(Object) - Method in class weka.gui.CostMatrixEditor: Sets the value of the CostMatrix to be edited.
setValue(Object) - Method in class weka.gui.EnvironmentField
setValue(Object) - Method in class weka.gui.FileEnvironmentField
setValue(Object) - Method in class weka.gui.GenericArrayEditor: Sets the current object array.
setValue(Object) - Method in class weka.gui.GenericObjectEditor: Sets the current Object.
setValue(Object) - Method in class weka.gui.PasswordField
setValue(Object) - Method in class weka.gui.SimpleDateFormatEditor: Sets the value of the date format to be edited.
setValueAt(Object, int, int) - Method in class weka.gui.arffviewer.ArffTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int) - Method in class weka.gui.InteractiveTableModel
setValueAt(Object, int, int) - Method in class weka.gui.SortedTableModel: Sets the value in the cell at columnIndex and rowIndex to aValue.
setValueAt(Object, int, int) - Method in class weka.gui.sql.ResultSetTableModel: sets the value in the cell at columnIndex and rowIndex to aValue.
setValueIndex(int) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Sets index of the indicator value.
setValueIndices(String) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Sets indices of the indicator values.
setValueIndicesArray(int[]) - Method in class weka.filters.unsupervised.attribute.MakeIndicator: Set which attributes are to be deleted (or kept if invert is true)
setValueReplacements(String) - Method in class weka.filters.unsupervised.attribute.RenameNominalValues
setValuesList(String) - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Sets the ranges for each attribute.
setValueSparse(int, double) - Method in class weka.core.BinarySparseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValueSparse(int, double) - Method in class weka.core.DenseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setValueSparse(int, double) - Method in interface weka.core.Instance: Sets a specific value in the instance to the given value (internal floating-point format), given an index into the sparse representation.
setValueSparse(int, double) - Method in class weka.core.SparseInstance: Sets a specific value in the instance to the given value (internal floating-point format).
setVariables(VariableDeclarations) - Method in class weka.core.expressionlanguage.parser.Parser: Sets the variable declarations for the program
SetVariables - Class in weka.knowledgeflow.steps: Step that can be used to set the values of environment variables for the flow being executed.
SetVariables() - Constructor for class weka.knowledgeflow.steps.SetVariables
SetVariablesStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the SetVariables step
SetVariablesStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SetVariablesStepEditorDialog
setVariance(double) - Method in class weka.core.pmml.jaxbbindings.AnyDistribution: Sets the value of the variance property.
setVariance(double) - Method in class weka.core.pmml.jaxbbindings.GaussianDistribution: Sets the value of the variance property.
setVarianceCovered(double) - Method in class weka.attributeSelection.PrincipalComponents: Sets the amount of variance to account for when retaining principal components
setVarianceCovered(double) - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Sets the amount of variance to account for when retaining principal components.
setVarsInternalRep(String) - Method in class weka.knowledgeflow.steps.SetVariables: Set the static variables to set (in internal representation)
setVectorFields(VectorFields) - Method in class weka.core.pmml.jaxbbindings.VectorDictionary: Sets the value of the vectorFields property.
setVectorId(String) - Method in class weka.core.pmml.jaxbbindings.SupportVector: Sets the value of the vectorId property.
setVerbose(boolean) - Method in class weka.associations.Apriori: Sets verbose mode
setVerboseOn() - Method in class weka.core.Debug.DBO: Set the verbose on flag on
setVerificationFields(VerificationFields) - Method in class weka.core.pmml.jaxbbindings.ModelVerification: Sets the value of the verificationFields property.
setVersion(String) - Method in class weka.core.pmml.jaxbbindings.Application: Sets the value of the version property.
setVersion(String) - Method in class weka.core.pmml.jaxbbindings.PMML: Sets the value of the version property.
setVersionConstraint(VersionPackageConstraint.VersionComparison) - Method in class weka.core.packageManagement.VersionPackageConstraint
setVersionConstraint(String) - Method in class weka.core.packageManagement.VersionPackageConstraint
setVisible(boolean) - Method in class weka.gui.knowledgeflow.InvisibleNode: Set the visible status of this node
setVisible(boolean) - Method in class weka.gui.Main: Shows or hides this component depending on the value of parameter b.
setVisible(boolean) - Method in class weka.gui.sql.SqlViewerDialog: displays the dialog if TRUE.
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSink: Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractDataSource: Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractEvaluator: Set the visual
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTestSetProducer: Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.AbstractTrainingSetProducer: Set the visual for this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.Appender: Set a new visual representation
setVisual(BeanVisual) - Method in class weka.gui.beans.Associator: Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ClassAssigner
setVisual(BeanVisual) - Method in class weka.gui.beans.Classifier: Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ClassValuePicker
setVisual(BeanVisual) - Method in class weka.gui.beans.Clusterer: Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.CostBenefitAnalysis
setVisual(BeanVisual) - Method in class weka.gui.beans.DataVisualizer: Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.Filter: Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.FlowByExpression
setVisual(BeanVisual) - Method in class weka.gui.beans.GraphViewer: Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ImageSaver
setVisual(BeanVisual) - Method in class weka.gui.beans.ImageViewer
setVisual(BeanVisual) - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.Join: Set the visual for this step
setVisual(BeanVisual) - Method in class weka.gui.beans.MetaBean: Sets the visual appearance of this wrapper bean
setVisual(BeanVisual) - Method in class weka.gui.beans.ModelPerformanceChart: Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.PredictionAppender: Set the visual for this data source
setVisual(BeanVisual) - Method in class weka.gui.beans.SerializedModelSaver: Set the visual for this data source.
setVisual(BeanVisual) - Method in class weka.gui.beans.Sorter: Set a new visual representation
setVisual(BeanVisual) - Method in class weka.gui.beans.StripChart: Set the visual appearance of this bean
setVisual(BeanVisual) - Method in class weka.gui.beans.SubstringLabeler: Set a new visual representation
setVisual(BeanVisual) - Method in class weka.gui.beans.SubstringReplacer: Set a new visual representation
setVisual(BeanVisual) - Method in class weka.gui.beans.TextSaver
setVisual(BeanVisual) - Method in class weka.gui.beans.TextViewer: Describe setVisual method here.
setVisual(BeanVisual) - Method in interface weka.gui.beans.Visible: Set a new visual representation
setVoteFlag(boolean) - Method in class weka.datagenerators.classifiers.classification.RDG1: Sets the vote flag.
setWeight(double) - Method in class weka.core.AbstractInstance: Sets the weight of an instance.
setWeight(double) - Method in class weka.core.Attribute: Sets the new attribute's weight.
setWeight(double) - Method in interface weka.core.Instance: Sets the weight of an instance.
setWeight(double) - Method in class weka.core.pmml.jaxbbindings.Con1: Sets the value of the weight property.
setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.Item: Sets the value of the weight property.
setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.Segment: Sets the value of the weight property.
setWeight(Double) - Method in class weka.core.pmml.jaxbbindings.SimpleRule: Sets the value of the weight property.
setWeight(double) - Method in class weka.filters.unsupervised.attribute.Add: Sets weight of the attribute used.
setWeightByDistance(boolean) - Method in class weka.attributeSelection.ReliefFAttributeEval: Set the nearest neighbour weighting method
setWeighted(String) - Method in class weka.core.pmml.jaxbbindings.PartitionFieldStats: Sets the value of the weighted property.
setWeighted(String) - Method in class weka.core.pmml.jaxbbindings.UnivariateStats: Sets the value of the weighted property.
setWeightField(String) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the weightField property.
setWeightingDimensions(boolean[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Set the dimensions to be used in computing a weight for each instance generated
setWeightingDimensions(boolean[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Set which dimensions to use when computing a weight for the next instance to generate
setWeightingKernel(int) - Method in class weka.classifiers.lazy.LWL: Sets the kernel weighting method to use.
setWeightingValues(double[]) - Method in interface weka.gui.boundaryvisualizer.DataGenerator: Set the values of the dimensions (chosen via setWeightingDimensions) to be used when computing instance weights
setWeightingValues(double[]) - Method in class weka.gui.boundaryvisualizer.KDDataGenerator: Set the values for the weighting dimensions to be used when computing the weight for the next instance to be generated
setWeightThreshold(int) - Method in class weka.classifiers.meta.AdaBoostM1: Set weight threshold
setWeightThreshold(int) - Method in class weka.classifiers.meta.LogitBoost: Set weight thresholding
setWeightTrimBeta(double) - Method in class weka.classifiers.functions.SimpleLogistic: Set the value of weightTrimBeta.
setWeightTrimBeta(double) - Method in class weka.classifiers.trees.lmt.LogisticBase: Sets the option "weightTrimBeta".
setWeightTrimBeta(double) - Method in class weka.classifiers.trees.LMT: Set the value of weightTrimBeta.
setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralLayer: Sets the value of the width property.
setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.NeuralNetwork: Sets the value of the width property.
setWidth(Double) - Method in class weka.core.pmml.jaxbbindings.Neuron: Sets the value of the width property.
setWindowSize(int) - Method in class weka.classifiers.lazy.IBk: Sets the maximum number of instances allowed in the training pool.
setWindowSize(BigInteger) - Method in class weka.core.pmml.jaxbbindings.TestDistributions: Sets the value of the windowSize property.
setWords(String) - Method in class weka.core.CheckScheme: Sets the comma-separated list of words to use for generating strings.
setWords(String) - Method in class weka.core.TestInstances: Sets the comma-separated list of words to use for generating strings.
setWordSeparators(String) - Method in class weka.core.CheckScheme: sets the word separators (chars) to use for assembling strings.
setWordSeparators(String) - Method in class weka.core.TestInstances: sets the word separators (chars) to use for assembling strings.
setWordsToKeep(int) - Method in class weka.core.converters.DictionarySaver: Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.
setWordsToKeep(int) - Method in class weka.core.DictionaryBuilder: Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.
setWordsToKeep(int) - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Sets the number of words (per class if there is a class attribute assigned) to attempt to keep.
setWordwrap(boolean) - Method in class weka.gui.LogWindow: toggles the wordwrap
override wordwrap from: http://forum.java.sun.com/thread.jspa?threadID=498535&messageID=2356174
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Associator: Sets the algorithm (associator) for this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Classifier: Sets the algorithm (classifier) for this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Clusterer: Sets the algorithm (clusterer) for this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Filter: Set the filter to be wrapped by this bean
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Loader: Set the loader
setWrappedAlgorithm(Object) - Method in class weka.gui.beans.Saver: Set the saver
setWrappedAlgorithm(Object) - Method in interface weka.gui.beans.WekaWrapper: Set the algorithm.
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.ASEvaluator: Set an instance of the wrapped algorithm to use
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Set the actual algorithm wrapped by this instance
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Associator: Set the wrapped algorithm
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Classifier
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Clusterer: Set the wrapped algorithm
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.DataGenerator: Set the algorithm to wrap
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Filter: Set the wrapped algorithm (filter)
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Loader: Set the wrapped algorithm to use
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.Saver: Set the actual wrapped algorithm instance
setWrappedAlgorithm(Object) - Method in class weka.knowledgeflow.steps.WekaAlgorithmWrapper: Set the wrapped algorithm
setWrappedRules(AssociationRules) - Method in class weka.associations.FilteredAssociationRules: Set the wrapped AssociationRules object to use.
setWriteTitleString(boolean) - Method in class weka.knowledgeflow.steps.TextSaver: Set whether the title string will be written to the file
setX(double) - Method in class weka.classifiers.functions.neural.NeuralConnection
setX(int) - Method in class weka.gui.beans.BeanInstance: Sets the x coordinate of this bean
setX(int) - Method in class weka.gui.knowledgeflow.StepVisual: Set the x coordinate of this step on the graphical layout
setX(int) - Method in class weka.gui.visualize.AttributePanel: shows which bar is the current x attribute.
setXAttName(String) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the name/index of the X axis attribute
setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the x attribute index
setXAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the x axis fixed dimension
setXCoordinates(XCoordinates) - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Sets the value of the xCoordinates property.
setXCoordinates(XCoordinates) - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Sets the value of the xCoordinates property.
setXindex(int) - Method in class weka.gui.visualize.Plot2D: Set the index of the attribute to go on the x axis
setXindex(int) - Method in class weka.gui.visualize.PlotData2D: Set the x index of the data.
setXIndex(int) - Method in class weka.gui.visualize.VisualizePanel: Set the index of the attribute for the x axis
setXLabelFreq(int) - Method in class weka.gui.beans.StripChart: Set the frequency for printing x label values
setXLabelFreq(int) - Method in class weka.knowledgeflow.steps.StripChart: Set the x label frequency
setXML(Reader) - Method in class weka.core.xml.XMLInstances: reads the XML structure from the given reader
setXORMode(Color) - Method in class weka.gui.visualize.PostscriptGraphics: Not implemented
setXval(boolean) - Method in class weka.attributeSelection.AttributeSelection: do a cross validation
setXY(int, int) - Method in class weka.gui.beans.BeanInstance: Set the x and y coordinates of this bean
setY(double) - Method in class weka.classifiers.functions.neural.NeuralConnection
setY(int) - Method in class weka.gui.beans.BeanInstance: Sets the y coordinate of this bean
setY(int) - Method in class weka.gui.knowledgeflow.StepVisual: Set the y coordinate of this step on the graphical layout
setY(int) - Method in class weka.gui.visualize.AttributePanel: shows which bar is the current y attribute.
setYAttName(String) - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Set the name/index of the Y axis attribute
setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Set the y attribute index
setYAttribute(int) - Method in class weka.gui.boundaryvisualizer.RemoteBoundaryVisualizerSubTask: Set the y axis fixed dimension
setYCoordinates(YCoordinates) - Method in class weka.core.pmml.jaxbbindings.LiftGraph: Sets the value of the yCoordinates property.
setYCoordinates(YCoordinates) - Method in class weka.core.pmml.jaxbbindings.ROCGraph: Sets the value of the yCoordinates property.
setYindex(int) - Method in class weka.gui.visualize.Plot2D: Set the index of the attribute to go on the y axis
setYindex(int) - Method in class weka.gui.visualize.PlotData2D: Set the y index of the data
setYIndex(int) - Method in class weka.gui.visualize.VisualizePanel: Set the index of the attribute for the y axis
setZeroThreshold(Double) - Method in class weka.core.pmml.jaxbbindings.VerificationField: Sets the value of the zeroThreshold property.
setZMax(double) - Method in class weka.classifiers.meta.LogitBoost: Set the Z max threshold on the responses
setZoomSetting(int, int) - Method in class weka.gui.beans.KnowledgeFlowApp.MainKFPerspective
setZoomSetting(int) - Method in class weka.gui.knowledgeflow.VisibleLayout: Set the current zoom setting for this layout
SEVERE - Static variable in class weka.core.Debug: the log level Severe
SFEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation: Returns the difference in base-2 log loss between null model and scheme.
SFEntropyGain() - Method in class weka.classifiers.Evaluation: Returns the total SF, which is the null model entropy minus the scheme entropy.
SFMeanEntropyGain() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean difference in base-2 log loss between null model and scheme.
SFMeanEntropyGain() - Method in class weka.classifiers.Evaluation: Returns the SF per instance, which is the null model entropy minus the scheme entropy, per instance.
SFMeanPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean base-2 log loss wrt the null model.
SFMeanPriorEntropy() - Method in class weka.classifiers.Evaluation: Returns the entropy per instance for the null model.
SFMeanSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation: Returns the mean base-2 log loss wrt the scheme.
SFMeanSchemeEntropy() - Method in class weka.classifiers.Evaluation: Returns the entropy per instance for the scheme.
SFPriorEntropy() - Method in class weka.classifiers.evaluation.Evaluation: Returns the base-2 log loss wrt the null model.
SFPriorEntropy() - Method in class weka.classifiers.Evaluation: Returns the total entropy for the null model.
SFSchemeEntropy() - Method in class weka.classifiers.evaluation.Evaluation: Returns the base-2 log loss wrt the scheme.
SFSchemeEntropy() - Method in class weka.classifiers.Evaluation: Returns the total entropy for the scheme.
SGD - Class in weka.classifiers.functions: Implements stochastic gradient descent for learning various linear models (binary class SVM, binary class logistic regression, squared loss, Huber loss and epsilon-insensitive loss linear regression).
SGD() - Constructor for class weka.classifiers.functions.SGD
SGDText - Class in weka.classifiers.functions: Implements stochastic gradient descent for learning a linear binary class SVM or binary class logistic regression on text data.
SGDText() - Constructor for class weka.classifiers.functions.SGDText
SGDText.Count - Class in weka.classifiers.functions
ShadowBorder - Class in weka.gui.beans
ShadowBorder() - Constructor for class weka.gui.beans.ShadowBorder: Constructor.
ShadowBorder(int) - Constructor for class weka.gui.beans.ShadowBorder: Constructor.
ShadowBorder(int, Color) - Constructor for class weka.gui.beans.ShadowBorder: Constructor.
ShadowBorder - Class in weka.gui.knowledgeflow: Border implementation that provides a drop shadow
ShadowBorder() - Constructor for class weka.gui.knowledgeflow.ShadowBorder: Constructor.
ShadowBorder(int) - Constructor for class weka.gui.knowledgeflow.ShadowBorder: Constructor.
ShadowBorder(int, Color) - Constructor for class weka.gui.knowledgeflow.ShadowBorder: Constructor.
shear(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
shift(int, int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Shifts given instance from one bag to another one.
shift(int, int) - Method in class weka.core.matrix.IntVector: Shifts an element to another position.
shiftBeans(BeanInstance, boolean) - Method in class weka.gui.beans.MetaBean: Move coords of all inputs and outputs of this meta bean to the coords of the supplied BeanInstance.
shiftRange(int, int, Instances, int, int) - Method in class weka.classifiers.trees.j48.Distribution: Shifts all instances in given range from one bag to another one.
shiftToEnd(int) - Method in class weka.core.matrix.IntVector: Shifts an element to the end of the vector.
SHORT - Static variable in class weka.experiment.DatabaseUtils: Type mapping for SHORT used for reading experiment results.
show(Component, int, int) - Method in class weka.gui.GenericObjectEditor.JTreePopupMenu: Displays the menu, making sure it will fit on the screen.
SHOW_GRID - Static variable in class weka.knowledgeflow.KFDefaults
SHOW_GRID_KEY - Static variable in class weka.knowledgeflow.KFDefaults
SHOW_JTREE_GLOBAL_INFO_TIPS - Static variable in class weka.knowledgeflow.KFDefaults
SHOW_JTREE_TIP_TEXT_KEY - Static variable in class weka.knowledgeflow.KFDefaults
showApplicationSettingsEditor(Settings, GUIApplication) - Static method in class weka.gui.SettingsEditor: Popup a settings editor for an application
showAttributes() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: displays all the attributes, returns the selected item or NULL if canceled
showAverageTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
showChart() - Method in class weka.gui.beans.StripChart: Popup the chart panel
showDialog(Component, String) - Method in class weka.gui.ConverterFileChooser: Pops a custom file chooser dialog with a custom approve button.
showDialog() - Method in class weka.gui.experiment.OutputFormatDialog: Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.ListSelectorDialog: Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.PropertySelectorDialog: Pops up the modal dialog and waits for cancel or a selection.
showDialog() - Method in class weka.gui.ViewerDialog: Pops up the modal dialog and waits for Cancel or OK.
showDialog(Instances) - Method in class weka.gui.ViewerDialog: Pops up the modal dialog and waits for Cancel or OK.
showErrorDialog(Exception) - Method in class weka.gui.AbstractGUIApplication: Popup a dialog displaying the supplied Exception
showErrorDialog(Exception) - Method in interface weka.gui.GUIApplication: Popup a dialog displaying the supplied Exception
showErrorDialog(Exception) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Popup an error dialog
showExplorer(String) - Method in class weka.gui.GUIChooserApp
showHistory() - Method in class weka.gui.sql.ConnectionPanel: displays the query history.
showHistory() - Method in class weka.gui.sql.QueryPanel: displays the query history.
showInfoDialog(Object, String, boolean) - Method in class weka.gui.AbstractGUIApplication: Popup an information dialog
showInfoDialog(Object, String, boolean) - Method in interface weka.gui.GUIApplication: Popup an information dialog
showInfoDialog(Object, String, boolean) - Method in class weka.gui.knowledgeflow.MainKFPerspective: Popup an information dialog
showInformationBox(Component, String, String, int) - Static method in class weka.gui.ComponentHelper: displays a message box with the given title, message, buttons and icon ant the dimension.
showInputBox(Component, String, String, Object) - Static method in class weka.gui.ComponentHelper: pops up an input dialog
showKnowledgeFlow(String) - Method in class weka.gui.GUIChooserApp
showMemoryIsLow() - Method in class weka.core.Memory: Prints a warning message if memoryIsLow (and if GUI is present a dialog).
showMemoryIsLow() - Method in class weka.gui.knowledgeflow.MainKFPerspective: Print a warning if memory is low (and show a GUI dialog if running in a graphical environment)
showMenuBar(JFrame) - Method in class weka.gui.AbstractGUIApplication: Show the menu bar for the application
showMenuBar(JFrame) - Method in interface weka.gui.GUIApplication: Show the menu bar for the application
showMenuBar(JFrame) - Method in class weka.gui.PerspectiveManager: Tell the perspective manager to show the menu bar
showMessageBox(Component, String, String, int, int) - Static method in class weka.gui.ComponentHelper: displays a message box with the given title, message, buttons and icon ant the dimension.
showOpenDialog(Component) - Method in class weka.gui.ConverterFileChooser: Pops up an "Open File" file chooser dialog.
showOutOfMemory() - Method in class weka.core.Memory: prints an error message if OutOfMemory (and if GUI is present a dialog), otherwise nothing happens.
showPanel(ScriptingPanel, String[]) - Static method in class weka.gui.scripting.ScriptingPanel: Displays the panel in a frame.
showPanel(ScriptingPanel, String[], int, int) - Static method in class weka.gui.scripting.ScriptingPanel: Displays the panel in a frame.
showPerspectivesToolBar() - Method in class weka.gui.AbstractGUIApplication: Show the perspectives toolbar
showPerspectivesToolBar() - Method in interface weka.gui.GUIApplication: Show the perspectives toolbar
showPopup() - Method in class weka.gui.GenericObjectEditor.CapabilitiesFilterDialog: if a JPopupMenu is set, it is displayed again.
showProperties() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: displays some properties of the instances
showPropertyDialog() - Method in class weka.gui.PropertyPanel: Displays the property edit dialog for the panel.
showResults() - Method in class weka.gui.beans.GraphViewer: Popup a result list from which the user can select a graph to view
showResults() - Method in class weka.gui.beans.TextViewer: Popup a component to display the selected text
showSaveDialog(Component) - Method in class weka.gui.ConverterFileChooser: Pops up an "Save File" file chooser dialog.
showSingleSettingsEditor(Settings, String, String, JComponent) - Static method in class weka.gui.SettingsEditor: Popup a single panel settings editor dialog for one group of related settings
showSingleSettingsEditor(Settings, String, String, JComponent, int, int) - Static method in class weka.gui.SettingsEditor: Popup a single panel settings editor dialog for one group of related settings
showStdDevTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
showTree() - Method in class weka.gui.HierarchyPropertyParser: Show the whole tree in text format
showValues() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: displays all the distinct values for an attribute
showWindow(Container) - Method in class weka.gui.Main: brings child frame to the top.
showWindow(Class<?>) - Method in class weka.gui.Main: brings the first frame to the top that is of the specified window class.
shrinkageTipText() - Method in class weka.classifiers.meta.AdditiveRegression: Returns the tip text for this property
shrinkageTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
sigLevel - Variable in class weka.experiment.PairedStats: The significance level for comparisons
sigmaTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
sigmaTipText() - Method in class weka.classifiers.functions.supportVector.Puk: Returns the tip text for this property
SigmoidKernelType - Class in weka.core.pmml.jaxbbindings: Java class for SigmoidKernelType element declaration.
SigmoidKernelType() - Constructor for class weka.core.pmml.jaxbbindings.SigmoidKernelType
SigmoidUnit - Class in weka.classifiers.functions.neural: This can be used by the neuralnode to perform all it's computations (as a sigmoid unit).
SigmoidUnit() - Constructor for class weka.classifiers.functions.neural.SigmoidUnit
sign() - Method in class weka.core.matrix.DoubleVector: Returns the signs of all elements in terms of -1, 0 and +1.
SIGNIFICANCE_LOSS - Static variable in class weka.experiment.ResultMatrix: loss.
SIGNIFICANCE_TIE - Static variable in class weka.experiment.ResultMatrix: tie.
SIGNIFICANCE_WIN - Static variable in class weka.experiment.ResultMatrix: win.
significanceLevelTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
significanceLevelTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
significanceWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
SimpleBatchFilter - Class in weka.filters: This filter is a superclass for simple batch filters.
SimpleBatchFilter() - Constructor for class weka.filters.SimpleBatchFilter
SimpleCLI - Class in weka.gui: Creates a very simple command line for invoking the main method of classes.
SimpleCLI() - Constructor for class weka.gui.SimpleCLI: Constructor.
SimpleCLIPanel - Class in weka.gui: Creates a very simple command line for invoking the main method of classes.
SimpleCLIPanel() - Constructor for class weka.gui.SimpleCLIPanel
SimpleCLIPanel.ClassRunner - Class in weka.gui: A class that handles running the main method of the class in a separate thread.
SimpleCLIPanel.CommandlineCompletion - Class in weka.gui: A class for commandline completion of classnames.
SimpleDateFormatEditor - Class in weka.gui: Class for editing SimpleDateFormat strings.
SimpleDateFormatEditor() - Constructor for class weka.gui.SimpleDateFormatEditor: Constructs a new SimpleDateFormatEditor.
SimpleEstimator - Class in weka.classifiers.bayes.net.estimate: SimpleEstimator is used for estimating the conditional probability tables of a Bayes network once the structure has been learned.
SimpleEstimator() - Constructor for class weka.classifiers.bayes.net.estimate.SimpleEstimator
SimpleFilter - Class in weka.filters: This filter contains common behavior of the SimpleBatchFilter and the SimpleStreamFilter.
SimpleFilter() - Constructor for class weka.filters.SimpleFilter
SimpleKMeans - Class in weka.clusterers: Cluster data using the k means algorithm.
SimpleKMeans() - Constructor for class weka.clusterers.SimpleKMeans: the default constructor.
SimpleLinearRegression - Class in weka.classifiers.functions: Learns a simple linear regression model.
SimpleLinearRegression() - Constructor for class weka.classifiers.functions.SimpleLinearRegression
SimpleLinearRegression - Class in weka.classifiers.trees.lmt: Stripped down version of SimpleLinearRegression.
SimpleLinearRegression() - Constructor for class weka.classifiers.trees.lmt.SimpleLinearRegression: Default constructor.
SimpleLinearRegression(int, double, double) - Constructor for class weka.classifiers.trees.lmt.SimpleLinearRegression: Construct a simple linear regression model based on the given info.
SimpleLog() - Constructor for class weka.core.Debug.SimpleLog: default constructor, uses only stdout
SimpleLog(String) - Constructor for class weka.core.Debug.SimpleLog: Creates a logger that writes into the specified file.
SimpleLog(String, boolean) - Constructor for class weka.core.Debug.SimpleLog: Creates a logger that writes into the specified file.
SimpleLogger() - Constructor for class weka.gui.beans.FlowRunner.SimpleLogger
SimpleLogger() - Constructor for class weka.knowledgeflow.FlowRunner.SimpleLogger
SimpleLogistic - Class in weka.classifiers.functions: Classifier for building linear logistic regression models.
SimpleLogistic() - Constructor for class weka.classifiers.functions.SimpleLogistic: Constructor for creating SimpleLogistic object with standard options.
SimpleLogistic(int, boolean, boolean) - Constructor for class weka.classifiers.functions.SimpleLogistic: Constructor for creating SimpleLogistic object.
SimpleMatching - Class in weka.core.pmml.jaxbbindings: Java class for simpleMatching element declaration.
SimpleMatching() - Constructor for class weka.core.pmml.jaxbbindings.SimpleMatching
SimplePredicate - Class in weka.core.pmml.jaxbbindings: Java class for SimplePredicate element declaration.
SimplePredicate() - Constructor for class weka.core.pmml.jaxbbindings.SimplePredicate
SimpleRule - Class in weka.core.pmml.jaxbbindings: Java class for SimpleRule element declaration.
SimpleRule() - Constructor for class weka.core.pmml.jaxbbindings.SimpleRule
SimpleSetPredicate - Class in weka.core.pmml.jaxbbindings: Java class for SimpleSetPredicate element declaration.
SimpleSetPredicate() - Constructor for class weka.core.pmml.jaxbbindings.SimpleSetPredicate
SimpleSetupPanel - Class in weka.gui.experiment: This panel controls the configuration of an experiment.
SimpleSetupPanel(Experiment) - Constructor for class weka.gui.experiment.SimpleSetupPanel: Creates the setup panel with the supplied initial experiment.
SimpleSetupPanel() - Constructor for class weka.gui.experiment.SimpleSetupPanel: Creates the setup panel with no initial experiment.
SimpleStreamFilter - Class in weka.filters: This filter is a superclass for simple stream filters.
SimpleStreamFilter() - Constructor for class weka.filters.SimpleStreamFilter
SimpleVariableDeclarations - Class in weka.core.expressionlanguage.common: A set of customizable variable declarations for primitive types.
SimpleVariableDeclarations() - Constructor for class weka.core.expressionlanguage.common.SimpleVariableDeclarations
SimpleVariableDeclarations.VariableInitializer - Class in weka.core.expressionlanguage.common: A class to initialize variables that have been declared by a SimpleVariableDeclarations class and used inside a program
SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.

For more information see:

R.R.
SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
SimulatedAnnealing - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses the general purpose search method of simulated annealing to find a well scoring network structure.

For more information see:

R.R.
SimulatedAnnealing() - Constructor for class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
SINE - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: Constant set for choice of pattern.
SingleAssociatorEnhancer - Class in weka.associations: Abstract utility class for handling settings common to meta associators that use a single base associator.
SingleAssociatorEnhancer() - Constructor for class weka.associations.SingleAssociatorEnhancer
SingleClassifierEnhancer - Class in weka.classifiers: Abstract utility class for handling settings common to meta classifiers that use a single base learner.
SingleClassifierEnhancer() - Constructor for class weka.classifiers.SingleClassifierEnhancer
SingleClustererEnhancer - Class in weka.clusterers: Meta-clusterer for enhancing a base clusterer.
SingleClustererEnhancer() - Constructor for class weka.clusterers.SingleClustererEnhancer
SingleIndex - Class in weka.core: Class representing a single cardinal number.
SingleIndex() - Constructor for class weka.core.SingleIndex: Default constructor.
SingleIndex(String) - Constructor for class weka.core.SingleIndex: Constructor to set initial index.
SingleSettingsEditor(Map<Settings.SettingKey, Object>) - Constructor for class weka.gui.SettingsEditor.SingleSettingsEditor
SingleThreadedExecution - Annotation Type in weka.knowledgeflow: Class annotation that can be used to indicate that something should be executed in a non-parallel manner - i.e.
singletons(Instances, boolean) - Static method in class weka.associations.AprioriItemSet: Converts the header info of the given set of instances into a set of item sets (singletons).
singletons(Instances) - Static method in class weka.associations.ItemSet: Converts the header info of the given set of instances into a set of item sets (singletons).
singletons(Instances, Instances) - Static method in class weka.associations.LabeledItemSet: Converts the header info of the given set of instances into a set of item sets (singletons).
SINGULAR_DUMMY - Static variable in interface weka.gui.graphvisualizer.GraphConstants: SINGULAR_DUMMY node - node with only one outgoing edge i.e.
SingularValueDecomposition - Class in weka.core.matrix: Singular Value Decomposition.
SingularValueDecomposition(Matrix) - Constructor for class weka.core.matrix.SingularValueDecomposition: Construct the singular value decomposition
size() - Method in class weka.classifiers.CostMatrix: The number of rows (and columns)
size() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of classes.
size() - Method in class weka.classifiers.lazy.kstar.KStarCache.CacheTable: Returns the number of keys in this hashtable.
size() - Method in class weka.classifiers.rules.JRip.RipperRule: the number of antecedents of the rule
size() - Method in class weka.classifiers.rules.Rule: The size of the rule.
size() - Method in class weka.core.Instances: Returns the number of instances in the dataset.
size() - Method in class weka.core.matrix.DoubleVector: Gets the size of the vector.
size() - Method in class weka.core.matrix.IntVector: Gets the size of the vector.
size() - Method in class weka.core.PropertyPath.Path: returns the number of path elements of this structure
size() - Method in class weka.core.Queue: Gets queue's size.
size() - Method in class weka.core.Tee: returns the number of streams currently in the list.
size() - Method in class weka.core.Trie: Returns the number of elements in this collection.
size() - Method in class weka.core.Trie.TrieNode: returns the number of stored strings, i.e., leaves
size() - Method in class weka.core.xml.MethodHandler: returns the number of currently stored Methods
size() - Method in class weka.gui.GenericObjectEditorHistory: Returns the number of entries in the history.
size() - Method in class weka.knowledgeflow.Flow: Get the number of steps in this flow
sizeOfPredictedRegions() - Method in class weka.classifiers.evaluation.Evaluation: Gets the average size of the predicted regions, relative to the range of the target in the training data, at the confidence level specified when evaluation was performed.
sizeOfPredictedRegions() - Method in class weka.classifiers.Evaluation: Gets the average size of the predicted regions, relative to the range of the target in the training data, at the confidence level specified when evaluation was performed.
skipIdenticalTipText() - Method in class weka.core.neighboursearch.LinearNNSearch: Returns the tip text for this property.
SlidingMidPointOfWidestSide - Class in weka.core.neighboursearch.kdtrees: The class that splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
SlidingMidPointOfWidestSide() - Constructor for class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide
sm(double, double) - Static method in class weka.core.Utils: Tests if a is smaller than b.
SMALL - Static variable in class weka.core.Utils: The small deviation allowed in double comparisons.
SMO - Class in weka.classifiers.functions: Implements John Platt's sequential minimal optimization algorithm for training a support vector classifier.

This implementation globally replaces all missing values and transforms nominal attributes into binary ones.
SMO() - Constructor for class weka.classifiers.functions.SMO
SMO.BinarySMO - Class in weka.classifiers.functions: Class for building a binary support vector machine.
SMOreg - Class in weka.classifiers.functions: SMOreg implements the support vector machine for regression.
SMOreg() - Constructor for class weka.classifiers.functions.SMOreg
smOrEq(double, double) - Static method in class weka.core.Utils: Tests if a is smaller or equal to b.
SMOset - Class in weka.classifiers.functions.supportVector: Stores a set of integer of a given size.
SMOset(int) - Constructor for class weka.classifiers.functions.supportVector.SMOset: Creates a new set of the given size.
SNAPSHOT - Static variable in class weka.core.Version: True if snapshot
SnowballStemmer - Class in weka.core.stemmers: A wrapper class for the Snowball stemmers.
SnowballStemmer() - Constructor for class weka.core.stemmers.SnowballStemmer: initializes the stemmer ("porter").
SnowballStemmer(String) - Constructor for class weka.core.stemmers.SnowballStemmer: initializes the stemmer with the given stemmer.
solve(Matrix) - Method in class weka.core.matrix.CholeskyDecomposition: Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.LUDecomposition: Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.Matrix: Solve A*X = B
solve(Matrix) - Method in class weka.core.matrix.QRDecomposition: Least squares solution of A*X = B
solve(double[]) - Method in class weka.core.Matrix: Deprecated.

Solve A*X = B using backward substitution.
solveTranspose(Matrix) - Method in class weka.core.matrix.Matrix: Solve X*A = B, which is also A'*X' = B'
solveTriangle(Matrix, double[], boolean, boolean[]) - Static method in class weka.core.Optimization: Solve the linear equation of TX=B where T is a triangle matrix It can be solved using back/forward substitution, with O(N^2) complexity
sort(int) - Method in class weka.core.Instances: Sorts the instances based on an attribute.
sort(Attribute) - Method in class weka.core.Instances: Sorts the instances based on an attribute.
sort() - Method in class weka.core.matrix.DoubleVector: Sorts the array in place
sort() - Method in class weka.core.matrix.IntVector: Sorts the elements in place
sort(int[]) - Static method in class weka.core.Utils: Sorts a given array of integers in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
sort(double[]) - Static method in class weka.core.Utils: Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
sort(int, boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sorts the table over the given column, either ascending or descending
sort(int) - Method in class weka.gui.SortedTableModel: sorts the table over the given column (ascending)
sort(int, boolean) - Method in class weka.gui.SortedTableModel: sorts the table over the given column, either ascending or descending
SORT_CASEINSENSITIVE - Static variable in class weka.filters.unsupervised.attribute.SortLabels: sorts the strings case-insensitive.
SORT_CASESENSITIVE - Static variable in class weka.filters.unsupervised.attribute.SortLabels: sorts the strings case-sensitive.
sortClassesByRoot(String) - Static method in class weka.gui.GenericObjectEditor: parses the given string of classes separated by ", " and returns the a hashtable with as many entries as there are different root elements in the class names (the key is the root element).
SortContainer(Comparable<?>, int) - Constructor for class weka.gui.SortedTableModel.SortContainer: Initializes the container.
sortDictionaryTipText() - Method in class weka.core.DictionaryBuilder: Tip text for this property
SortedTableModel - Class in weka.gui: Represents a TableModel with sorting functionality.
SortedTableModel() - Constructor for class weka.gui.SortedTableModel: initializes with no model
SortedTableModel(TableModel) - Constructor for class weka.gui.SortedTableModel: initializes with the given model
SortedTableModel.SortContainer - Class in weka.gui: Helper class for sorting the columns.
Sorter - Class in weka.gui.beans: Sorts incoming instances in ascending or descending order according to the values of user specified attributes.
Sorter() - Constructor for class weka.gui.beans.Sorter: Constructs a new Sorter
Sorter - Class in weka.knowledgeflow.steps: Step for sorting instances according to one or more attributes.
Sorter() - Constructor for class weka.knowledgeflow.steps.Sorter
Sorter.SortRule - Class in weka.knowledgeflow.steps: Implements a sorting rule based on a single attribute
SorterBeanInfo - Class in weka.gui.beans: BeanInfo class for the Sorter step
SorterBeanInfo() - Constructor for class weka.gui.beans.SorterBeanInfo
SorterCustomizer - Class in weka.gui.beans: Customizer for the Sorter step
SorterCustomizer() - Constructor for class weka.gui.beans.SorterCustomizer: Constructor
SorterStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the Sorter step
SorterStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SorterStepEditorDialog
sortInstances() - Method in class weka.gui.arffviewer.ArffPanel: sorts the instances via the currently selected column
sortInstances(int) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sorts the instances via the given attribute
sortInstances(int, boolean) - Method in class weka.gui.arffviewer.ArffSortedTableModel: sorts the instances via the given attribute
sortInstances(int) - Method in class weka.gui.arffviewer.ArffTableModel: sorts the instances via the given attribute (ascending)
sortInstances(int, boolean) - Method in class weka.gui.arffviewer.ArffTableModel: sorts the instances via the given attribute
sortInstances() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sorts the current selected attribute
SortLabels - Class in weka.filters.unsupervised.attribute: A simple filter for sorting the labels of nominal attributes.
SortLabels() - Constructor for class weka.filters.unsupervised.attribute.SortLabels
SortLabels.CaseInsensitiveComparator - Class in weka.filters.unsupervised.attribute: Represents a case-insensitive comparator for two strings.
SortLabels.CaseSensitiveComparator - Class in weka.filters.unsupervised.attribute: Represents a case-sensitive comparator for two strings.
SortRule(String, boolean) - Constructor for class weka.knowledgeflow.steps.Sorter.SortRule: Constructor
SortRule() - Constructor for class weka.knowledgeflow.steps.Sorter.SortRule: Constructor
SortRule(String) - Constructor for class weka.knowledgeflow.steps.Sorter.SortRule: Constructor
sortTipText() - Method in class weka.filters.unsupervised.attribute.AddValues: Returns the tip text for this property
sortTypeTipText() - Method in class weka.filters.unsupervised.attribute.SortLabels: Returns the tip text for this property.
sortWithIndex() - Method in class weka.core.matrix.DoubleVector: Sorts the array in place with index returned
sortWithIndex(int, int, IntVector) - Method in class weka.core.matrix.DoubleVector: Sorts the array in place with index changed
sortWithNoMissingValues(double[]) - Static method in class weka.core.Utils: Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
Sourcable - Interface in weka.classifiers: Interface for classifiers that can be converted to Java source.
Sourcable - Interface in weka.filters: Interface for filters that can be converted to Java source.
sourceClass(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.BinC45Split: Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.C45Split: Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.j48.NoSplit: Returns a string containing java source code equivalent to the test made at this node.
sourceExpression(int, Instances) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
SOUTH_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
spaceHorizontal(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: space out set of nodes evenly between left and right most node in the list
spaceVertical(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: space out set of nodes evenly between top and bottom most node in the list
SPARSE - Static variable in class weka.core.json.JSONInstances: the sparse attribute.
SPARSE1 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection: distribution type: sparse 1
SPARSE2 - Static variable in class weka.filters.unsupervised.attribute.RandomProjection: distribution type: sparse 2
SPARSE_SEPARATOR - Static variable in class weka.core.json.JSONInstances: the separator for index/value in case of sparse instances.
SparseArray - Class in weka.core.pmml: Implementation of a sparse array.
sparseDataTipText() - Method in class weka.core.converters.DatabaseLoader: Returns the tip text for this property
sparseDataTipText() - Method in class weka.experiment.InstanceQuery: Returns the tip text for this property
sparseIndices() - Method in class weka.classifiers.functions.SMO: Returns the indices in sparse format.
SparseInstance - Class in weka.core: Class for storing an instance as a sparse vector.
SparseInstance(Instance) - Constructor for class weka.core.SparseInstance: Constructor that generates a sparse instance from the given instance.
SparseInstance(SparseInstance) - Constructor for class weka.core.SparseInstance: Constructor that copies the info from the given instance.
SparseInstance(double, double[]) - Constructor for class weka.core.SparseInstance: Constructor that generates a sparse instance from the given parameters.
SparseInstance(double, double[], int[], int) - Constructor for class weka.core.SparseInstance: Constructor that initializes instance variable with given values.
SparseInstance(int) - Constructor for class weka.core.SparseInstance: Constructor of an instance that sets weight to one, all values to be missing, and the reference to the dataset to null.
SparseToNonSparse - Class in weka.filters.unsupervised.instance: An instance filter that converts all incoming sparse instances into non-sparse format.
SparseToNonSparse() - Constructor for class weka.filters.unsupervised.instance.SparseToNonSparse
sparseWeights() - Method in class weka.classifiers.functions.SMO: Returns the weights in sparse format.
SpecialFunctions - Class in weka.core: Class implementing some mathematical functions.
SpecialFunctions() - Constructor for class weka.core.SpecialFunctions
sphere - Variable in class weka.classifiers.lazy.kstar.KStarWrapper: used/reused to hold the sphere size
splash(Image, List<String>) - Static method in class weka.gui.SplashWindow: Open's a splash window using the specified image.
splash(URL) - Static method in class weka.gui.SplashWindow: Open's a splash window using the specified image.
splash(URL, List<String>) - Static method in class weka.gui.SplashWindow: Open's a splash window using the specified image and message
SplashWindow - Class in weka.gui: A Splash window.
Split - Class in weka.classifiers.trees.ht: Base class for different split types
Split() - Constructor for class weka.classifiers.trees.ht.Split
split(Instances) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Splits the given set of instances into subsets.
split() - Method in class weka.classifiers.trees.m5.RuleNode: Finds an attribute and split point for this node
splitAtt() - Method in class weka.classifiers.trees.m5.RuleNode: Get the index of the splitting attribute for this node
splitAttr() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Returns the attribute used in this split
splitAttr() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Returns the attribute used in this split
splitAttr() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Returns the attribute used in this split
splitAttributes() - Method in class weka.classifiers.trees.ht.Split
SplitCandidate - Class in weka.classifiers.trees.ht: Encapsulates a candidate split
SplitCandidate(Split, List<Map<String, WeightMass>>, double) - Constructor for class weka.classifiers.trees.ht.SplitCandidate: Constructor
splitConfidenceTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
SplitCriterion - Class in weka.classifiers.trees.j48: Abstract class for computing splitting criteria with respect to distributions of class values.
SplitCriterion() - Constructor for class weka.classifiers.trees.j48.SplitCriterion
splitCriterionTipText() - Method in class weka.classifiers.trees.HoeffdingTree: Returns the tip text for this property
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit: Computes entropy for given distribution.
splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.EntropySplitCrit: Computes entropy of test distribution with respect to training distribution.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit: This method is a straightforward implementation of the gain ratio criterion for the given distribution.
splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.GainRatioSplitCrit: This method computes the gain ratio in the same way C4.5 does.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit: This method is a straightforward implementation of the information gain criterion for the given distribution.
splitCritValue(Distribution, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit: This method computes the information gain in the same way C4.5 does.
splitCritValue(Distribution, double, double) - Method in class weka.classifiers.trees.j48.InfoGainSplitCrit: This method computes the information gain in the same way C4.5 does.
splitCritValue(Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion: Computes result of splitting criterion for given distribution.
splitCritValue(Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion: Computes result of splitting criterion for given training and test distributions.
splitCritValue(Distribution, Distribution, int) - Method in class weka.classifiers.trees.j48.SplitCriterion: Computes result of splitting criterion for given training and test distributions and given number of classes.
splitCritValue(Distribution, Distribution, Distribution) - Method in class weka.classifiers.trees.j48.SplitCriterion: Computes result of splitting criterion for given training and test distributions and given default distribution.
splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.Antd
splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.NominalAntd: Implements the splitData function.
splitData(Instances, double, double) - Method in class weka.classifiers.rules.JRip.NumericAntd: Implements the splitData function.
splitEnt(Distribution) - Method in class weka.classifiers.trees.j48.EntropyBasedSplitCrit: Computes entropy after splitting without considering the class values.
SplitEvaluate - Interface in weka.classifiers.trees.m5: Interface for objects that determine a split point on an attribute
SplitEvaluator - Interface in weka.experiment: Interface to objects able to generate a fixed set of results for a particular split of a dataset.
splitEvaluatorTipText() - Method in class weka.experiment.CrossValidationResultProducer: Returns the tip text for this property
splitEvaluatorTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
splitEvaluatorTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
SplitMetric - Class in weka.classifiers.trees.ht: Base class for split metrics
SplitMetric() - Constructor for class weka.classifiers.trees.ht.SplitMetric
SplitNode - Class in weka.classifiers.trees.ht: Class for a node that splits the data in a Hoeffding tree
SplitNode(Map<String, WeightMass>, Split) - Constructor for class weka.classifiers.trees.ht.SplitNode: Construct a new SplitNode
splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.BallSplitter: Splits a node into two.
splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.MedianDistanceFromArbitraryPoint: Splits a ball into two.
splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.MedianOfWidestDimension: Splits a ball into two.
splitNode(BallNode, int) - Method in class weka.core.neighboursearch.balltrees.PointsClosestToFurthestChildren: Splits a ball into two.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Splits a node into two.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.KMeansInpiredMethod: Splits a node into two such that the overall sum of squared distances of points to their centres on both sides of the (axis-parallel) splitting plane is minimum.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.MedianOfWidestDimension: Splits a node into two based on the median value of the dimension in which the points have the widest spread.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.MidPointOfWidestDimension: Splits a node into two based on the midpoint value of the dimension in which the points have the widest spread.
splitNode(KDTreeNode, int, double[][], double[][]) - Method in class weka.core.neighboursearch.kdtrees.SlidingMidPointOfWidestSide: Splits a node into two based on the midpoint value of the dimension in which the node's rectangle is widest.
splitOnResidualsTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
splitOptions(String) - Static method in class weka.core.Utils: Split up a string containing options into an array of strings, one for each option.
splitOptions(String, String[], char[]) - Static method in class weka.core.Utils: Split up a string containing options into an array of strings, one for each option.
splitPercentageTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
splitPercentTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
splitPoint() - Method in class weka.classifiers.trees.j48.BinC45Split: Returns the split point (numeric attribute only).
splitPoint() - Method in class weka.classifiers.trees.j48.C45Split: Returns the split point (numeric attribute only).
splitPointTipText() - Method in class weka.filters.unsupervised.instance.RemoveWithValues: Returns the tip text for this property
splitVal() - Method in class weka.classifiers.trees.m5.RuleNode: Get the split point for this node
splitValue() - Method in class weka.classifiers.trees.m5.CorrelationSplitInfo: Returns the split value
splitValue() - Method in interface weka.classifiers.trees.m5.SplitEvaluate: Returns the split value
splitValue() - Method in class weka.classifiers.trees.m5.YongSplitInfo: Returns the split value
spreadAttributeWeightTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
spreadAttributeWeightTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
spreadAttributeWeightTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
spreadAttributeWeightTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
spreadInitialCountTipText() - Method in class weka.classifiers.trees.REPTree: Returns the tip text for this property
SpreadSubsample - Class in weka.filters.supervised.instance: Produces a random subsample of a dataset.
SpreadSubsample() - Constructor for class weka.filters.supervised.instance.SpreadSubsample
sqDifference(int, double, double) - Method in class weka.core.EuclideanDistance: Returns the squared difference of two values of an attribute.
SqlViewer - Class in weka.gui.sql: Represents a little tool for querying SQL databases.
SqlViewer(JFrame) - Constructor for class weka.gui.sql.SqlViewer: initializes the SqlViewer.
SqlViewerDialog - Class in weka.gui.sql: A little dialog containing the SqlViewer.
SqlViewerDialog(JFrame) - Constructor for class weka.gui.sql.SqlViewerDialog: initializes the dialog.
SQLViewerPerspective - Class in weka.gui.beans: Simple Knowledge Flow perspective that wraps the SqlViewer class
SQLViewerPerspective() - Constructor for class weka.gui.beans.SQLViewerPerspective: Constructor
SQLViewerPerspective - Class in weka.gui.knowledgeflow: Perspective that wraps the {@code SQLViewer) component
SQLViewerPerspective() - Constructor for class weka.gui.knowledgeflow.SQLViewerPerspective: Constructor
sqrt() - Method in class weka.core.matrix.DoubleVector: Returns the square-root of all the elements in the vector
sqrt() - Method in class weka.core.matrix.Matrix: returns the square root of the matrix, i.e., X from the equation X*X = A.
Steps in the Calculation (see sqrtm in Matlab):
perform eigenvalue decomposition
[V,D]=eig(A) take the square root of all elements in D (only the ones with positive sign are considered for further computation)
S=sqrt(D) calculate the root
X=V*S/V, which can be also written as X=(V'\(V*S)')'
Note: since this method uses other high-level methods, it generates several instances of matrices.
square() - Method in class weka.core.matrix.DoubleVector: Returns the squared vector
square(double) - Static method in class weka.core.matrix.Maths: Returns the square of a value
SquaredEuclidean - Class in weka.core.pmml.jaxbbindings: Java class for squaredEuclidean element declaration.
SquaredEuclidean() - Constructor for class weka.core.pmml.jaxbbindings.SquaredEuclidean
SQUAREDLOSS - Static variable in class weka.classifiers.functions.SGD: the squared loss function.
src - Variable in class weka.gui.graphvisualizer.GraphEdge: The index of source node in Nodes vector
srcLbl - Variable in class weka.gui.graphvisualizer.GraphEdge: Label of source node
stableSort(int) - Method in class weka.core.Instances: Sorts the instances based on an attribute, using a stable sort.
stableSort(Attribute) - Method in class weka.core.Instances: Sorts the instances based on an attribute, using a stable sort.
stableSort(double[]) - Static method in class weka.core.Utils: Sorts a given array of doubles in ascending order and returns an array of integers with the positions of the elements of the original array in the sorted array.
Stack<T> - Class in weka.core.neighboursearch.covertrees: Class implementing a stack.
Stack() - Constructor for class weka.core.neighboursearch.covertrees.Stack: Constructor.
Stack(int) - Constructor for class weka.core.neighboursearch.covertrees.Stack: Constructor.
Stacking - Class in weka.classifiers.meta: Combines several classifiers using the stacking method.
Stacking() - Constructor for class weka.classifiers.meta.Stacking
stackTraceToString(Throwable) - Static method in class weka.knowledgeflow.LogManager: Utility method to convert a stack trace to a String
StandardEvaluationMetric - Interface in weka.classifiers.evaluation: Primarily a marker interface for a "standard" evaluation metric - i.e.
Standardize - Class in weka.filters.unsupervised.attribute: Standardizes all numeric attributes in the given dataset to have zero mean and unit variance (apart from the class attribute, if set).
Standardize() - Constructor for class weka.filters.unsupervised.attribute.Standardize
start() - Method in class weka.core.Debug.Clock: saves the current system time (or CPU time) in msec as start time
start() - Method in class weka.gui.beans.Loader: Start loading
start() - Method in class weka.gui.beans.MetaBean
start() - Method in interface weka.gui.beans.Startable: Start the flow running
start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Start the plotting thread
start() - Method in class weka.gui.boundaryvisualizer.BoundaryPanelDistributed: Start processing
start(String[]) - Method in class weka.gui.scripting.Script: Executes the script.
start() - Method in class weka.knowledgeflow.steps.BaseStep: Start processing.
start() - Method in interface weka.knowledgeflow.steps.BaseStepExtender: Start executing (if this component is a start point).
start() - Method in class weka.knowledgeflow.steps.DataGenerator: Start the data generation process.
start() - Method in class weka.knowledgeflow.steps.DataGrid: Start processing
start() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Start processing if operating as a start point in a flow
start() - Method in class weka.knowledgeflow.steps.GetDataFromResult
start() - Method in class weka.knowledgeflow.steps.Job
start() - Method in class weka.knowledgeflow.steps.Loader: Start executing
start() - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Start processing
start() - Method in interface weka.knowledgeflow.steps.Step: Start executing (if this component is a start point)
start_production() - Method in class weka.core.expressionlanguage.parser.Parser: Indicates start production.
start_production() - Method in class weka.core.json.Parser: Indicates start production.
start_state() - Method in class weka.core.expressionlanguage.parser.Parser: Indicates start state.
start_state() - Method in class weka.core.json.Parser: Indicates start state.
Startable - Interface in weka.gui.beans: Interface to something that is a start point for a flow and can be launched programatically.
startApp() - Static method in class weka.gui.beans.KnowledgeFlow: Static method that can be called from a running program to launch the KnowledgeFlow
startClock() - Method in class weka.core.Debug: starts the clock
startLoading() - Method in class weka.gui.beans.Loader: Start loading data
startPlotThread() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Starts the plotting thread.
StartSetHandler - Interface in weka.attributeSelection: Interface for search methods capable of doing something sensible given a starting set of attributes.
startSetTipText() - Method in class weka.attributeSelection.BestFirst: Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
startSetTipText() - Method in class weka.attributeSelection.Ranker: Returns the tip text for this property
startThread(SimpleCLIPanel.ClassRunner) - Method in class weka.gui.SimpleCLIPanel: Starts the thread.
startupCheck(boolean, PrintStream...) - Static method in class weka.core.WekaPackageManager
startUpComplete() - Method in interface weka.gui.beans.StartUpListener
StartUpListener - Interface in weka.gui.beans: Interface to something that can be notified of a successful startup
stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffPanel: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.arffviewer.ArffViewerMainPanel: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.LogWindow: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.sql.ResultPanel: Invoked when the target of the listener has changed its state.
stateChanged(ChangeEvent) - Method in class weka.gui.ViewerDialog: Invoked when the target of the listener has changed its state.
statisticIsMaximisable(String) - Method in class weka.classifiers.evaluation.AbstractEvaluationMetric: True if the optimum value of the named metric is a maximum value; false if the optimim value is a minimum value.
Statistics - Class in weka.core: Class implementing some distributions, tests, etc.
Statistics() - Constructor for class weka.core.Statistics
Stats - Class in weka.classifiers.trees.j48: Class implementing a statistical routine needed by J48 to compute its error estimate.
Stats() - Constructor for class weka.classifiers.trees.j48.Stats
Stats - Class in weka.experiment: A class to store simple statistics.
Stats() - Constructor for class weka.experiment.Stats
StatsHelper - Class in weka.core.expressionlanguage.weka: A helper class to expose a Stats object to a program
StatsHelper() - Constructor for class weka.core.expressionlanguage.weka.StatsHelper: Construct a StatsHelper
statusFrequencyTipText() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Return a tip text string for this property
statusFrequencyTipText() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Return a tip text string for this property
statusMessage(String) - Method in class weka.gui.beans.FlowRunner.SimpleLogger
statusMessage(String) - Method in class weka.gui.beans.LogPanel: Sends the supplied message to the status area.
statusMessage(String) - Method in interface weka.gui.Logger: Sends the supplied message to the status line.
statusMessage(String) - Method in class weka.gui.LogPanel: Sends the supplied message to the status line.
statusMessage(String) - Method in class weka.gui.SysErrLog: Sends the supplied message to the status line.
statusMessage(String) - Method in class weka.knowledgeflow.FlowRunner.SimpleLogger
statusMessage(String) - Method in class weka.knowledgeflow.LogManager: Output a status message
statusMessage(String) - Method in interface weka.knowledgeflow.StepManager: Write a status message
statusMessage(String) - Method in class weka.knowledgeflow.StepManagerImpl: Output a status message to the status area of the log
stdDev - Variable in class weka.experiment.Stats: The std deviation of values at the last calculateDerived() call
stdDevPrecTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
stdDevWidthTipText() - Method in class weka.experiment.ResultMatrix: Returns the tip text for this property.
stealPoints(MiddleOutConstructor.TempNode, Vector<MiddleOutConstructor.TempNode>, Vector<double[]>) - Method in class weka.core.neighboursearch.balltrees.MiddleOutConstructor: Removes points from old anchors that are nearer to the given new anchor and adds them to the list of points of the new anchor.
stem(String) - Method in class weka.core.stemmers.IteratedLovinsStemmer: Iterated stemming of the given word.
stem(String) - Method in class weka.core.stemmers.LovinsStemmer: Returns the stemmed version of the given word.
stem(String) - Method in class weka.core.stemmers.NullStemmer: Returns the word as it is.
stem(String) - Method in class weka.core.stemmers.SnowballStemmer: Returns the word in its stemmed form.
stem(String) - Method in interface weka.core.stemmers.Stemmer: Stems the given word and returns the stemmed version
Stemmer - Interface in weka.core.stemmers: Interface for all stemming algorithms.
stemmerTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property.
stemmerTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property.
stemmerTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
stemmerTipText() - Method in class weka.core.stemmers.SnowballStemmer: Returns the tip text for this property.
stemmerTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
Stemming - Class in weka.core.stemmers: A helper class for using the stemmers.
Stemming() - Constructor for class weka.core.stemmers.Stemming
stemString(String) - Method in class weka.core.stemmers.LovinsStemmer: Stems everything in the given string.
Step - Interface in weka.knowledgeflow.steps: Client API for Knowledge Flow steps.
STEP_EXECUTOR_SERVICE_NUM_THREADS - Static variable in class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults
STEP_EXECUTOR_SERVICE_NUM_THREADS_KEY - Static variable in class weka.knowledgeflow.BaseExecutionEnvironment.BaseExecutionEnvironmentDefaults
STEP_FIELD_NAME - Static variable in class weka.experiment.LearningRateResultProducer: The name of the key field containing the learning rate step number
STEP_LABEL_FONT_SIZE - Static variable in class weka.knowledgeflow.KFDefaults
STEP_LABEL_FONT_SIZE_KEY - Static variable in class weka.knowledgeflow.KFDefaults
StepEditorDialog - Class in weka.gui.knowledgeflow: Base class for step editor dialogs.
StepEditorDialog() - Constructor for class weka.gui.knowledgeflow.StepEditorDialog: Constructor
StepEditorDialog.ClosingListener - Interface in weka.gui.knowledgeflow: Interface for those that want to be notified when this dialog closes
stepInit() - Method in class weka.knowledgeflow.steps.AlterRelationName: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Appender: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.ASEvaluator: Initialize at the start of a run
stepInit() - Method in class weka.knowledgeflow.steps.ASSearchStrategy: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Associator: Initializes the step
stepInit() - Method in class weka.knowledgeflow.steps.BaseSimpleDataVisualizer
stepInit() - Method in interface weka.knowledgeflow.steps.BaseStepExtender: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.Block: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.BoundaryPlotter: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.ClassAssigner: Initialize the step prior to execution
stepInit() - Method in class weka.knowledgeflow.steps.Classifier
stepInit() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
stepInit() - Method in class weka.knowledgeflow.steps.ClassValuePicker: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.Clusterer: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.ClustererPerformanceEvaluator: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.CrossValidationFoldMaker: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.DataGenerator: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.DataGrid: Initialize the step;
stepInit() - Method in class weka.knowledgeflow.steps.DataVisualizer
stepInit() - Method in class weka.knowledgeflow.steps.Dummy: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.ExecuteProcess: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Filter: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.FlowByExpression: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.GetDataFromResult
stepInit() - Method in class weka.knowledgeflow.steps.ImageSaver: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.ImageViewer: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.IncrementalClassifierEvaluator: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.InstanceStreamToBatchMaker: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.Job
stepInit() - Method in class weka.knowledgeflow.steps.Join: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Loader: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.MakeResourceIntensive: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.MemoryBasedDataSource: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.ModelPerformanceChart: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Note: Initialize - does nothing in the case of a note :-)
stepInit() - Method in class weka.knowledgeflow.steps.PredictionAppender: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.Saver: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.SendToPerspective
stepInit() - Method in class weka.knowledgeflow.steps.SerializedModelSaver: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.SetPropertiesFromEnvironment: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.SetVariables: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.Sorter: Initialize the step.
stepInit() - Method in interface weka.knowledgeflow.steps.Step: Initialize the step.
stepInit() - Method in class weka.knowledgeflow.steps.StorePropertiesInEnvironment
stepInit() - Method in class weka.knowledgeflow.steps.StripChart
stepInit() - Method in class weka.knowledgeflow.steps.SubstringLabeler: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.SubstringReplacer: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.TestSetMaker: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.TextSaver: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.TextViewer: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.TrainingSetMaker: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.TrainTestSplitMaker: Initialize the step
stepInit() - Method in class weka.knowledgeflow.steps.WriteDataToResult
stepInit() - Method in class weka.knowledgeflow.steps.WriteWekaLog: Initialize the step
StepInjectorFlowRunner - Class in weka.knowledgeflow: A flow runner that runs a flow by injecting data into a target step
StepInjectorFlowRunner() - Constructor for class weka.knowledgeflow.StepInjectorFlowRunner
StepInteractiveViewer - Interface in weka.gui.knowledgeflow: Interface for GUI interactive viewer components that can be popped up from the contextual menu in the Knowledge Flow that appears when you right-click over a step on the layout.
stepIsResourceIntensive() - Method in interface weka.knowledgeflow.StepManager: Returns true if the step managed by this step manager has been marked as being resource (cpu/memory) intensive.
stepIsResourceIntensive() - Method in class weka.knowledgeflow.StepManagerImpl: Get whether the managed step is resource (cpu/memory) intensive or not
StepManager - Interface in weka.knowledgeflow: Client public interface for the StepManager.
StepManagerImpl - Class in weka.knowledgeflow: Concrete implementation of the StepManager interface.
StepManagerImpl(Step) - Constructor for class weka.knowledgeflow.StepManagerImpl: Constructor
stepMustRunSingleThreaded() - Method in class weka.knowledgeflow.steps.BaseStep: Get whether this step must run single threaded.
StepOutputListener - Interface in weka.knowledgeflow: Inteface to something that listens to the output from a Step
STEPS - Static variable in class weka.knowledgeflow.JSONFlowUtils
stepSizeTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
stepSizeTipText() - Method in class weka.experiment.LearningRateResultProducer: Returns the tip text for this property
stepStatusMessagePrefix() - Method in class weka.knowledgeflow.StepManagerImpl: Gets a prefix for the step managed by this manager.
StepTask<T> - Class in weka.knowledgeflow: A task that can be executed by the ExecutionEnvironment's submitTask() service.
StepTask(Step) - Constructor for class weka.knowledgeflow.StepTask: Constructor.
StepTask(Step, boolean) - Constructor for class weka.knowledgeflow.StepTask: Constructor.
StepTask(Step, StepTaskCallback<T>) - Constructor for class weka.knowledgeflow.StepTask: Constructor with supplied callback.
StepTask(Step, StepTaskCallback<T>, boolean) - Constructor for class weka.knowledgeflow.StepTask: Constructor with supplied callback.
StepTaskCallback<T> - Interface in weka.knowledgeflow: Callback that Steps can use when executing StepTasks via EnvironmentManager.submitTask().
StepTree - Class in weka.gui.knowledgeflow: Subclass of JTree for displaying available steps.
StepTree(MainKFPerspective) - Constructor for class weka.gui.knowledgeflow.StepTree: Constructor
StepTreeIgnore - Annotation Type in weka.gui.knowledgeflow: Marker annotation.
StepTreeLeafDetails - Class in weka.gui.knowledgeflow: Maintains information about a step in the StepTree - e.g.
StepTreeLeafDetails(Object) - Constructor for class weka.gui.knowledgeflow.StepTreeLeafDetails: Constructor
StepTreeLeafDetails(Object, boolean) - Constructor for class weka.gui.knowledgeflow.StepTreeLeafDetails: Constructor
StepVisual - Class in weka.gui.knowledgeflow: Class for managing the appearance of a step in the GUI Knowledge Flow environment.
stirlingFormula(double) - Static method in class weka.core.Statistics: Returns the Gamma function computed by Stirling's formula.
stop() - Method in class weka.core.Debug.Clock: saves the current system (or CPU time) in msec as stop time
STOP - Static variable in class weka.core.Trie.TrieNode: the stop character
stop() - Method in class weka.gui.beans.AbstractDataSink: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractEvaluator: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTestSetProducer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.AbstractTrainingSetProducer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.Appender: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.Associator: Stop any associator action
stop() - Method in interface weka.gui.beans.BeanCommon: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.ClassAssigner
stop() - Method in class weka.gui.beans.Classifier: Stop any classifier action
stop() - Method in class weka.gui.beans.ClassifierPerformanceEvaluator: Try and stop any action
stop() - Method in class weka.gui.beans.ClassValuePicker
stop() - Method in class weka.gui.beans.Clusterer: Stop any clusterer action
stop() - Method in class weka.gui.beans.ClustererPerformanceEvaluator: Try and stop any action
stop() - Method in class weka.gui.beans.CostBenefitAnalysis: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.CrossValidationFoldMaker: Stop any action
stop() - Method in class weka.gui.beans.DataVisualizer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.Filter: Stop all action if possible
stop() - Method in class weka.gui.beans.FlowByExpression
stop() - Method in class weka.gui.beans.ImageSaver
stop() - Method in class weka.gui.beans.ImageViewer
stop() - Method in class weka.gui.beans.IncrementalClassifierEvaluator: Stop all action
stop() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Stop any action (if possible).
stop() - Method in class weka.gui.beans.Join: Attempt to stop processing
stop() - Method in class weka.gui.beans.Loader: Stop any loading action.
stop() - Method in class weka.gui.beans.MetaBean: Stop all encapsulated beans
stop() - Method in class weka.gui.beans.ModelPerformanceChart: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.PredictionAppender
stop() - Method in class weka.gui.beans.Saver: Stops the bean
stop() - Method in class weka.gui.beans.SerializedModelSaver: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.Sorter: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.StripChart: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.SubstringLabeler: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.SubstringReplacer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.TestSetMaker
stop() - Method in class weka.gui.beans.TextSaver
stop() - Method in class weka.gui.beans.TextViewer: Stop any processing that the bean might be doing.
stop() - Method in class weka.gui.beans.TrainingSetMaker: Stop any action
stop() - Method in class weka.gui.beans.TrainTestSplitMaker: Stop processing
stop() - Method in class weka.gui.scripting.Script: Stops the execution of the script.
stop() - Method in class weka.knowledgeflow.steps.BaseStep: Request that processing be stopped.
stop() - Method in class weka.knowledgeflow.steps.ClassifierPerformanceEvaluator
stop() - Method in interface weka.knowledgeflow.steps.Step: Request a stop to all processing by this step (as soon as possible)
stopAllFlows() - Method in class weka.gui.beans.FlowRunner
stopClock(String) - Method in class weka.core.Debug: stops the clock and prints the message associated with the time, but only if the logging is enabled.
stopFlow() - Method in class weka.gui.knowledgeflow.VisibleLayout: Stop the flow from executing
stopMonitoring() - Method in class weka.gui.MemoryUsagePanel: stops the monitoring thread.
stopPlotting() - Method in class weka.gui.boundaryvisualizer.BoundaryPanel: Stop the plotting thread
stopPlotting() - Method in class weka.gui.boundaryvisualizer.BoundaryVisualizer: Stops the plotting thread.
stopProcessing() - Method in class weka.knowledgeflow.BaseExecutionEnvironment: The main point at which to request stop processing of a flow.
stopProcessing() - Method in interface weka.knowledgeflow.ExecutionEnvironment: Step/StepManager can use this to request a stop to all processing
stopProcessing() - Method in interface weka.knowledgeflow.FlowExecutor: Stop all processing
stopProcessing() - Method in class weka.knowledgeflow.FlowRunner: Attempt to stop processing in all steps
stopScript() - Method in class weka.gui.scripting.Script.ScriptThread: Stops the script execution.
stopThread() - Method in class weka.gui.SimpleCLIPanel: Stops the currently running thread, if any.
stopThreads() - Method in class weka.core.Memory: stops all the current threads, to make a restart possible
Stopwords - Class in weka.core: Class that can test whether a given string is a stop word.
Stopwords() - Constructor for class weka.core.Stopwords: initializes the stopwords (based on Rainbow).
StopwordsHandler - Interface in weka.core.stopwords: Interface for classes that support stopword handling.
stopwordsHandlerTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property.
stopwordsHandlerTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property.
stopwordsHandlerTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
stopwordsHandlerTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
stopwordsTipText() - Method in class weka.core.stopwords.AbstractFileBasedStopwords: Returns the tip text for this property.
stopwordsTipText() - Method in class weka.core.stopwords.MultiStopwords: Returns the tip text for this property.
stopwordsTipText() - Method in class weka.core.stopwords.RegExpFromFile: Returns the tip text for this property.
stopwordsTipText() - Method in class weka.core.stopwords.WordsFromFile: Returns the tip text for this property.
store(double, double, double) - Method in class weka.classifiers.lazy.kstar.KStarCache: Stores the specified values in the cahce table for easy retrieval.
storeEntry(String, String, Object) - Method in interface weka.core.metastore.MetaStore: Store a named entry
storeEntry(String, String, Object) - Method in class weka.core.metastore.XMLFileBasedMetaStore
storeOutOfBagPredictionsTipText() - Method in class weka.classifiers.meta.Bagging: Returns the tip text for this property
StorePropertiesInEnvironment - Class in weka.knowledgeflow.steps: Stores property values specified in incoming instances in the flow environment.
StorePropertiesInEnvironment() - Constructor for class weka.knowledgeflow.steps.StorePropertiesInEnvironment
StorePropertiesInEnvironmentStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Editor dialog for the StorePropertiesInEnvironment step.
StorePropertiesInEnvironmentStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.StorePropertiesInEnvironmentStepEditorDialog
StratifiedRemoveFolds - Class in weka.filters.supervised.instance: This filter takes a dataset and outputs a specified fold for cross validation.
StratifiedRemoveFolds() - Constructor for class weka.filters.supervised.instance.StratifiedRemoveFolds
stratify(Instances, int, Random) - Static method in class weka.classifiers.rules.RuleStats: Stratify the given data into the given number of bags based on the class values.
stratify(int) - Method in class weka.core.Instances: Stratifies a set of instances according to its class values if the class attribute is nominal (so that afterwards a stratified cross-validation can be performed).
StreamableFilter - Interface in weka.filters: Interface for filters can work with a stream of instances.
StreamThroughput - Class in weka.gui.beans: Class for measuring throughput of an incremental Knowledge Flow step.
StreamThroughput(String) - Constructor for class weka.gui.beans.StreamThroughput: Construct a new StreamThroughput
StreamThroughput(String, String, Logger) - Constructor for class weka.gui.beans.StreamThroughput: Construct a new StreamThroughput
StreamTokenizerUtils - Class in weka.core.converters: Helper class for using stream tokenizers
StreamTokenizerUtils() - Constructor for class weka.core.converters.StreamTokenizerUtils
STRING - Static variable in class weka.core.Attribute: Constant set for attributes with string values.
STRING - Static variable in interface weka.core.expressionlanguage.parser.sym
STRING - Static variable in class weka.core.json.Scanner
STRING - Static variable in interface weka.core.json.sym
STRING - Static variable in class weka.experiment.DatabaseUtils: Type mapping for STRING used for reading experiment results.
STRING1 - Static variable in class weka.core.expressionlanguage.parser.Scanner
STRING2 - Static variable in class weka.core.expressionlanguage.parser.Scanner
stringAttributesTipText() - Method in class weka.core.converters.CSVLoader: Returns the tip text for this property.
StringCompare() - Constructor for class weka.core.ClassDiscovery.StringCompare
StringConstant(String) - Constructor for class weka.core.expressionlanguage.common.Primitives.StringConstant
stringFreeStructure() - Method in class weka.core.Instances: Create a copy of the structure.
StringKernel - Class in weka.classifiers.functions.supportVector: Implementation of the subsequence kernel (SSK) as described in [1] and of the subsequence kernel with lambda pruning (SSK-LP) as described in [2].

For more information, see

Huma Lodhi, Craig Saunders, John Shawe-Taylor, Nello Cristianini, Christopher J.
StringKernel() - Constructor for class weka.classifiers.functions.supportVector.StringKernel: default constructor
StringKernel(Instances, int, int, double, boolean) - Constructor for class weka.classifiers.functions.supportVector.StringKernel: creates a new StringKernel object.
StringLocator - Class in weka.core: This class locates and records the indices of String attributes, recursively in case of Relational attributes.
StringLocator(Instances) - Constructor for class weka.core.StringLocator: initializes the StringLocator with the given data
StringLocator(Instances, int, int) - Constructor for class weka.core.StringLocator: Initializes the StringLocator with the given data.
StringLocator(Instances, int[]) - Constructor for class weka.core.StringLocator: Initializes the AttributeLocator with the given data.
stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Edge: This will calculate how large a rectangle using the FontMetrics passed that the lines of the label will take up
stringSize(FontMetrics) - Method in class weka.gui.treevisualizer.Node: This will return the width and height of the rectangle that the text will fit into.
stringToLevel(String) - Static method in class weka.core.Debug.Log: turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).
stringToLevel(String) - Static method in class weka.core.Debug: turns the string representing a level, e.g., "FINE" or "ALL" into the corresponding level (case-insensitive).
stringToLevel(String) - Static method in enum weka.knowledgeflow.LoggingLevel: Return LoggingLevel given its name as a string
StringToNominal - Class in weka.filters.unsupervised.attribute: Converts a range of string attributes (unspecified number of values) to nominal (set number of values).
StringToNominal() - Constructor for class weka.filters.unsupervised.attribute.StringToNominal
StringToWordVector - Class in weka.filters.unsupervised.attribute: Converts string attributes into a set of numeric attributes representing word occurrence information from the text contained in the strings.
StringToWordVector() - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector: Default constructor.
StringToWordVector(int) - Constructor for class weka.filters.unsupervised.attribute.StringToWordVector: Constructor that allows specification of the target number of words in the output.
stringValue(int) - Method in class weka.core.AbstractInstance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
stringValue(Attribute) - Method in class weka.core.AbstractInstance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
stringValue(int) - Method in interface weka.core.Instance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
stringValue(Attribute) - Method in interface weka.core.Instance: Returns the value of a nominal, string, date, or relational attribute for the instance as a string.
StringVariable(String) - Constructor for class weka.core.expressionlanguage.common.Primitives.StringVariable
StripChart - Class in weka.gui.beans: Bean that can display a horizontally scrolling strip chart.
StripChart() - Constructor for class weka.gui.beans.StripChart
StripChart - Class in weka.knowledgeflow.steps: A step that can display a viewer showing a right-to-left scrolling chart for streaming data
StripChart() - Constructor for class weka.knowledgeflow.steps.StripChart
StripChart.PlotNotificationListener - Interface in weka.knowledgeflow.steps: StripChartInteractiveView implements this in order to receive data points.
StripChartBeanInfo - Class in weka.gui.beans: Bean info class for the strip chart bean
StripChartBeanInfo() - Constructor for class weka.gui.beans.StripChartBeanInfo
StripChartCustomizer - Class in weka.gui.beans: GUI Customizer for the strip chart bean
StripChartCustomizer() - Constructor for class weka.gui.beans.StripChartCustomizer
StripChartInteractiveView - Class in weka.gui.knowledgeflow.steps: Implements the actual strip chart view
StripChartInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.StripChartInteractiveView
StructureNotReadyException(String) - Constructor for exception weka.core.converters.Loader.StructureNotReadyException
StructureProducer - Interface in weka.gui.beans: Interface for something that can describe the structure of what is encapsulated in a named event type as an empty set of Instances (i.e.
STYLE_STDERR - Static variable in class weka.gui.LogWindow: the name of the style for stderr
STYLE_STDOUT - Static variable in class weka.gui.LogWindow: the name of the style for stdout
sub(int, Instance) - Method in class weka.classifiers.trees.j48.Distribution: Subtracts given instance from given bag.
subFlowContains(BeanInstance) - Method in class weka.gui.beans.MetaBean
subList(int, int) - Method in class weka.core.neighboursearch.covertrees.Stack: Returns a sublist of the elements in the stack.
submitTask(StepTask<T>) - Method in class weka.knowledgeflow.BaseExecutionEnvironment: Submit a task to be run by the execution environment.
submitTask(StepTask<T>) - Method in interface weka.knowledgeflow.ExecutionEnvironment: Submit a task to be run by the execution environment.
subpath(int) - Method in class weka.core.PropertyPath.Path: returns a subpath of the current structure, starting with the specified element index up to the end
subpath(int, int) - Method in class weka.core.PropertyPath.Path: returns a subpath of the current structure, starting with the specified element index up.
subsequenceLengthTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
SubsetByExpression - Class in weka.filters.unsupervised.instance: Filters instances according to a user-specified expression.

Examples:
- extracting only mammals and birds from the 'zoo' UCI dataset:
(CLASS is 'mammal') or (CLASS is 'bird')
- extracting only animals with at least 2 legs from the 'zoo' UCI dataset:
(ATT14 >= 2)
- extracting only instances with non-missing 'wage-increase-second-year'
from the 'labor' UCI dataset:
not ismissing(ATT3)

Valid options are:
SubsetByExpression() - Constructor for class weka.filters.unsupervised.instance.SubsetByExpression
subsetDL(double, double, double) - Static method in class weka.classifiers.rules.RuleStats: Subset description length:
S(t,k,p) = -k*log2(p)-(n-k)log2(1-p) Details see Quilan: "MDL and categorical theories (Continued)",ML95
SubsetEvaluator - Interface in weka.attributeSelection: Interface for attribute subset evaluators.
SubspaceCluster - Class in weka.datagenerators.clusterers: A data generator that produces data points in hyperrectangular subspace clusters.
SubspaceCluster() - Constructor for class weka.datagenerators.clusterers.SubspaceCluster: initializes the generator, sets the number of clusters to 0, since user has to specify them explicitly
SubspaceClusterDefinition - Class in weka.datagenerators.clusterers: A single cluster for the SubspaceCluster data generator.
SubspaceClusterDefinition() - Constructor for class weka.datagenerators.clusterers.SubspaceClusterDefinition: Needed so that this class can be found as permissible.
SubspaceClusterDefinition(ClusterGenerator) - Constructor for class weka.datagenerators.clusterers.SubspaceClusterDefinition: initializes the cluster with default values
subSpaceSizeTipText() - Method in class weka.classifiers.meta.RandomSubSpace: Returns the tip text for this property
substitute(String) - Method in class weka.core.Environment: Substitute a variable names for their values in the given string.
substract(AlgVector) - Method in class weka.core.AlgVector: Returns the difference of this vector minus another.
SubstringLabeler - Class in weka.gui.beans: A bean that finds matches in string attribute values (using either substring or regular expression matches) and labels the instance (sets the value of a new attribute) according to the supplied label for the matching rule.
SubstringLabeler() - Constructor for class weka.gui.beans.SubstringLabeler: Constructor
SubstringLabeler - Class in weka.knowledgeflow.steps: Step that appends a label to incoming instances according to substring matches in string attributes.
SubstringLabeler() - Constructor for class weka.knowledgeflow.steps.SubstringLabeler
SubstringLabelerBeanInfo - Class in weka.gui.beans: Bean info class for the substring labeler bean
SubstringLabelerBeanInfo() - Constructor for class weka.gui.beans.SubstringLabelerBeanInfo
SubstringLabelerCustomizer - Class in weka.gui.beans: Customizer class for the Substring labeler step
SubstringLabelerCustomizer() - Constructor for class weka.gui.beans.SubstringLabelerCustomizer
SubstringLabelerMatchRule() - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Constructor
SubstringLabelerMatchRule(String) - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Constructor
SubstringLabelerMatchRule(String, boolean, boolean, String) - Constructor for class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Constructor
SubstringLabelerRules - Class in weka.gui.beans: Manages a list of match rules for labeling strings.
SubstringLabelerRules(String, String, boolean, boolean, Instances, String, Logger, Environment) - Constructor for class weka.gui.beans.SubstringLabelerRules: Constructor
SubstringLabelerRules(String, String, Instances) - Constructor for class weka.gui.beans.SubstringLabelerRules: Constructor.
SubstringLabelerRules.SubstringLabelerMatchRule - Class in weka.gui.beans: Inner class encapsulating the logic for matching
SubstringLabelerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the SubstringLabeler step
SubstringLabelerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SubstringLabelerStepEditorDialog
SubstringReplacer - Class in weka.gui.beans: A bean that can replace substrings in the values of string attributes.
SubstringReplacer() - Constructor for class weka.gui.beans.SubstringReplacer: Constructs a new SubstringReplacer
SubstringReplacer - Class in weka.knowledgeflow.steps: A step that can replace sub-strings in the values of string attributes.
SubstringReplacer() - Constructor for class weka.knowledgeflow.steps.SubstringReplacer
SubstringReplacerBeanInfo - Class in weka.gui.beans: Bean info class for the substring replacer
SubstringReplacerBeanInfo() - Constructor for class weka.gui.beans.SubstringReplacerBeanInfo
SubstringReplacerCustomizer - Class in weka.gui.beans: Customizer for the SubstringReplacer
SubstringReplacerCustomizer() - Constructor for class weka.gui.beans.SubstringReplacerCustomizer: Constructor
SubstringReplacerMatchRule() - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Constructor
SubstringReplacerMatchRule(String) - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Constructor
SubstringReplacerMatchRule(String, String, boolean, boolean, String) - Constructor for class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Constructor
SubstringReplacerRules - Class in weka.gui.beans: Manages a list of match and replace rules for replacing values in string attributes
SubstringReplacerRules(String, Instances, String, Logger, Environment) - Constructor for class weka.gui.beans.SubstringReplacerRules: Constructor
SubstringReplacerRules(String, Instances) - Constructor for class weka.gui.beans.SubstringReplacerRules: Constructor.
SubstringReplacerRules.SubstringReplacerMatchRule - Class in weka.gui.beans: Inner class encapsulating the logic for matching and replacing.
SubstringReplacerStepEditorDialog - Class in weka.gui.knowledgeflow.steps: Step editor dialog for the SubstringReplacer step
SubstringReplacerStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.SubstringReplacerStepEditorDialog
subtract(AprioriItemSet) - Method in class weka.associations.AprioriItemSet: Subtracts an item set from another one.
subtract(Distribution) - Method in class weka.classifiers.trees.j48.Distribution: Subtracts the given distribution from this one.
subtract(double[]) - Method in class weka.core.pmml.VectorInstance: Subtract the values in the supplied array from this vector instance
subtract(VectorInstance) - Method in class weka.core.pmml.VectorInstance: Subtract the supplied VectorInstance from this one and return the result as a new VectorInstance
subtract(double, double) - Method in class weka.experiment.PairedStats: Removes an observed pair of values.
subtract(double[], double[]) - Method in class weka.experiment.PairedStats: Removes an array of observed pair of values.
subtract(double) - Method in class weka.experiment.Stats: Removes a value to the observed values (no checking is done that the value being removed was actually added).
subtract(double, double) - Method in class weka.experiment.Stats: Subtracts a weighted value from the observed values
subtreeRaisingTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
subvector(int, int) - Method in class weka.core.matrix.DoubleVector: Returns a subvector.
subvector(IntVector) - Method in class weka.core.matrix.DoubleVector: Returns a subvector.
subvector(int, int) - Method in class weka.core.matrix.IntVector: Returns a subvector.
subvector(IntVector) - Method in class weka.core.matrix.IntVector: Returns a subvector as indexed by an IntVector.
sum(Map<String, WeightMass>) - Static method in class weka.classifiers.trees.ht.SplitMetric: Utility method to return the sum of instance weight in a distribution
sum() - Method in class weka.core.matrix.DoubleVector: Returns the sum of all elements in the vector.
sum(double[]) - Static method in class weka.core.Utils: Computes the sum of the elements of an array of doubles.
sum(int[]) - Static method in class weka.core.Utils: Computes the sum of the elements of an array of integers.
sum - Variable in class weka.experiment.Stats: The sum of values seen
sum2() - Method in class weka.core.matrix.DoubleVector: Returns the squared sum of all elements in the vector.
sum2(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Returns ||u-v||^2
Summarizable - Interface in weka.core: Interface to something that provides a short textual summary (as opposed to toString() which is usually a fairly complete description) of itself.
sumOfWeights() - Method in class weka.core.Instances: Computes the sum of all the instances' weights.
sumSq - Variable in class weka.experiment.Stats: The sum of values squared seen
SupervisedFilter - Interface in weka.filters: Interface for filters that make use of a class attribute.
support() - Method in class weka.associations.ItemSet: Outputs the support for an item set.
support() - Method in class weka.associations.LabeledItemSet: Outputs the support for an item set.
supports(Capabilities) - Method in class weka.core.Capabilities: Returns true if the currently set capabilities support at least all of the capabilities of the given Capabilities object (checks only the enum!)
supportsCustomEditor() - Method in class weka.gui.beans.EnvironmentField: Deprecated.
supportsCustomEditor() - Method in class weka.gui.ColorEditor: We use JColorChooser, so return true
supportsCustomEditor() - Method in class weka.gui.CostMatrixEditor: Indicates whether the cost matrix can be edited in a GUI, which it can.
supportsCustomEditor() - Method in class weka.gui.EnvironmentField
supportsCustomEditor() - Method in class weka.gui.FileEditor: Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.GenericArrayEditor: Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.GenericObjectEditor: Returns true because we do support a custom editor.
supportsCustomEditor() - Method in class weka.gui.PasswordField
supportsCustomEditor() - Method in class weka.gui.SimpleDateFormatEditor: Indicates whether the date format can be edited in a GUI, which it can.
supportsMaybe(Capabilities) - Method in class weka.core.Capabilities: Returns true if the currently set capabilities support (or have a dependency) at least all of the capabilities of the given Capabilities object (checks only the enum!)
SupportVector - Class in weka.core.pmml.jaxbbindings: Java class for SupportVector element declaration.
SupportVector() - Constructor for class weka.core.pmml.jaxbbindings.SupportVector
SupportVectorMachine - Class in weka.core.pmml.jaxbbindings: Java class for SupportVectorMachine element declaration.
SupportVectorMachine() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectorMachine
SupportVectorMachineModel - Class in weka.classifiers.pmml.consumer: Implements a PMML SupportVectorMachineModel
SupportVectorMachineModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.SupportVectorMachineModel: Construct a new SupportVectorMachineModel encapsulating the information provided in the PMML document.
SupportVectorMachineModel - Class in weka.core.pmml.jaxbbindings: Java class for SupportVectorMachineModel element declaration.
SupportVectorMachineModel() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectorMachineModel
SupportVectors - Class in weka.core.pmml.jaxbbindings: Java class for SupportVectors element declaration.
SupportVectors() - Constructor for class weka.core.pmml.jaxbbindings.SupportVectors
SUPPRESS_PROPERTY_WARNINGS - Static variable in class weka.core.xml.XMLSerialization: List of fully qualified property names to suppress any warning messages for
suppressMappingReportTipText() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the tip text for this property
suppressOutputTipText() - Method in class weka.classifiers.evaluation.output.prediction.AbstractOutput: Returns the tip text for this property.
svd() - Method in class weka.core.matrix.Matrix: Singular Value Decomposition
SVMCLASSIFICATIONMETHOD - Enum in weka.core.pmml.jaxbbindings: Java class for SVM-CLASSIFICATION-METHOD.
SVMLightLoader - Class in weka.core.converters: Reads a source that is in svm light format.

For more information about svm light see:

http://svmlight.joachims.org/
SVMLightLoader() - Constructor for class weka.core.converters.SVMLightLoader
SVMLightSaver - Class in weka.core.converters: Writes to a destination that is in svm light format.

For more information about svm light see:

http://svmlight.joachims.org/
Valid options are:
SVMLightSaver() - Constructor for class weka.core.converters.SVMLightSaver: Constructor.
SVMOutput(int, Instance) - Method in class weka.classifiers.functions.SMO.BinarySMO: Computes SVM output for given instance.
SVMOutput(Instance) - Method in class weka.classifiers.functions.supportVector.RegOptimizer
SVMREPRESENTATION - Enum in weka.core.pmml.jaxbbindings: Java class for SVM-REPRESENTATION.
swap(int, int) - Method in class weka.core.FastVector: Deprecated.

Swaps two elements in the vector.
swap(int, int) - Method in class weka.core.Instances: Swaps two instances in the set.
swap(int, int) - Method in class weka.core.matrix.DoubleVector: Swaps the values stored at i and j
swap(int, int) - Method in class weka.core.matrix.IntVector: Swaps the values stored at i and j
SwapValues - Class in weka.filters.unsupervised.attribute: Swaps two values of a nominal attribute.
SwapValues() - Constructor for class weka.filters.unsupervised.attribute.SwapValues
switchSetup() - Method in class weka.gui.sql.ConnectionPanel: Lets the user select a props file for changing the database connection parameters.
switchTo(AbstractSetupPanel, Experiment) - Method in class weka.gui.experiment.SetupModePanel: Switches to the specified panel.
switchToAdvanced(Experiment) - Method in class weka.gui.experiment.SetupModePanel: Switches to the advanced panel.
sym - Interface in weka.core.expressionlanguage.parser: CUP generated interface containing symbol constants.
sym - Interface in weka.core.json: CUP generated interface containing symbol constants.
symmetricalUncertainty(double[][]) - Static method in class weka.core.ContingencyTables: Calculates the symmetrical uncertainty for base 2.
SymmetricalUncertAttributeEval - Class in weka.attributeSelection: SymmetricalUncertAttributeEval :

Evaluates the worth of an attribute by measuring the symmetrical uncertainty with respect to the class.
SymmetricalUncertAttributeEval() - Constructor for class weka.attributeSelection.SymmetricalUncertAttributeEval: Constructor
Sync(BayesNet) - Method in class weka.classifiers.bayes.net.BIFReader: synchronizes the node ordering of this Bayes network with those in the other network (if possible).
synopsis() - Method in class weka.core.Option: Returns the option's synopsis.
SyntaxDocument - Class in weka.gui.scripting: Highlights syntax in a DefaultStyledDocument.
SyntaxDocument(Properties) - Constructor for class weka.gui.scripting.SyntaxDocument: Initializes the document.
SyntaxDocument.ATTR_TYPE - Enum in weka.gui.scripting: The attribute type.
SyntaxException - Exception in weka.core.expressionlanguage.core: An exception to represent an invalid syntax of a program
SyntaxException(String) - Constructor for exception weka.core.expressionlanguage.core.SyntaxException: Constructs a SyntaxException with a message
SysErrLog - Class in weka.gui: This Logger just sends messages to System.err.
SysErrLog() - Constructor for class weka.gui.SysErrLog
SystemInfo - Class in weka.core: This class prints some information about the system setup, like Java version, JVM settings etc.
SystemInfo() - Constructor for class weka.core.SystemInfo: initializes the object and reads the system information

T

t1TipText() - Method in class weka.clusterers.Canopy: Tip text for this property
t2TipText() - Method in class weka.clusterers.Canopy: Tip text for this property
TAB_INSTANCES - Static variable in class weka.gui.arffviewer.ArffPanel: the name of the tab for instances that were set directly
tabClosing(int) - Method in interface weka.gui.CloseableTabTitle.ClosingCallback
tableChanged(TableModelEvent) - Method in class weka.gui.arffviewer.ArffTable: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
tableChanged(TableModelEvent) - Method in class weka.gui.InteractiveTablePanel.InteractiveTableModelListener
tableChanged(TableModelEvent) - Method in class weka.gui.SortedTableModel: This fine grain notification tells listeners the exact range of cells, rows, or columns that changed.
TableEntry(int, double, double, double, KStarCache.TableEntry) - Constructor for class weka.classifiers.lazy.kstar.KStarCache.TableEntry: Constructor
tableExists(String) - Method in class weka.experiment.DatabaseUtils: Checks that a given table exists.
TableLocator - Class in weka.core.pmml.jaxbbindings: Java class for TableLocator element declaration.
TableLocator() - Constructor for class weka.core.pmml.jaxbbindings.TableLocator
tableNameTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.global.TabuSearch
tabuListTipText() - Method in class weka.classifiers.bayes.net.search.local.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.global.TabuSearch
TabuSearch - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm uses tabu search for finding a well scoring Bayes network structure.
TabuSearch() - Constructor for class weka.classifiers.bayes.net.search.local.TabuSearch
Tag - Class in weka.core: A Tag simply associates a numeric ID with a String description.
Tag() - Constructor for class weka.core.Tag: Creates a new default Tag
Tag(int, String) - Constructor for class weka.core.Tag: Creates a new Tag instance.
Tag(int, String, String) - Constructor for class weka.core.Tag: Creates a new Tag instance.
Tag(int, String, String, boolean) - Constructor for class weka.core.Tag
TAG_ACTUAL_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the actual_nominal tag.
TAG_ACTUAL_VALUE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the actual_numeric tag.
TAG_ATTRIBUTE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the attribute tag.
TAG_ATTRIBUTE - Static variable in class weka.core.xml.XMLInstances: the attribute element
TAG_ATTRIBUTES - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the attributes tag.
TAG_ATTRIBUTES - Static variable in class weka.core.xml.XMLInstances: the attributes element
TAG_BODY - Static variable in class weka.core.xml.XMLInstances: the body element
TAG_CLASS_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the class_label tag.
TAG_DATASET - Static variable in class weka.core.xml.XMLInstances: the root element
TAG_DISTRIBUTION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the distribution tag.
TAG_ERROR - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the error tag.
TAG_HEADER - Static variable in class weka.core.xml.XMLInstances: the header element
TAG_INSTANCE - Static variable in class weka.core.xml.XMLInstances: the instance element
TAG_INSTANCES - Static variable in class weka.core.xml.XMLInstances: the data element
TAG_LABEL - Static variable in class weka.core.xml.XMLInstances: the label element
TAG_LABELS - Static variable in class weka.core.xml.XMLInstances: the labels element
TAG_METADATA - Static variable in class weka.core.xml.XMLInstances: the meta-data element
TAG_NOTES - Static variable in class weka.core.xml.XMLInstances: the notes element
TAG_OBJECT - Static variable in class weka.core.xml.XMLSerialization: the tag for an object
TAG_OPTION - Static variable in class weka.core.xml.XMLOptions: tag for a single option.
TAG_OPTIONS - Static variable in class weka.core.xml.XMLOptions: tag for a list of options.
TAG_PREDICTED_LABEL - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted_nominal tag.
TAG_PREDICTED_VALUE - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predicted_numeric tag.
TAG_PREDICTION - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the prediction tag.
TAG_PREDICTIONS - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the predictions tag.
TAG_PROPERTY - Static variable in class weka.core.xml.XMLInstances: the property element
TAG_VALUE - Static variable in class weka.core.xml.XMLInstances: the value element
TAGS_ATTRIBUTETYPE - Static variable in class weka.filters.unsupervised.attribute.RemoveType: Tag allowing selection of attribute type to delete
TAGS_CLUSTERSUBTYPE - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: the tags for the cluster types
TAGS_CLUSTERTYPE - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: the tags for the cluster types
TAGS_CV_TYPE - Static variable in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm: the score types
TAGS_DSTRS_TYPE - Static variable in class weka.filters.unsupervised.attribute.RandomProjection: The types of distributions that can be used for calculating the random matrix
TAGS_EVAL - Static variable in class weka.classifiers.meta.IterativeClassifierOptimizer
TAGS_EVALUATION - Static variable in class weka.attributeSelection.ClassifierSubsetEval: Holds all tags for metrics
TAGS_EVALUATION - Static variable in class weka.attributeSelection.WrapperSubsetEval: Holds all tags for metrics
TAGS_EVALUATION - Static variable in class weka.classifiers.rules.DecisionTable
TAGS_FILTER - Static variable in class weka.classifiers.functions.GaussianProcesses: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMO: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.classifiers.functions.SMOreg: The filter to apply to the training data
TAGS_FILTER - Static variable in class weka.filters.unsupervised.attribute.StringToWordVector: Specifies whether document's (instance's) word frequencies are to be normalized.
TAGS_FORMAT - Static variable in class weka.core.Debug.Clock: the output formats
TAGS_GUI - Static variable in class weka.gui.Main: GUI tags.
TAGS_INPUTORDER - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: the input order tags
TAGS_LINK_TYPE - Static variable in class weka.clusterers.HierarchicalClusterer
TAGS_MATRIX_SOURCE - Static variable in class weka.classifiers.meta.CostSensitiveClassifier: Specify possible sources of the cost matrix
TAGS_METHOD - Static variable in class weka.classifiers.meta.MultiClassClassifier: The error correction modes
TAGS_MISSING - Static variable in class weka.classifiers.lazy.KStar: Define possible missing value handling methods
TAGS_PATTERN - Static variable in class weka.datagenerators.clusterers.BIRCHCluster: the pattern tags
TAGS_PRUNING - Static variable in class weka.classifiers.functions.supportVector.StringKernel: Pruning methods
TAGS_RULES - Static variable in class weka.classifiers.meta.Vote: combination rules
TAGS_SCORE_TYPE - Static variable in class weka.classifiers.bayes.net.search.local.LocalScoreSearchAlgorithm: the score types
TAGS_SELECTION - Static variable in class weka.associations.Apriori: Metric types.
TAGS_SELECTION - Static variable in class weka.associations.DefaultAssociationRule: Tags for display in the GUI
TAGS_SELECTION - Static variable in class weka.attributeSelection.BestFirst: search directions
TAGS_SELECTION - Static variable in class weka.classifiers.functions.LinearRegression: Attribute selection methods
TAGS_SELECTION - Static variable in class weka.classifiers.functions.SGD: Loss functions to choose from
TAGS_SELECTION - Static variable in class weka.classifiers.functions.SGDText: Loss functions to choose from
TAGS_SELECTION - Static variable in class weka.classifiers.trees.HoeffdingTree
TAGS_SELECTION - Static variable in class weka.clusterers.SimpleKMeans: Initialization methods
TAGS_SELECTION2 - Static variable in class weka.classifiers.trees.HoeffdingTree
TAGS_SORTTYPE - Static variable in class weka.filters.unsupervised.attribute.SortLabels: Tag allowing selection of sort type.
TAGS_TYPE - Static variable in class weka.filters.unsupervised.attribute.Add: the attribute type.
TAGS_WEIGHTING - Static variable in class weka.classifiers.lazy.IBk: possible instance weighting methods.
takeSample(double[], Random) - Static method in class weka.core.Utils: Takes a sample based on the given array of weights based on Walker's method.
TAN - Class in weka.classifiers.bayes.net.search.global: This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.

For more information see:

N.
TAN() - Constructor for class weka.classifiers.bayes.net.search.global.TAN
TAN - Class in weka.classifiers.bayes.net.search.local: This Bayes Network learning algorithm determines the maximum weight spanning tree and returns a Naive Bayes network augmented with a tree.

For more information see:

N.
TAN() - Constructor for class weka.classifiers.bayes.net.search.local.TAN
Tanimoto - Class in weka.core.pmml.jaxbbindings: Java class for tanimoto element declaration.
Tanimoto() - Constructor for class weka.core.pmml.jaxbbindings.Tanimoto
Target - Class in weka.core.pmml.jaxbbindings: Java class for Target element declaration.
Target() - Constructor for class weka.core.pmml.jaxbbindings.Target
TargetMetaInfo - Class in weka.core.pmml: Class to encapsulate information about a Target.
Targets - Class in weka.core.pmml.jaxbbindings: Java class for Targets element declaration.
Targets() - Constructor for class weka.core.pmml.jaxbbindings.Targets
TargetValue - Class in weka.core.pmml.jaxbbindings: Java class for TargetValue element declaration.
TargetValue() - Constructor for class weka.core.pmml.jaxbbindings.TargetValue
TargetValueCount - Class in weka.core.pmml.jaxbbindings: Java class for TargetValueCount element declaration.
TargetValueCount() - Constructor for class weka.core.pmml.jaxbbindings.TargetValueCount
TargetValueCounts - Class in weka.core.pmml.jaxbbindings: Java class for TargetValueCounts element declaration.
TargetValueCounts() - Constructor for class weka.core.pmml.jaxbbindings.TargetValueCounts
Task - Interface in weka.experiment: Interface to something that can be remotely executed as a task.
taskFailed(StepTask<T>, ExecutionResult<T>) - Method in interface weka.knowledgeflow.StepTaskCallback: Gets called if the StepTask fails for some reason
taskFinished() - Method in class weka.gui.LogPanel: Record a task ending
taskFinished() - Method in interface weka.gui.TaskLogger: Tells the task logger that a task has completed
taskFinished() - Method in class weka.gui.WekaTaskMonitor: Tells the panel that a task has completed
taskFinished(ExecutionResult<T>) - Method in interface weka.knowledgeflow.StepTaskCallback: Gets called when the StepTask finishes processing
TaskLogger - Interface in weka.gui: Interface for objects that display log and display information on running tasks.
taskStarted() - Method in class weka.gui.LogPanel: Record the starting of a new task
taskStarted() - Method in interface weka.gui.TaskLogger: Tells the task logger that a new task has been started
taskStarted() - Method in class weka.gui.WekaTaskMonitor: Tells the panel that a new task has been started
TaskStatusInfo - Class in weka.experiment: A class holding information for tasks being executed on RemoteEngines.
TaskStatusInfo() - Constructor for class weka.experiment.TaskStatusInfo
tauVal(double[][]) - Static method in class weka.core.ContingencyTables: Computes Goodman and Kruskal's tau-value for a contingency table.
Taxonomy - Class in weka.core.pmml.jaxbbindings: Java class for Taxonomy element declaration.
Taxonomy() - Constructor for class weka.core.pmml.jaxbbindings.Taxonomy
TechnicalInformation - Class in weka.core: Used for paper references in the Javadoc and for BibTex generation.
TechnicalInformation(TechnicalInformation.Type) - Constructor for class weka.core.TechnicalInformation: Initializes the information with the given type
TechnicalInformation(TechnicalInformation.Type, String) - Constructor for class weka.core.TechnicalInformation: Initializes the information with the given type
TechnicalInformation.Field - Enum in weka.core: the possible fields
TechnicalInformation.Type - Enum in weka.core: the different types of information
TechnicalInformationHandler - Interface in weka.core: For classes that are based on some kind of publications.
TechnicalInformationHandlerJavadoc - Class in weka.core: Generates Javadoc comments from the TechnicalInformationHandler's data.
TechnicalInformationHandlerJavadoc() - Constructor for class weka.core.TechnicalInformationHandlerJavadoc: default constructor
Tee - Class in weka.core: This class pipelines print/println's to several PrintStreams.
Tee() - Constructor for class weka.core.Tee: initializes the object, with a default printstream.
Tee(PrintStream) - Constructor for class weka.core.Tee: initializes the object with the given default printstream, e.g., System.out.
TemplateManager - Class in weka.gui.knowledgeflow: Manages all things template-related
TemplateManager() - Constructor for class weka.gui.knowledgeflow.TemplateManager
terminalNames - Static variable in interface weka.core.expressionlanguage.parser.sym
terminalNames - Static variable in interface weka.core.json.sym
terminate() - Method in class weka.gui.AbstractGUIApplication: Method to be called when GUI application is no longer needed, to free up resources so that they can be garbage collected.
terminate() - Method in class weka.gui.AbstractPerspective: Subclasses should override this to free any additional resources (e.g., JFrames and threads) when the perspective is no longer needed.
terminate() - Method in class weka.gui.experiment.AbstractSetupPanel: Terminates this panel.
terminate() - Method in class weka.gui.experiment.AlgorithmListPanel: Terminates this panel, which means, in the case of this panel, that it disposes of the property dialog and removes the relevant listeners from the GenericObjectEditor and the GOEPanel.
terminate() - Method in class weka.gui.experiment.Experimenter: Terminates this panel, which means, in the case of this panel, that it sets all references to associated JFrame objects to null.
terminate() - Method in class weka.gui.experiment.SetupModePanel: Terminates this panel, which means, in the case of this panel, that it sets all references to associated JFrame objects to null.
terminate() - Method in class weka.gui.experiment.SetupPanel: Terminates this panel, which means, in the case of this panel, that it sets all references to associated JFrame objects to null.
terminate() - Method in class weka.gui.experiment.SimpleSetupPanel: Terminates this panel, which means, in the case of this panel, that it sets all references to associated JFrame objects to null.
terminate() - Method in class weka.gui.explorer.Explorer: Terminates this panel, which means, in the case of this panel, that it terminates the associated LogPanel.
terminate() - Method in class weka.gui.LogPanel: Terminates this panel, which means, in the case of this panel, that it terminates the frame that it may have created.
terminate() - Method in class weka.gui.PerspectiveManager: Method to be called when GUI application is no longer needed, to free up resources so that they can be garbage collected.
terminate() - Method in class weka.gui.scripting.ScriptingPanel: Terminates this panel, i.e., terminates the output threads it started.
test(Attribute) - Method in class weka.core.Capabilities: Test the given attribute, whether it can be processed by the handler, given its capabilities.
test(Attribute, boolean) - Method in class weka.core.Capabilities: Test the given attribute, whether it can be processed by the handler, given its capabilities.
test(Instances) - Method in class weka.core.Capabilities: Tests the given data, whether it can be processed by the handler, given its capabilities.
test(Instances, int, int) - Method in class weka.core.Capabilities: Tests a certain range of attributes of the given data, whether it can be processed by the handler, given its capabilities.
test(String[]) - Static method in class weka.core.Instances: Method for testing this class.
Test - Class in weka.datagenerators: Class to represent a test.
Test(int, double, Instances) - Constructor for class weka.datagenerators.Test: Constructor
Test(int, double, Instances, boolean) - Constructor for class weka.datagenerators.Test: Constructor
TEST - Static variable in class weka.gui.beans.BatchClustererEvent
testAggregation() - Static method in class weka.estimators.KernelEstimator
testAggregation() - Static method in class weka.estimators.NormalEstimator
testCapabilities(Instances, int) - Method in class weka.estimators.Estimator: Test if the estimator can handle the data.
testCV(int, int) - Method in class weka.core.Instances: Creates the test set for one fold of a cross-validation on the dataset.
TestDistributions - Class in weka.core.pmml.jaxbbindings: Java class for TestDistributions element declaration.
TestDistributions() - Constructor for class weka.core.pmml.jaxbbindings.TestDistributions
Tester - Interface in weka.experiment: Interface for different kinds of Testers in the Experimenter.
TestInstances - Class in weka.core: Generates artificial datasets for testing.
TestInstances() - Constructor for class weka.core.TestInstances: the default constructor
TestOptions - Class in weka.core
TestOptions() - Constructor for class weka.core.TestOptions
testsetDirTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
TestSetEvent - Class in weka.gui.beans: Event encapsulating a test set
TestSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetEvent(Object, Instances, int, int) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetEvent(Object, Instances, int, int, int, int) - Constructor for class weka.gui.beans.TestSetEvent: Creates a new TestSetEvent
TestSetListener - Interface in weka.gui.beans: Interface to something that can accpet test set events
TestSetMaker - Class in weka.gui.beans: Bean that accepts data sets and produces test sets
TestSetMaker() - Constructor for class weka.gui.beans.TestSetMaker
TestSetMaker - Class in weka.knowledgeflow.steps: A step that makes an incoming dataSet or trainingSet into a testSet.
TestSetMaker() - Constructor for class weka.knowledgeflow.steps.TestSetMaker
TestSetMakerBeanInfo - Class in weka.gui.beans: Bean info class for the test set maker bean.
TestSetMakerBeanInfo() - Constructor for class weka.gui.beans.TestSetMakerBeanInfo
testsetPrefixTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
TestSetProducer - Interface in weka.gui.beans: Interface to something that can produce test sets
testsetSuffixTipText() - Method in class weka.experiment.ExplicitTestsetResultProducer: Returns the tip text for this property.
testWithFail(Attribute) - Method in class weka.core.Capabilities: tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
testWithFail(Attribute, boolean) - Method in class weka.core.Capabilities: tests the given attribute by calling the test(Attribute,boolean) method and throws an exception if the test fails.
testWithFail(Instances, int, int) - Method in class weka.core.Capabilities: tests the given data by calling the test(Instances,int,int) method and throws an exception if the test fails.
testWithFail(Instances) - Method in class weka.core.Capabilities: tests the given data by calling the test(Instances) method and throws an exception if the test fails.
TEXT - Static variable in class weka.experiment.DatabaseUtils: Type mapping for TEXT used for reading, e.g., text blobs.
TextCorpus - Class in weka.core.pmml.jaxbbindings: Java class for TextCorpus element declaration.
TextCorpus() - Constructor for class weka.core.pmml.jaxbbindings.TextCorpus
TextDictionary - Class in weka.core.pmml.jaxbbindings: Java class for TextDictionary element declaration.
TextDictionary() - Constructor for class weka.core.pmml.jaxbbindings.TextDictionary
TextDirectoryLoader - Class in weka.core.converters: Loads all text files in a directory and uses the subdirectory names as class labels.
TextDirectoryLoader() - Constructor for class weka.core.converters.TextDirectoryLoader: default constructor
TextDocument - Class in weka.core.pmml.jaxbbindings: Java class for TextDocument element declaration.
TextDocument() - Constructor for class weka.core.pmml.jaxbbindings.TextDocument
TextEvent - Class in weka.gui.beans: Event that encapsulates some textual information
TextEvent(Object, String, String) - Constructor for class weka.gui.beans.TextEvent: Creates a new TextEvent instance.
TextListener - Interface in weka.gui.beans: Interface to something that can process a TextEvent
TextModel - Class in weka.core.pmml.jaxbbindings: Java class for TextModel element declaration.
TextModel() - Constructor for class weka.core.pmml.jaxbbindings.TextModel
TextModelNormalization - Class in weka.core.pmml.jaxbbindings: Java class for TextModelNormalization element declaration.
TextModelNormalization() - Constructor for class weka.core.pmml.jaxbbindings.TextModelNormalization
TextModelSimiliarity - Class in weka.core.pmml.jaxbbindings: Java class for TextModelSimiliarity element declaration.
TextModelSimiliarity() - Constructor for class weka.core.pmml.jaxbbindings.TextModelSimiliarity
TextSaver - Class in weka.gui.beans: Simple component to save the text carried in text events out to a file
TextSaver() - Constructor for class weka.gui.beans.TextSaver: Default constructors a new TextSaver
TextSaver - Class in weka.knowledgeflow.steps: Step for saving textual data to a file.
TextSaver() - Constructor for class weka.knowledgeflow.steps.TextSaver
TextSaver.TextSaverDefaults - Class in weka.knowledgeflow.steps: Defaults for the step
TextSaverBeanInfo - Class in weka.gui.beans: Bean info class for the serialized model saver bean
TextSaverBeanInfo() - Constructor for class weka.gui.beans.TextSaverBeanInfo
TextSaverCustomizer - Class in weka.gui.beans: Customizer for the TextSaver component.
TextSaverCustomizer() - Constructor for class weka.gui.beans.TextSaverCustomizer: Default Constructor
TextSaverDefaults() - Constructor for class weka.knowledgeflow.steps.TextSaver.TextSaverDefaults: Constructor
TextViewer - Class in weka.gui.beans: Bean that collects and displays pieces of text
TextViewer() - Constructor for class weka.gui.beans.TextViewer
TextViewer - Class in weka.knowledgeflow.steps: A step for collecting and viewing textual data
TextViewer() - Constructor for class weka.knowledgeflow.steps.TextViewer
TextViewer.TextNotificationListener - Interface in weka.knowledgeflow.steps: Interface for listeners of textual results
TextViewerBeanInfo - Class in weka.gui.beans: Bean info class for the text viewer
TextViewerBeanInfo() - Constructor for class weka.gui.beans.TextViewerBeanInfo
TextViewerInteractiveView - Class in weka.gui.knowledgeflow.steps: Interactive viewer for the TextViewer step
TextViewerInteractiveView() - Constructor for class weka.gui.knowledgeflow.steps.TextViewerInteractiveView
TFTransformTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
TFTransformTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
theoryDL(int) - Method in class weka.classifiers.rules.RuleStats: The description length of the theory for a given rule.
ThreadSafe - Interface in weka.core: Interface to something that is thread safe
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.CostCurve: attribute name: Threshold
THRESHOLD_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: Threshold
ThresholdCurve - Class in weka.classifiers.evaluation: Generates points illustrating prediction tradeoffs that can be obtained by varying the threshold value between classes.
ThresholdCurve() - Constructor for class weka.classifiers.evaluation.ThresholdCurve
ThresholdDataEvent - Class in weka.gui.beans: Event encapsulating classifier performance data based on varying a threshold over the classifier's predicted probabilities
ThresholdDataEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.ThresholdDataEvent
ThresholdDataEvent(Object, PlotData2D, Attribute) - Constructor for class weka.gui.beans.ThresholdDataEvent
ThresholdDataListener - Interface in weka.gui.beans: Interface to something that can accept ThresholdDataEvents
ThresholdProducingMetric - Interface in weka.classifiers.evaluation: Some evaluation measures may optimize thresholds on the class probabilities.
thresholdTipText() - Method in class weka.attributeSelection.ClassifierAttributeEval: Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.GreedyStepwise: Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.Ranker: Returns the tip text for this property
thresholdTipText() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns the tip text for this property
thresholdTipText() - Method in class weka.filters.unsupervised.instance.RemoveMisclassified: Returns the tip text for this property
ThresholdVisualizePanel - Class in weka.gui.visualize: This panel is a VisualizePanel, with the added ablility to display the area under the ROC curve if an ROC curve is chosen.
ThresholdVisualizePanel() - Constructor for class weka.gui.visualize.ThresholdVisualizePanel: default constructor
throughputFinished(Data...) - Method in interface weka.knowledgeflow.StepManager: Signal that throughput measurement has finished.
throughputFinished(Data...) - Method in class weka.knowledgeflow.StepManagerImpl: Clients can use this to indicate that throughput measuring is finished (i.e.
throughputUpdateEnd() - Method in interface weka.knowledgeflow.StepManager: End a throughput measurement.
throughputUpdateEnd() - Method in class weka.knowledgeflow.StepManagerImpl: Clients can use this to record a stop point for streaming throughput measuring
throughputUpdateStart() - Method in interface weka.knowledgeflow.StepManager: Start a throughput measurement.
throughputUpdateStart() - Method in class weka.knowledgeflow.StepManagerImpl: Clients can use this to record a start point for streaming throughput measuring
TIE_STRING - Variable in class weka.experiment.ResultMatrix: tie string.
Time - Class in weka.core.pmml.jaxbbindings: Java class for Time element declaration.
Time() - Constructor for class weka.core.pmml.jaxbbindings.Time
TIME - Static variable in class weka.experiment.DatabaseUtils: Type mapping for TIME used for reading TIME columns.
TimeAnchor - Class in weka.core.pmml.jaxbbindings: Java class for TimeAnchor element declaration.
TimeAnchor() - Constructor for class weka.core.pmml.jaxbbindings.TimeAnchor
TIMEANCHOR2 - Enum in weka.core.pmml.jaxbbindings: Java class for TIME-ANCHOR.
TimeCycle - Class in weka.core.pmml.jaxbbindings: Java class for TimeCycle element declaration.
TimeCycle() - Constructor for class weka.core.pmml.jaxbbindings.TimeCycle
TimeException - Class in weka.core.pmml.jaxbbindings: Java class for TimeException element declaration.
TimeException() - Constructor for class weka.core.pmml.jaxbbindings.TimeException
TIMEEXCEPTIONTYPE - Enum in weka.core.pmml.jaxbbindings: Java class for TIME-EXCEPTION-TYPE.
times(Node, Node) - Static method in class weka.core.expressionlanguage.common.Operators: '*' times operator
TIMES - Static variable in interface weka.core.expressionlanguage.parser.sym
times(double) - Method in class weka.core.matrix.DoubleVector: Multiplies a scalar
times(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Multiplies another DoubleVector element by element
times(double) - Method in class weka.core.matrix.Matrix: Multiply a matrix by a scalar, C = s*A
times(Matrix) - Method in class weka.core.matrix.Matrix: Linear algebraic matrix multiplication, A * B
timesEquals(double) - Method in class weka.core.matrix.DoubleVector: Multiply a vector by a scalar in place, u = s * u
timesEquals(DoubleVector) - Method in class weka.core.matrix.DoubleVector: Multiplies another DoubleVector element by element in place
timesEquals(double) - Method in class weka.core.matrix.Matrix: Multiply a matrix by a scalar in place, A = s*A
TimeSeries - Class in weka.core.pmml.jaxbbindings: Java class for TimeSeries element declaration.
TimeSeries() - Constructor for class weka.core.pmml.jaxbbindings.TimeSeries
TIMESERIESALGORITHM - Enum in weka.core.pmml.jaxbbindings: Java class for TIMESERIES-ALGORITHM.
TimeSeriesDelta - Class in weka.filters.unsupervised.attribute: An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the difference between the current value and the equivalent attribute attribute value of some previous (or future) instance.
TimeSeriesDelta() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesDelta
TimeSeriesModel - Class in weka.core.pmml.jaxbbindings: Java class for TimeSeriesModel element declaration.
TimeSeriesModel() - Constructor for class weka.core.pmml.jaxbbindings.TimeSeriesModel
TimeSeriesTranslate - Class in weka.filters.unsupervised.attribute: An instance filter that assumes instances form time-series data and replaces attribute values in the current instance with the equivalent attribute values of some previous (or future) instance.
TimeSeriesTranslate() - Constructor for class weka.filters.unsupervised.attribute.TimeSeriesTranslate
TIMESERIESUSAGE - Enum in weka.core.pmml.jaxbbindings: Java class for TIMESERIES-USAGE.
Timestamp() - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the current date and time and the default format.
Timestamp(String) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the current date and time and the specified format.
Timestamp(Date) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the given date and the default format.
Timestamp(Date, String) - Constructor for class weka.core.Debug.Timestamp: creates a timestamp with the given date and format.
Timestamp - Class in weka.core.pmml.jaxbbindings: Java class for Timestamp element declaration.
Timestamp() - Constructor for class weka.core.pmml.jaxbbindings.Timestamp
TIMESTAMP - Static variable in class weka.experiment.DatabaseUtils: Type mapping for TIMESTAMP used for reading java.sql.Timestamp columns
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.CrossValidationResultProducer: The name of the result field containing the timestamp
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.ExplicitTestsetResultProducer: The name of the result field containing the timestamp.
TIMESTAMP_FIELD_NAME - Static variable in class weka.experiment.RandomSplitResultProducer: The name of the result field containing the timestamp
TimeValue - Class in weka.core.pmml.jaxbbindings: Java class for TimeValue element declaration.
TimeValue() - Constructor for class weka.core.pmml.jaxbbindings.TimeValue
titleUpdated(TitleUpdatedEvent) - Method in interface weka.gui.scripting.event.TitleUpdatedListener: Gets called when the title of the frame/dialog needs updating.
titleUpdated(TitleUpdatedEvent) - Method in class weka.gui.scripting.ScriptingPanel: Gets called when the title of the frame/dialog needs updating.
TitleUpdatedEvent - Class in weka.gui.scripting.event: Event that gets send in case a scripting panel updates the title.
TitleUpdatedEvent(ScriptingPanel) - Constructor for class weka.gui.scripting.event.TitleUpdatedEvent: Initializes the event.
TitleUpdatedListener - Interface in weka.gui.scripting.event: Interface for frames/dialogs that listen to changes of the title.
TO_BE_RUN - Static variable in class weka.experiment.TaskStatusInfo
toArray() - Method in class weka.core.Trie: Returns an array containing all of the elements in this collection.
toArray(T[]) - Method in class weka.core.Trie: Returns an array containing all of the elements in this collection; the runtime type of the returned array is that of the specified array.
toArray() - Method in class weka.core.xml.XMLOptions: returns the current DOM document as string array.
toArray() - Method in class weka.gui.CheckBoxList.CheckBoxListModel: Returns an array containing all of the elements in this list in the correct order.
toBibTex() - Method in class weka.core.TechnicalInformation: Returns a BibTex string representing this technical information.
toClassDetailsString() - Method in class weka.classifiers.evaluation.Evaluation: Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.evaluation.Evaluation: Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString() - Method in class weka.classifiers.Evaluation: Generates a breakdown of the accuracy for each class (with default title), incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toClassDetailsString(String) - Method in class weka.classifiers.Evaluation: Generates a breakdown of the accuracy for each class, incorporating various information-retrieval statistics, such as true/false positive rate, precision/recall/F-Measure.
toCommandLine(Object) - Static method in class weka.core.Utils: Generates a commandline of the given object.
toCommandLine() - Method in class weka.core.xml.XMLOptions: returns the given DOM document as command line.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.evaluation.Evaluation: Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toCumulativeMarginDistributionString() - Method in class weka.classifiers.Evaluation: Output the cumulative margin distribution as a string suitable for input for gnuplot or similar package.
toDisplay() - Method in interface weka.core.CustomDisplayStringProvider: Returns the custom display string.
toDisplay() - Method in class weka.core.Range: Returns the custom display string.
toDisplay() - Method in class weka.core.SingleIndex: Returns the custom display string.
toDoubleArray() - Method in class weka.core.BinarySparseInstance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.DenseInstance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in interface weka.core.Instance: Returns the values of each attribute as an array of doubles.
toDoubleArray() - Method in class weka.core.SparseInstance: Returns the values of each attribute as an array of doubles.
toggleEvalMetrics(List<String>) - Method in class weka.classifiers.evaluation.Evaluation: Toggle the output of the metrics specified in the supplied list.
toggleEvalMetrics(List<String>) - Method in class weka.classifiers.Evaluation: Toggle the output of the metrics specified in the supplied list.
toggleLoadStatus(List<String>) - Static method in class weka.core.WekaPackageManager: Toggle the load status of the supplied list of package names
toHeader(JSONNode) - Static method in class weka.core.json.JSONInstances: Turns a JSON object, if possible, into an Instances object (only header).
toInstances(JSONNode) - Static method in class weka.core.json.JSONInstances: Turns a JSON object, if possible, into an Instances object.
toJSON(Instances) - Static method in class weka.core.json.JSONInstances: Turns the Instances object into a JSON object.
toJSON() - Method in class weka.knowledgeflow.Flow: Return the JSON encoded version of this Flow
toJTree(DefaultMutableTreeNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
toJTree(DefaultMutableTreeNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
toJTree(DefaultMutableTreeNode) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Get a DefaultMutableTreeNode for this node
tokenize(String) - Method in class weka.core.tokenizers.AlphabeticTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.CharacterNGramTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.NGramTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.core.tokenizers.Tokenizer: Sets the string to tokenize.
tokenize(Tokenizer, String[]) - Static method in class weka.core.tokenizers.Tokenizer: initializes the given tokenizer with the given options and runs the tokenizer over all the remaining strings in the options array.
tokenize(String) - Method in class weka.core.tokenizers.WordTokenizer: Sets the string to tokenize.
tokenize(String) - Method in class weka.gui.HierarchyPropertyParser: Tokenize the given string based on the seperator and put the tokens into an array of strings
Tokenizer - Class in weka.core.tokenizers: A superclass for all tokenizer algorithms.
Tokenizer() - Constructor for class weka.core.tokenizers.Tokenizer
tokenizerTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property.
tokenizerTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property.
tokenizerTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
tokenizerTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
toleranceParameterTipText() - Method in class weka.classifiers.functions.SMO: Returns the tip text for this property
toleranceTipText() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns the tip text for this property
toMatlab() - Method in class weka.classifiers.CostMatrix: converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatlab() - Method in class weka.core.matrix.Matrix: converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatlab() - Method in class weka.core.Matrix: Deprecated.

converts the Matrix into a single line Matlab string: matrix is enclosed by parentheses, rows are separated by semicolon and single cells by blanks, e.g., [1 2; 3 4].
toMatrixString() - Method in class weka.classifiers.evaluation.Evaluation: Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.evaluation.Evaluation: Outputs the performance statistics as a classification confusion matrix.
toMatrixString() - Method in class weka.classifiers.Evaluation: Calls toMatrixString() with a default title.
toMatrixString(String) - Method in class weka.classifiers.Evaluation: Outputs the performance statistics as a classification confusion matrix.
toMegaByte(long) - Static method in class weka.core.Memory: returns the amount of bytes as MB
toOptionList(Tag[]) - Static method in class weka.core.Tag: returns a list that can be used in the listOption methods to list all the available ID strings, e.g.: <0|1|2> or <what|ever>
toOptionSynopsis(Tag[]) - Static method in class weka.core.Tag: returns a string that can be used in the listOption methods to list all the available options, i.e., "\t\tID = Text\n" for each option
toOutput() - Method in class weka.gui.visualize.JComponentWriter: saves the current component to the currently set file.
toOutput(JComponentWriter, JComponent, File) - Static method in class weka.gui.visualize.JComponentWriter: outputs the given component with the given writer in the specified file
toOutput(JComponentWriter, JComponent, File, int, int) - Static method in class weka.gui.visualize.JComponentWriter: outputs the given component with the given writer in the specified file.
TopDownConstructor - Class in weka.core.neighboursearch.balltrees: The class implementing the TopDown construction method of ball trees.
TopDownConstructor() - Constructor for class weka.core.neighboursearch.balltrees.TopDownConstructor: Creates a new instance of TopDownConstructor.
toPMML(Instances) - Method in class weka.classifiers.functions.Logistic: Produce a PMML representation of this logistic model
toPMML(Instances, Instances, double[][], int) - Static method in class weka.classifiers.pmml.producer.LogisticProducerHelper: Produce the PMML for a Logistic classifier
toPMML(Instances) - Method in interface weka.core.pmml.PMMLProducer: Produce a PMML representation
topOfTree() - Method in class weka.classifiers.trees.m5.Rule: Returns the top of the tree.
toPrologString() - Method in class weka.datagenerators.Test: Returns the test represented by a string in Prolog notation.
toResultsString() - Method in class weka.attributeSelection.AttributeSelection: get a description of the attribute selection
toSource(String) - Method in class weka.classifiers.meta.AdaBoostM1: Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.meta.LogitBoost: Returns the boosted model as Java source code.
toSource(String) - Method in class weka.classifiers.rules.OneR: Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.rules.ZeroR: Returns a string that describes the classifier as source.
toSource(String) - Method in interface weka.classifiers.Sourcable: Returns a string that describes the classifier as source.
toSource(String) - Method in class weka.classifiers.trees.DecisionStump: Returns the decision tree as Java source code.
toSource(String) - Method in class weka.classifiers.trees.j48.ClassifierTree: Returns source code for the tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.J48: Returns tree as an if-then statement.
toSource(String) - Method in class weka.classifiers.trees.REPTree: Returns the tree as if-then statements.
toSource(String) - Method in class weka.core.Capabilities: turns the capabilities object into source code.
toSource(String, int) - Method in class weka.core.Capabilities: turns the capabilities object into source code.
toSource(String, Instances) - Method in class weka.filters.AllFilter: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in interface weka.filters.Sourcable: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Center: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Normalize: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.ReplaceMissingValues: Returns a string that describes the filter as source.
toSource(String, Instances) - Method in class weka.filters.unsupervised.attribute.Standardize: Returns a string that describes the filter as source.
toString() - Method in class weka.associations.Apriori: Outputs the size of all the generated sets of itemsets and the rules.
toString(Instances) - Method in class weka.associations.AprioriItemSet: Returns the contents of an item set as a string.
toString() - Method in class weka.associations.AssociatorEvaluation: returns the current result
toString() - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toString() - Method in class weka.associations.DefaultAssociationRule: Get a textual description of this rule.
toString() - Method in class weka.associations.FilteredAssociator: Output a representation of this associator
toString() - Method in class weka.associations.FPGrowth: Output the association rules.
toString() - Method in class weka.associations.Item: A string representation of this item.
toString(boolean) - Method in class weka.associations.Item: A string representation of this item, (i.e.
toString(Instances) - Method in class weka.associations.ItemSet: Returns the contents of an item set as a string.
toString(Instances, char, char) - Method in class weka.associations.ItemSet: Returns the contents of an item set as a delimited string.
toString(boolean) - Method in class weka.associations.NominalItem: A string representation of this item, (i.e.
toString(boolean) - Method in class weka.associations.NumericItem: A string representation of this item, (i.e.
toString() - Method in class weka.attributeSelection.BestFirst.Link2
toString() - Method in class weka.attributeSelection.BestFirst: returns a description of the search as a String
toString() - Method in class weka.attributeSelection.CfsSubsetEval: returns a string describing CFS
toString() - Method in class weka.attributeSelection.ClassifierAttributeEval: Return a description of the evaluator.
toString() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns a string describing classifierSubsetEval
toString() - Method in class weka.attributeSelection.CorrelationAttributeEval: Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.GainRatioAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.GreedyStepwise: returns a description of the search.
toString() - Method in class weka.attributeSelection.InfoGainAttributeEval: Describe the attribute evaluator
toString() - Method in class weka.attributeSelection.OneRAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.PrincipalComponents: Returns a description of this attribute transformer
toString() - Method in class weka.attributeSelection.Ranker: returns a description of the search as a String
toString() - Method in class weka.attributeSelection.ReliefFAttributeEval: Return a description of the ReliefF attribute evaluator.
toString() - Method in class weka.attributeSelection.SymmetricalUncertAttributeEval: Return a description of the evaluator
toString() - Method in class weka.attributeSelection.WrapperSubsetEval: Returns a string describing the wrapper
toString() - Method in class weka.classifiers.bayes.BayesNet: Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayes: Returns a description of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomial: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns a textual description of this classifier.
toString() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Returns a string representation of the classifier.
toString() - Method in class weka.classifiers.bayes.net.BayesNetGenerator: Returns either the net (if BIF format) or the generated instances
toString() - Method in class weka.classifiers.bayes.net.estimate.DiscreteEstimatorBayes: Display a representation of this estimator
toString() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeNode
toString() - Method in class weka.classifiers.bayes.net.MarginCalculator
toString() - Method in class weka.classifiers.bayes.net.search.SearchAlgorithm: a string representation of the algorithm
toString() - Method in class weka.classifiers.BVDecompose: Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.BVDecomposeSegCVSub: Returns description of the bias-variance decomposition results.
toString() - Method in class weka.classifiers.CostMatrix: Converts a matrix to a string.
toString() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Calls toString() with a default title.
toString(String) - Method in class weka.classifiers.evaluation.ConfusionMatrix: Outputs the performance statistics as a classification confusion matrix.
toString() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets a human readable representation of this prediction.
toString() - Method in class weka.classifiers.evaluation.output.prediction.InMemory.PredictionContainer: Returns a string representation of the container.
toString() - Method in class weka.classifiers.evaluation.TwoClassStats: Returns a string containing the various performance measures for the current object
toString() - Method in class weka.classifiers.functions.GaussianProcesses: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.LinearRegression: Outputs the linear regression model as a string.
toString() - Method in class weka.classifiers.functions.Logistic: Gets a string describing the classifier.
toString() - Method in class weka.classifiers.functions.MultilayerPerceptron
toString() - Method in class weka.classifiers.functions.SGD: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SGDText
toString() - Method in class weka.classifiers.functions.SimpleLinearRegression: Returns a description of this classifier as a string
toString() - Method in class weka.classifiers.functions.SimpleLogistic: Returns a description of the logistic model (attributes/coefficients).
toString() - Method in class weka.classifiers.functions.SMO.BinarySMO: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMO: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.SMOreg: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns the current result
toString() - Method in class weka.classifiers.functions.supportVector.NormalizedPolyKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.PolyKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.PrecomputedKernelMatrixKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.Puk: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.RBFKernel: returns a string representation for the Kernel
toString() - Method in class weka.classifiers.functions.supportVector.RegOptimizer: Prints out the classifier.
toString() - Method in class weka.classifiers.functions.VotedPerceptron: Returns textual description of classifier.
toString() - Method in class weka.classifiers.lazy.IBk: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.KStar: Returns a description of this classifier.
toString() - Method in class weka.classifiers.lazy.LWL: Returns a description of this classifier.
toString() - Method in class weka.classifiers.meta.AdaBoostM1: Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.AdditiveRegression: Returns textual description of the classifier.
toString() - Method in class weka.classifiers.meta.AttributeSelectedClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Bagging: Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.ClassificationViaRegression: Prints the classifiers.
toString() - Method in class weka.classifiers.meta.CostSensitiveClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.CVParameterSelection: Returns description of the cross-validated classifier.
toString() - Method in class weka.classifiers.meta.FilteredClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns a string describing the classifier.
toString() - Method in class weka.classifiers.meta.LogitBoost: Returns description of the boosted classifier.
toString() - Method in class weka.classifiers.meta.MultiClassClassifier: Prints the classifiers.
toString() - Method in class weka.classifiers.meta.MultiScheme: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.RandomCommittee: Returns description of the committee.
toString() - Method in class weka.classifiers.meta.RandomizableFilteredClassifier: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.RandomSubSpace: Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns a description of the classifier.
toString() - Method in class weka.classifiers.meta.Stacking: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.Vote: Output a representation of this classifier
toString() - Method in class weka.classifiers.meta.WeightedInstancesHandlerWrapper: Returns a string description of the model.
toString() - Method in class weka.classifiers.misc.InputMappedClassifier
toString() - Method in class weka.classifiers.misc.SerializedClassifier: Returns a string representation of the classifier
toString() - Method in class weka.classifiers.pmml.consumer.GeneralRegression: Return a textual description of this general regression.
toString() - Method in class weka.classifiers.pmml.consumer.NeuralNetwork
toString() - Method in class weka.classifiers.pmml.consumer.Regression: Return a textual description of this Regression model.
toString() - Method in class weka.classifiers.pmml.consumer.RuleSetModel: Return a textual description of this model.
toString() - Method in class weka.classifiers.pmml.consumer.SupportVectorMachineModel: Get a textual description of this SupportVectorMachineModel
toString() - Method in class weka.classifiers.pmml.consumer.TreeModel
toString() - Method in class weka.classifiers.rules.DecisionTable: Returns a description of the classifier.
toString(Instances, int) - Method in class weka.classifiers.rules.DecisionTableHashKey: Convert a hash entry to a string
toString() - Method in class weka.classifiers.rules.JRip.Antd
toString() - Method in class weka.classifiers.rules.JRip.NominalAntd: Prints this antecedent
toString() - Method in class weka.classifiers.rules.JRip.NumericAntd: Prints this antecedent
toString(Attribute) - Method in class weka.classifiers.rules.JRip.RipperRule: Prints this rule
toString() - Method in class weka.classifiers.rules.JRip: Prints the all the rules of the rule learner.
toString() - Method in class weka.classifiers.rules.OneR: Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.part.ClassifierDecList: Prints rules.
toString() - Method in class weka.classifiers.rules.part.MakeDecList: Outputs the classifier into a string.
toString() - Method in class weka.classifiers.rules.PART: Returns a description of the classifier
toString() - Method in class weka.classifiers.rules.ZeroR: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.DecisionStump: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.HoeffdingTree: Return a textual description of the mode
toString(boolean) - Method in class weka.classifiers.trees.ht.HNode: Print a textual description of the tree
toString() - Method in class weka.classifiers.trees.j48.ClassifierTree: Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeClassifierTree: Prints tree structure.
toString() - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Return a textual description of the node
toString() - Method in class weka.classifiers.trees.J48: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.lmt.LMTNode: Returns a description of the logistic model tree (tree structure and logistic models)
toString() - Method in class weka.classifiers.trees.lmt.LogisticBase: Returns a description of the logistic model (i.e., attributes and coefficients).
toString() - Method in class weka.classifiers.trees.LMT: Returns a description of the classifier.
toString() - Method in class weka.classifiers.trees.m5.Impurity: Converts an Impurity object to a string
toString() - Method in class weka.classifiers.trees.m5.M5Base: Returns a description of the classifier
toString() - Method in class weka.classifiers.trees.m5.PreConstructedLinearModel: Returns a textual description of this linear model
toString() - Method in class weka.classifiers.trees.m5.Rule: Return a description of the m5 tree or rule
toString() - Method in class weka.classifiers.trees.m5.RuleNode: print the linear model at this node
toString() - Method in class weka.classifiers.trees.m5.Values: Converts the stats to a string
toString(Instances) - Method in class weka.classifiers.trees.m5.YongSplitInfo: Converts the spliting information to string
toString() - Method in class weka.classifiers.trees.RandomForest: Returns description of the bagged classifier.
toString() - Method in class weka.classifiers.trees.RandomTree: Outputs the decision tree.
toString() - Method in class weka.classifiers.trees.REPTree: Outputs the decision tree.
toString(boolean) - Method in class weka.clusterers.Canopy: Return a textual description of this clusterer
toString() - Method in class weka.clusterers.Canopy
toString() - Method in class weka.clusterers.Cobweb: Returns a description of the clusterer as a string.
toString() - Method in class weka.clusterers.EM: Outputs the generated clusters into a string.
toString() - Method in class weka.clusterers.FarthestFirst: return a string describing this clusterer
toString() - Method in class weka.clusterers.FilteredClusterer: Output a representation of this clusterer.
toString() - Method in class weka.clusterers.HierarchicalClusterer
toString() - Method in class weka.clusterers.MakeDensityBasedClusterer: Returns a description of the clusterer.
toString() - Method in class weka.clusterers.SimpleKMeans: return a string describing this clusterer.
toString() - Method in class weka.core.AbstractInstance: Returns the description of one instance.
toString(int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(int, int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(Attribute) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString(Attribute, int) - Method in class weka.core.AbstractInstance: Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.AlgVector: Converts a vector to a string
toString() - Method in class weka.core.Attribute: Returns a description of this attribute in ARFF format.
toString() - Method in class weka.core.AttributeLocator: returns a string representation of this object
toString() - Method in class weka.core.AttributeStats: Returns a human readable representation of this AttributeStats instance.
toString() - Method in class weka.core.BinarySparseInstance: Returns the description of one instance in sparse format.
toString() - Method in enum weka.core.Capabilities.Capability: returns the display string of the capability
toString() - Method in class weka.core.Capabilities: returns a string representation of the capabilities
toString() - Method in class weka.core.Debug.Clock: returns the elapsed time, getStop() - getStart(), as string
toString() - Method in class weka.core.Debug.Log: returns a string representation of the logger
toString() - Method in class weka.core.Debug.Random: returns a string representation of this number generator
toString() - Method in class weka.core.Debug.SimpleLog: returns a string representation of the logger
toString() - Method in class weka.core.Debug.Timestamp: returns the timestamp as string in the specified format
toString(int, int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(Attribute, int) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString(Attribute) - Method in interface weka.core.Instance: Returns the description of one value of the instance as a string.
toString() - Method in class weka.core.Instances: Returns the dataset as a string in ARFF format.
toString(StringBuffer) - Method in class weka.core.json.JSONNode: Dumps the node structure into JSON format.
toString() - Method in class weka.core.json.JSONNode: Returns a string representation of the node.
toString() - Method in class weka.core.matrix.DoubleVector: Convert the DoubleVecor to a string
toString(int, boolean) - Method in class weka.core.matrix.DoubleVector: Convert the DoubleVecor to a string
toString() - Method in class weka.core.matrix.IntVector: Converts the IntVecor to a string
toString(int, boolean) - Method in class weka.core.matrix.IntVector: Convert the IntVecor to a string
toString() - Method in class weka.core.matrix.LinearRegression: returns the coefficients in a string representation
toString() - Method in class weka.core.matrix.Matrix: Converts a matrix to a string.
toString() - Method in class weka.core.Matrix: Deprecated.

Converts a matrix to a string
toString() - Method in class weka.core.NormalizableDistance: Returns an empty string.
toString() - Method in class weka.core.packageManagement.DefaultPackage
toString() - Method in class weka.core.packageManagement.Dependency
toString() - Method in class weka.core.packageManagement.VersionPackageConstraint
toString() - Method in enum weka.core.packageManagement.VersionPackageConstraint.VersionComparison
toString() - Method in class weka.core.packageManagement.VersionRangePackageConstraint
toString() - Method in enum weka.core.pmml.Array.ArrayType
toString() - Method in class weka.core.pmml.Array
toString() - Method in class weka.core.pmml.BuiltInArithmetic
toString(String) - Method in class weka.core.pmml.BuiltInArithmetic
toString() - Method in class weka.core.pmml.BuiltInMath
toString() - Method in class weka.core.pmml.BuiltInString
toString(String) - Method in class weka.core.pmml.Constant
toString() - Method in class weka.core.pmml.DefineFunction
toString(String) - Method in class weka.core.pmml.DefineFunction
toString() - Method in class weka.core.pmml.DerivedFieldMetaInfo
toString(String) - Method in class weka.core.pmml.Discretize
toString() - Method in class weka.core.pmml.Expression
toString(String) - Method in class weka.core.pmml.Expression
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure
toString(double, double) - Method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure
toString() - Method in class weka.core.pmml.FieldMetaInfo.Interval
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Optype
toString() - Method in enum weka.core.pmml.FieldMetaInfo.Value.Property
toString() - Method in class weka.core.pmml.FieldMetaInfo.Value
toString(String) - Method in class weka.core.pmml.FieldRef
toString() - Method in class weka.core.pmml.Function
toString(String) - Method in class weka.core.pmml.Function
toString() - Method in class weka.core.pmml.MiningFieldMetaInfo: Return a textual representation of this MiningField.
toString() - Method in class weka.core.pmml.MiningSchema: Get a textual description of the mining schema.
toString(String) - Method in class weka.core.pmml.NormContinuous
toString(String) - Method in class weka.core.pmml.NormDiscrete
toString() - Method in class weka.core.pmml.SparseArray
toString() - Method in class weka.core.PropertyPath.Path: returns the structure again as a dot-path
toString() - Method in class weka.core.PropertyPath.PathElement: returns the element once again as string
toString() - Method in class weka.core.Queue: Produces textual description of queue.
toString() - Method in class weka.core.Range: Constructs a representation of the current range.
toString() - Method in class weka.core.SelectedTag: returns the selected tag in string representation
toString() - Method in class weka.core.Settings.SettingKey: Return the description (display name) of this setting
toString() - Method in class weka.core.SingleIndex: Constructs a representation of the current range.
toString() - Method in class weka.core.stemmers.LovinsStemmer: returns a string representation of the stemmer
toString() - Method in class weka.core.stemmers.NullStemmer: returns a string representation of the stemmer
toString() - Method in class weka.core.stemmers.SnowballStemmer: returns a string representation of the stemmer.
toString() - Method in class weka.core.Stopwords: returns the current stopwords in a string
toString() - Method in class weka.core.SystemInfo: returns a string representation of all the system properties
toString() - Method in class weka.core.Tag: returns the IDStr
toString() - Method in enum weka.core.TechnicalInformation.Field: returns the display string of the Type
toString() - Method in class weka.core.TechnicalInformation: Returns a plain-text string representing this technical information.
toString() - Method in enum weka.core.TechnicalInformation.Type: returns the display string of the Type
toString() - Method in class weka.core.Tee: returns only the classname and the number of streams.
toString() - Method in class weka.core.TestInstances: returns a string representation of the object
toString() - Method in class weka.core.Trie: returns the trie in string representation
toString() - Method in class weka.core.Trie.TrieNode: returns the node in a string representation
toString() - Method in class weka.core.Version: returns the current version as string
toString() - Method in class weka.core.WekaPackageLibIsolatingClassLoader: String representation of this classloader
toString() - Method in class weka.core.xml.MethodHandler: returns the internal Hashtable (propety/class - method relationship) in a string representation
toString() - Method in class weka.core.xml.XMLDocument: returns the current DOM document as XML-string.
toString() - Method in class weka.core.xml.XMLOptions: returns the object in a string representation (as indented XML output).
toString() - Method in class weka.core.xml.XMLSerializationMethodHandler: returns the read and write method handlers as string
toString() - Method in class weka.datagenerators.ClusterDefinition: returns a string representation of the cluster
toString() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Make a string from the cluster features.
toString() - Method in class weka.datagenerators.Test: Returns the test represented by a string.
toString() - Method in class weka.estimators.DDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DiscreteEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DKConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.DNConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KernelEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.KKConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.MahalanobisEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.MultivariateGaussianEstimator: Returns string summarizing the estimator.
toString() - Method in class weka.estimators.NDConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.NNConditionalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.NormalEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.PoissonEstimator: Display a representation of this estimator
toString() - Method in class weka.estimators.UnivariateEqualFrequencyHistogramEstimator: Returns textual description of this estimator.
toString() - Method in class weka.estimators.UnivariateKernelEstimator: Returns textual description of this estimator.
toString() - Method in class weka.estimators.UnivariateMixtureEstimator.MM: Returns string describing the estimator.
toString() - Method in class weka.estimators.UnivariateMixtureEstimator: Returns textual description of this estimator.
toString() - Method in class weka.estimators.UnivariateNormalEstimator: Returns textual description of this estimator.
toString() - Method in class weka.experiment.AveragingResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.ClassifierSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CostSensitiveClassifierSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.CrossValidationResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.CrossValidationSplitResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DatabaseResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.DensityBasedClustererSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.Experiment: Gets a string representation of the experiment configuration.
toString() - Method in class weka.experiment.ExplicitTestsetResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.LearningRateResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.PairedStats: Returns statistics on the paired comparison.
toString() - Method in class weka.experiment.PropertyNode: Returns a string description of this property.
toString() - Method in class weka.experiment.RandomSplitResultProducer: Gets a text descrption of the result producer.
toString() - Method in class weka.experiment.RegressionSplitEvaluator: Returns a text description of the split evaluator.
toString() - Method in class weka.experiment.RemoteExperiment: Overides toString in Experiment
toString() - Method in class weka.experiment.ResultMatrix: returns the matrix as a string.
toString() - Method in class weka.experiment.Stats: Returns a string summarising the stats so far.
toString() - Method in class weka.filters.Filter: Returns a description of the filter, by default only the classname.
toString() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec: Return a nicely formatted string for display
toString() - Method in class weka.gui.AbstractPerspective: Returns the perspective's title
toString() - Method in class weka.gui.arffviewer.ArffViewer: returns only the classname
toString() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: returns only the classname
toString() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Return a textual description of this match rule
toString() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Return a textual description of this rule
toString() - Method in class weka.gui.experiment.AbstractSetupPanel: Just returns the name of the panel.
toString() - Method in class weka.gui.GenericObjectEditor.GOETreeNode: returns a string representation of this treenode.
toString() - Method in class weka.gui.graphvisualizer.GraphEdge
toString() - Method in enum weka.gui.knowledgeflow.MainKFPerspectiveToolBar.Widgets
toString() - Method in class weka.gui.knowledgeflow.StepTreeLeafDetails: Returns the leaf label
toString() - Method in class weka.gui.scripting.Script: Returns the content as string.
toString() - Method in class weka.gui.SortedTableModel.SortContainer: Returns a string representation of the sort container.
toString() - Method in class weka.gui.sql.event.ConnectionEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.HistoryChangedEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.QueryExecuteEvent: returns the event in a string representation
toString() - Method in class weka.gui.sql.event.ResultChangedEvent: returns the event in a string representation
toString() - Method in enum weka.knowledgeflow.LoggingLevel: String representation
toString() - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
toString() - Method in enum weka.knowledgeflow.steps.FlowByExpression.ExpressionClause.ExpressionType
toString() - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
toString() - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Prints the rule in human readable format
toString() - Method in enum weka.Run.SchemeType
toStringDisplay(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
toStringDisplay(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
toStringDisplay(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Get the display representation of this node
toStringHeader() - Method in class weka.experiment.ResultMatrix: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixCSV: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixHTML: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixLatex: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixPlainText: returns the header of the matrix as a string.
toStringHeader() - Method in class weka.experiment.ResultMatrixSignificance: returns the header of the matrix as a string.
toStringInternal() - Method in class weka.filters.unsupervised.attribute.AddUserFields.AttributeSpec
toStringInternal() - Method in class weka.gui.beans.SubstringLabelerRules.SubstringLabelerMatchRule: Get the internal representation of this rule
toStringInternal() - Method in class weka.gui.beans.SubstringReplacerRules.SubstringReplacerMatchRule: Return the internally encoded representation of this rule
toStringInternal(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.BracketNode
toStringInternal(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionClause
toStringInternal(StringBuffer) - Method in class weka.knowledgeflow.steps.FlowByExpression.ExpressionNode: Get the internal representation of this node
toStringInternal() - Method in class weka.knowledgeflow.steps.Sorter.SortRule: Gets the rule in internal format
toStringKey() - Method in class weka.experiment.ResultMatrix: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixCSV: returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixGnuPlot: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixHTML: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixLatex: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixPlainText: returns returns a key for all the col names, for better readability if the names got cut off.
toStringKey() - Method in class weka.experiment.ResultMatrixSignificance: returns returns a key for all the col names, for better readability if the names got cut off.
toStringMatrix() - Method in class weka.experiment.ResultMatrix: returns the matrix as a string.
toStringMatrix() - Method in class weka.experiment.ResultMatrixCSV: returns the matrix in CSV format.
toStringMatrix() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the matrix in CSV format.
toStringMatrix() - Method in class weka.experiment.ResultMatrixHTML: returns the matrix in an HTML table.
toStringMatrix() - Method in class weka.experiment.ResultMatrixLatex: returns the matrix as latex table.
toStringMatrix() - Method in class weka.experiment.ResultMatrixPlainText: returns the matrix as plain text.
toStringMatrix() - Method in class weka.experiment.ResultMatrixSignificance: returns the matrix as plain text.
toStringMaxDecimalDigits(int) - Method in class weka.core.AbstractInstance: Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.
toStringMaxDecimalDigits(int) - Method in interface weka.core.Instance: Returns the description of one instance with any numeric values printed at the supplied maximum number of decimal places.
toStringMetric(int, int, int, int) - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toStringNoWeight() - Method in class weka.core.DenseInstance: Returns the description of one instance (without weight appended).
toStringNoWeight(int) - Method in class weka.core.DenseInstance: Returns the description of one instance (without weight appended).
toStringNoWeight(int) - Method in interface weka.core.Instance: Returns the description of one instance (without weight appended).
toStringNoWeight() - Method in interface weka.core.Instance: Returns the description of one instance (without weight appended).
toStringNoWeight() - Method in class weka.core.SparseInstance: Returns the description of one instance in sparse format.
toStringNoWeight(int) - Method in class weka.core.SparseInstance: Returns the description of one instance in sparse format.
toStringRanking() - Method in class weka.experiment.ResultMatrix: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixCSV: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixHTML: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixLatex: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixPlainText: returns the ranking in a string representation.
toStringRanking() - Method in class weka.experiment.ResultMatrixSignificance: returns the ranking in a string representation.
toStringSummary() - Method in class weka.experiment.ResultMatrix: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixCSV: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixGnuPlot: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixHTML: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixLatex: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixPlainText: returns the summary as string.
toStringSummary() - Method in class weka.experiment.ResultMatrixSignificance: returns the summary as string.
toSummaryString() - Method in class weka.associations.AssociatorEvaluation: returns a summary string of the evaluation with a no title
toSummaryString(String) - Method in class weka.associations.AssociatorEvaluation: returns a summary string of the evaluation with a default title
toSummaryString() - Method in class weka.classifiers.evaluation.Evaluation: Calls toSummaryString() with no title and no complexity stats.
toSummaryString(boolean) - Method in class weka.classifiers.evaluation.Evaluation: Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.evaluation.Evaluation: Outputs the performance statistics in summary form.
toSummaryString() - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in interface weka.classifiers.evaluation.IntervalBasedEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Return a formatted string (suitable for displaying in console or GUI output) containing all the statistics that this metric computes.
toSummaryString() - Method in class weka.classifiers.Evaluation: Calls toSummaryString() with no title and no complexity stats.
toSummaryString(boolean) - Method in class weka.classifiers.Evaluation: Calls toSummaryString() with a default title.
toSummaryString(String, boolean) - Method in class weka.classifiers.Evaluation: Outputs the performance statistics in summary form.
toSummaryString() - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns a summary string of the evaluation with a no title
toSummaryString(String) - Method in class weka.classifiers.functions.supportVector.KernelEvaluation: returns a summary string of the evaluation with a default title
toSummaryString() - Method in class weka.classifiers.meta.CVParameterSelection: A concise description of the model.
toSummaryString() - Method in class weka.classifiers.rules.PART: Returns a superconcise version of the model
toSummaryString() - Method in class weka.classifiers.trees.J48: Returns a superconcise version of the model
toSummaryString() - Method in class weka.core.Instances: Generates a string summarizing the set of instances.
toSummaryString() - Method in interface weka.core.Summarizable: Returns a string that summarizes the object.
total() - Method in class weka.classifiers.evaluation.ConfusionMatrix: Gets the number of predictions that were made (actually the sum of the weights of predictions where the class value was known).
total() - Method in class weka.classifiers.trees.j48.Distribution: Returns total number of (possibly fractional) instances.
TOTAL_UNIFORM - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster type: total uniform
totalCost() - Method in class weka.classifiers.evaluation.Evaluation: Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCost() - Method in class weka.classifiers.Evaluation: Gets the total cost, that is, the cost of each prediction times the weight of the instance, summed over all instances.
totalCount - Variable in class weka.core.AttributeStats: The total number of values (i.e.
totalWeight() - Method in class weka.classifiers.trees.ht.HNode: Return the total weight of instances seen at this node
toXML(int, int, int, int) - Method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE
toXML(Object) - Method in class weka.core.xml.XMLSerialization: extracts all accesible properties from the given object
toXMLBIF03() - Method in class weka.classifiers.bayes.BayesNet: Returns a description of the classifier in XML BIF 0.3 format.
toXMLBIF03() - Method in class weka.classifiers.bayes.net.EditableBayesNet: returns network in XMLBIF format
toXMLBIF03(ArrayList<Integer>) - Method in class weka.classifiers.bayes.net.EditableBayesNet: return fragment of network in XMLBIF format
toXMLBIF03() - Method in class weka.classifiers.bayes.net.MarginCalculator
TP_RATE_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Positive Rate
trace() - Method in class weka.core.matrix.Matrix: Matrix trace.
trainCV(int, int) - Method in class weka.core.Instances: Creates the training set for one fold of a cross-validation on the dataset.
trainCV(int, int, Random) - Method in class weka.core.Instances: Creates the training set for one fold of a cross-validation on the dataset.
TRAINING - Static variable in class weka.gui.beans.BatchClustererEvent
TrainingInstances - Class in weka.core.pmml.jaxbbindings: Java class for TrainingInstances element declaration.
TrainingInstances() - Constructor for class weka.core.pmml.jaxbbindings.TrainingInstances
TrainingSetEvent - Class in weka.gui.beans: Event encapsulating a training set
TrainingSetEvent(Object, Instances) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetEvent(Object, Instances, int, int) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetEvent(Object, Instances, int, int, int, int) - Constructor for class weka.gui.beans.TrainingSetEvent: Creates a new TrainingSetEvent
TrainingSetListener - Interface in weka.gui.beans: Interface to something that can accept and process training set events
TrainingSetMaker - Class in weka.gui.beans: Bean that accepts a data sets and produces a training set
TrainingSetMaker() - Constructor for class weka.gui.beans.TrainingSetMaker
TrainingSetMaker - Class in weka.knowledgeflow.steps: Step that converts an incoming dataSet or testSet into a trainingSet.
TrainingSetMaker() - Constructor for class weka.knowledgeflow.steps.TrainingSetMaker
TrainingSetMakerBeanInfo - Class in weka.gui.beans: Bean info class for the training set maker bean
TrainingSetMakerBeanInfo() - Constructor for class weka.gui.beans.TrainingSetMakerBeanInfo
TrainingSetProducer - Interface in weka.gui.beans: Interface to something that can produce a training set
trainingTimeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
trainPercentTipText() - Method in class weka.experiment.RandomSplitResultProducer: Returns the tip text for this property
trainPercentTipText() - Method in class weka.gui.beans.TrainTestSplitMaker: Tip text info for this property
TrainTestSplitMaker - Class in weka.gui.beans: Bean that accepts data sets, training sets, test sets and produces both a training and test set by randomly spliting the data
TrainTestSplitMaker() - Constructor for class weka.gui.beans.TrainTestSplitMaker
TrainTestSplitMaker - Class in weka.knowledgeflow.steps: A step that creates a random train/test split from an incoming data set.
TrainTestSplitMaker() - Constructor for class weka.knowledgeflow.steps.TrainTestSplitMaker
TrainTestSplitMakerBeanInfo - Class in weka.gui.beans: Bean info class for the train test split maker bean
TrainTestSplitMakerBeanInfo() - Constructor for class weka.gui.beans.TrainTestSplitMakerBeanInfo
TrainTestSplitMakerCustomizer - Class in weka.gui.beans: GUI customizer for the train test split maker bean
TrainTestSplitMakerCustomizer() - Constructor for class weka.gui.beans.TrainTestSplitMakerCustomizer
transactionsMustContainTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
transform(AffineTransform) - Method in class weka.gui.visualize.PostscriptGraphics
transformAllValuesTipText() - Method in class weka.filters.supervised.attribute.NominalToBinary: Returns the tip text for this property
transformAllValuesTipText() - Method in class weka.filters.unsupervised.attribute.NominalToBinary: Returns the tip text for this property
TransformationDictionary - Class in weka.core.pmml.jaxbbindings: Java class for TransformationDictionary element declaration.
TransformationDictionary() - Constructor for class weka.core.pmml.jaxbbindings.TransformationDictionary
transformBackToOriginalTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
transformedData(Instances) - Method in interface weka.attributeSelection.AttributeTransformer: Transform the supplied data set (assumed to be the same format as the training data)
transformedData(Instances) - Method in class weka.attributeSelection.PrincipalComponents: Gets the transformed training data.
transformedHeader() - Method in interface weka.attributeSelection.AttributeTransformer: Returns just the header for the transformed data (ie.
transformedHeader() - Method in class weka.attributeSelection.PrincipalComponents: Returns just the header for the transformed data (ie.
translate(int, int) - Method in class weka.gui.visualize.PostscriptGraphics: Translates the origin of the graphics context to the point (x, y) in the current coordinate system.
translate(double, double) - Method in class weka.gui.visualize.PostscriptGraphics
translateDBColumnType(String) - Method in class weka.experiment.DatabaseUtils: translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
translateDBColumnType(String) - Method in interface weka.experiment.InstanceQueryAdapter: translates the column data type string to an integer value that indicates which data type / get()-Method to use in order to retrieve values from the database (see DatabaseUtils.Properties, InstanceQuery()).
translationTipText() - Method in class weka.filters.unsupervised.attribute.Normalize: Returns the tip text for this property.
transpose() - Method in class weka.core.matrix.Matrix: Matrix transpose.
transpose() - Method in class weka.core.Matrix: Deprecated.

Returns the transpose of a matrix.
Transpose - Class in weka.filters.unsupervised.attribute: Transposes the data: instances become attributes and attributes become instances.
Transpose() - Constructor for class weka.filters.unsupervised.attribute.Transpose
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNominalAttribute: Calculates the probability of the indexed nominal attribute of the test instance transforming into the indexed nominal attribute of the training instance.
transProb() - Method in class weka.classifiers.lazy.kstar.KStarNumericAttribute: Calculates the transformation probability of the attribute indexed "m_AttrIndex" in test instance "m_Test" to the same attribute in the train instance "m_Train".
treatMissingValuesAsZeroTipText() - Method in class weka.filters.unsupervised.instance.NonSparseToSparse: Returns the tip text for this property
treatZeroAsMissingTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
TREE - Static variable in interface weka.core.Drawable
TreeBuild - Class in weka.gui.treevisualizer: This class will parse a dotty file and construct a tree structure from it with Edge's and Node's
TreeBuild() - Constructor for class weka.gui.treevisualizer.TreeBuild: Upon construction this will only setup the color table for quick reference of a color.
TreeDisplayEvent - Class in weka.gui.treevisualizer: An event containing the user selection from the tree display
TreeDisplayEvent(int, String) - Constructor for class weka.gui.treevisualizer.TreeDisplayEvent: Constructs an event with the specified command and what the command is applied to.
TreeDisplayListener - Interface in weka.gui.treevisualizer: Interface implemented by classes that wish to recieve user selection events from a tree displayer.
treeErrors() - Method in class weka.classifiers.trees.lmt.LMTNode: Updates the numIncorrectTree field for all nodes.
TreeModel - Class in weka.classifiers.pmml.consumer: Class implementing import of PMML TreeModel.
TreeModel(Element, Instances, MiningSchema) - Constructor for class weka.classifiers.pmml.consumer.TreeModel
TreeModel - Class in weka.core.pmml.jaxbbindings: Java class for TreeModel element declaration.
TreeModel() - Constructor for class weka.core.pmml.jaxbbindings.TreeModel
TreePerformanceStats - Class in weka.core.neighboursearch: The class that measures the performance of a tree based nearest neighbour search algorithm.
TreePerformanceStats() - Constructor for class weka.core.neighboursearch.TreePerformanceStats: Default constructor.
treeToString(int) - Method in class weka.classifiers.trees.m5.RuleNode: Recursively builds a textual description of the tree
TreeVisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
TreeVisualizer - Class in weka.gui.treevisualizer: Class for displaying a Node structure in Swing.
TreeVisualizer(TreeDisplayListener, String, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer: Constructs Displayer to display a tree provided in a dot format.
TreeVisualizer(TreeDisplayListener, Node, NodePlace) - Constructor for class weka.gui.treevisualizer.TreeVisualizer: Constructs Displayer with the specified Node as the top of the tree, and uses the NodePlacer to place the Nodes.
TrendExpoSmooth - Class in weka.core.pmml.jaxbbindings: Java class for Trend_ExpoSmooth element declaration.
TrendExpoSmooth() - Constructor for class weka.core.pmml.jaxbbindings.TrendExpoSmooth
TRIANGLEDOWN_SHAPE - Static variable in class weka.gui.visualize.Plot2D
TRIANGLEUP_SHAPE - Static variable in class weka.gui.visualize.Plot2D
TRICUBE - Static variable in class weka.classifiers.lazy.LWL
Trie - Class in weka.core: A class representing a Trie data structure for strings.
Trie() - Constructor for class weka.core.Trie: initializes the data structure
Trie.TrieIterator - Class in weka.core: Represents an iterator over a trie
Trie.TrieNode - Class in weka.core: Represents a node in the trie.
TrieIterator(Trie.TrieNode) - Constructor for class weka.core.Trie.TrieIterator: initializes the iterator
TrieNode(char) - Constructor for class weka.core.Trie.TrieNode: initializes the node
TrieNode(Character) - Constructor for class weka.core.Trie.TrieNode: initializes the node
trim() - Method in class weka.gui.LogWindow: trims the JTextPane, if too big
trimTipText() - Method in class weka.classifiers.misc.InputMappedClassifier: Returns the tip text for this property
True - Class in weka.core.pmml.jaxbbindings: Java class for True element declaration.
True() - Constructor for class weka.core.pmml.jaxbbindings.True
TRUE_NEG_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Negatives
TRUE_POS_NAME - Static variable in class weka.classifiers.evaluation.ThresholdCurve: attribute name: True Positives
trueClassCounts() - Method in class weka.classifiers.evaluation.Evaluation: Returns the number (really, weight) of instances in each class.
trueNegativeRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true negative rate with respect to a particular class.
trueNegativeRate(int, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true negative rate with respect to a particular class.
trueNegativeRate(int) - Method in class weka.classifiers.Evaluation: Calculate the true negative rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true positive rate with respect to a particular class.
truePositiveRate(int, double) - Method in class weka.classifiers.evaluation.Evaluation: Calculate the true positive rate with respect to a particular class.
truePositiveRate(int) - Method in class weka.classifiers.Evaluation: Calculate the true positive rate with respect to a particular class.
truncateTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
TStartTipText() - Method in class weka.classifiers.bayes.net.search.global.SimulatedAnnealing
TStartTipText() - Method in class weka.classifiers.bayes.net.search.local.SimulatedAnnealing
turnChecksOff() - Method in class weka.classifiers.functions.LinearRegression: Turns off checks for missing values, etc.
turnChecksOff() - Method in class weka.classifiers.functions.SMO: Turns off checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.LinearRegression: Turns on checks for missing values, etc.
turnChecksOn() - Method in class weka.classifiers.functions.SMO: Turns on checks for missing values, etc.
TwoClassStats - Class in weka.classifiers.evaluation: Encapsulates performance functions for two-class problems.
TwoClassStats(double, double, double, double) - Constructor for class weka.classifiers.evaluation.TwoClassStats: Creates the TwoClassStats with the given initial performance values.
type() - Method in class weka.core.Attribute: Returns the attribute's type as an integer.
TYPE - Static variable in class weka.core.json.JSONInstances: the type attribute.
type - Variable in class weka.gui.graphvisualizer.GraphEdge: The type of Edge
typeIsNumeric(int) - Static method in class weka.gui.sql.ResultSetHelper: returns whether the SQL type is numeric (and therefore the justification should be right).
typeName(int) - Static method in class weka.experiment.DatabaseUtils: Returns the name associated with a SQL type.
typeToClass(int) - Static method in class weka.gui.sql.ResultSetHelper: Returns the class associated with a SQL type.
typeToString(Attribute) - Static method in class weka.core.Attribute: Returns a string representation of the attribute type.
typeToString(int) - Static method in class weka.core.Attribute: Returns a string representation of the attribute type.
typeToStringShort(Attribute) - Static method in class weka.core.Attribute: Returns a short string representation of the attribute type.
typeToStringShort(int) - Static method in class weka.core.Attribute: Returns a short string representation of the attribute type.

U

uminus(Node) - Static method in class weka.core.expressionlanguage.common.Operators: '-' unary minus operator
UMINUS - Static variable in interface weka.core.expressionlanguage.parser.sym
uminus() - Method in class weka.core.matrix.Matrix: Unary minus
UnassignedClassException - Exception in weka.core: Exception that is raised when trying to use some data that has no class assigned to it, but a class is needed to perform the operation.
UnassignedClassException() - Constructor for exception weka.core.UnassignedClassException: Creates a new UnassignedClassException with no message.
UnassignedClassException(String) - Constructor for exception weka.core.UnassignedClassException: Creates a new UnassignedClassException.
UnassignedDatasetException - Exception in weka.core: Exception that is raised when trying to use something that has no reference to a dataset, when one is required.
UnassignedDatasetException() - Constructor for exception weka.core.UnassignedDatasetException: Creates a new UnassignedDatasetException with no message.
UnassignedDatasetException(String) - Constructor for exception weka.core.UnassignedDatasetException: Creates a new UnassignedDatasetException.
unbackQuoteChars(String) - Static method in class weka.core.Utils: The inverse operation of backQuoteChars().
unclassified() - Method in class weka.classifiers.evaluation.Evaluation: Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
unclassified() - Method in class weka.classifiers.Evaluation: Gets the number of instances not classified (that is, for which no prediction was made by the classifier).
UNCONNECTED - Static variable in class weka.classifiers.functions.neural.NeuralConnection: This unit is not connected to any others.
undefinedDistribution - Static variable in class weka.core.matrix.Maths: Distribution type: undefined
undo() - Method in class weka.classifiers.bayes.net.EditableBayesNet: undo the last edit action performed on the network.
undo() - Method in interface weka.core.Undoable: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffPanel: performs an undo action
undo() - Method in class weka.gui.arffviewer.ArffSortedTableModel: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffTableModel: undoes the last action
undo() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: undoes the last action
undo() - Method in class weka.gui.explorer.PreprocessPanel: Reverts to the last backed up version of the dataset.
UNDO_DIR - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
UNDO_DIR_KEY - Static variable in class weka.gui.explorer.PreprocessPanel.PreprocessDefaults
Undoable - Interface in weka.core: Interface implemented by classes that support undo.
UNHANDLED_DIALOG - Static variable in class weka.gui.ConverterFileChooser: unhandled type of dialog.
UNIFORM_RANDOM - Static variable in class weka.datagenerators.clusterers.SubspaceCluster: cluster type: uniform/random
UniformDistribution - Class in weka.core.pmml.jaxbbindings: Java class for UniformDistribution element declaration.
UniformDistribution() - Constructor for class weka.core.pmml.jaxbbindings.UniformDistribution
uninstallPackage(String, PrintStream...) - Method in class weka.core.packageManagement.DefaultPackageManager: Uninstall a package.
uninstallPackage(String, PrintStream...) - Method in class weka.core.packageManagement.PackageManager: Uninstall a package.
uninstallPackage(String, boolean, PrintStream...) - Static method in class weka.core.WekaPackageManager: Uninstall a named package
uniqueCount - Variable in class weka.core.AttributeStats: The number of values that only appear once
UnivariateDensityEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate density estimators.
UnivariateEqualFrequencyHistogramEstimator - Class in weka.estimators: Simple histogram density estimator.
UnivariateEqualFrequencyHistogramEstimator() - Constructor for class weka.estimators.UnivariateEqualFrequencyHistogramEstimator
UnivariateIntervalEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate interval estimators.
UnivariateKernelEstimator - Class in weka.estimators: Simple weighted kernel density estimator.
UnivariateKernelEstimator() - Constructor for class weka.estimators.UnivariateKernelEstimator
UnivariateMixtureEstimator - Class in weka.estimators: Simple weighted mixture density estimator.
UnivariateMixtureEstimator() - Constructor for class weka.estimators.UnivariateMixtureEstimator
UnivariateMixtureEstimator.MM - Class in weka.estimators: Fast univariate mixture model implementation.
UnivariateNominalMultiwaySplit - Class in weka.classifiers.trees.ht: A multiway split based on a single nominal attribute
UnivariateNominalMultiwaySplit(String) - Constructor for class weka.classifiers.trees.ht.UnivariateNominalMultiwaySplit: Constructor
UnivariateNormalEstimator - Class in weka.estimators: Simple weighted normal density estimator.
UnivariateNormalEstimator() - Constructor for class weka.estimators.UnivariateNormalEstimator
UnivariateNumericBinarySplit - Class in weka.classifiers.trees.ht: A binary split based on a single numeric attribute
UnivariateNumericBinarySplit(String, double) - Constructor for class weka.classifiers.trees.ht.UnivariateNumericBinarySplit: Constructor
UnivariateQuantileEstimator - Interface in weka.estimators: Interface that can be implemented by simple weighted univariate quantile estimators.
UnivariateStats - Class in weka.core.pmml.jaxbbindings: Java class for UnivariateStats element declaration.
UnivariateStats() - Constructor for class weka.core.pmml.jaxbbindings.UnivariateStats
UNKNOWN_NOMINAL_VALUE - Static variable in class weka.core.pmml.MappingInfo: Index for incoming nominal values that are not defined in the mining schema.
UnknownStatisticException(String) - Constructor for exception weka.classifiers.evaluation.AbstractEvaluationMetric.UnknownStatisticException: Constructs a new UnknownStatisticsException
unnormalizedKernel(char[], char[]) - Method in class weka.classifiers.functions.supportVector.StringKernel: evaluates the unnormalized kernel between s and t.
unpivoting(IntVector, int) - Method in class weka.core.matrix.DoubleVector: Returns a vector from the pivoting indices.
unprunedTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
unprunedTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
unprunedTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
unquote(String) - Static method in class weka.core.Utils: unquotes are previously quoted string (but only if necessary), i.e., it removes the single quotes around it.
unrecovered_syntax_error(Symbol) - Method in class weka.core.expressionlanguage.parser.Parser
UNSET - Static variable in class weka.filters.unsupervised.attribute.ClassAssigner: unset the class attribute.
Unset - Class in weka.gui.simplecli: Removes a variable.
Unset() - Constructor for class weka.gui.simplecli.Unset
unsorted() - Method in class weka.core.matrix.DoubleVector: Returns true if vector not sorted
UnsupervisedAttributeEvaluator - Class in weka.attributeSelection: Abstract unsupervised attribute evaluator.
UnsupervisedAttributeEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedAttributeEvaluator
UnsupervisedFilter - Interface in weka.filters: Interface for filters that do not need a class attribute.
UnsupervisedSubsetEvaluator - Class in weka.attributeSelection: Abstract unsupervised attribute subset evaluator.
UnsupervisedSubsetEvaluator() - Constructor for class weka.attributeSelection.UnsupervisedSubsetEvaluator
UnsupportedAttributeTypeException - Exception in weka.core: Exception that is raised by an object that is unable to process some of the attribute types it has been passed.
UnsupportedAttributeTypeException() - Constructor for exception weka.core.UnsupportedAttributeTypeException: Creates a new UnsupportedAttributeTypeException with no message.
UnsupportedAttributeTypeException(String) - Constructor for exception weka.core.UnsupportedAttributeTypeException: Creates a new UnsupportedAttributeTypeException.
UnsupportedClassTypeException - Exception in weka.core: Exception that is raised by an object that is unable to process the class type of the data it has been passed.
UnsupportedClassTypeException() - Constructor for exception weka.core.UnsupportedClassTypeException: Creates a new UnsupportedClassTypeException with no message.
UnsupportedClassTypeException(String) - Constructor for exception weka.core.UnsupportedClassTypeException: Creates a new UnsupportedClassTypeException.
unweightedMacroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation: Unweighted macro-averaged F-measure.
unweightedMacroFmeasure() - Method in class weka.classifiers.Evaluation: Unweighted macro-averaged F-measure.
unweightedMicroFmeasure() - Method in class weka.classifiers.evaluation.Evaluation: Unweighted micro-averaged F-measure.
unweightedMicroFmeasure() - Method in class weka.classifiers.Evaluation: Unweighted micro-averaged F-measure.
update(MarginCalculator.JunctionTreeNode) - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set
update(double, String, double) - Method in class weka.classifiers.trees.ht.ConditionalSufficientStats: Update this stat with the supplied attribute value and class value
update(double, String, double) - Method in class weka.classifiers.trees.ht.GaussianConditionalSufficientStats
update(double, String, double) - Method in class weka.classifiers.trees.ht.NominalConditionalSufficientStats
update(Instance) - Method in interface weka.core.DistanceFunction: Update the distance function (if necessary) for the newly added instance.
update(Instance) - Method in class weka.core.FilteredDistance: Update the distance function (if necessary) for the newly added instance.
update(double) - Method in class weka.core.matrix.FlexibleDecimalFormat
update(Instance) - Method in class weka.core.neighboursearch.BallTree: Adds one instance to the BallTree.
update(Instance) - Method in class weka.core.neighboursearch.CoverTree: Adds an instance to the cover tree.
update(Instance) - Method in class weka.core.neighboursearch.FilteredNeighbourSearch: Updates ranges based on the given instance, once it has been filtered.
update(Instance) - Method in class weka.core.neighboursearch.KDTree: Adds one instance to the KDTree.
update(Instance) - Method in class weka.core.neighboursearch.LinearNNSearch: Updates the LinearNNSearch to cater for the new added instance.
update(Instance) - Method in class weka.core.neighboursearch.NearestNeighbourSearch: Updates the NearNeighbourSearch algorithm for the new added instance.
update(Instance) - Method in class weka.core.NormalizableDistance: Update the distance function (if necessary) for the newly added instance.
update(String) - Method in class weka.experiment.DatabaseUtils: Executes a SQL DDL query or an INSERT, DELETE or UPDATE.
update(Graphics) - Method in class weka.gui.SplashWindow: Updates the display area of the window.
UpdateableBatchProcessor - Interface in weka.classifiers: Updateable classifiers can implement this if they wish to be informed at the end of the training stream.
UpdateableClassifier - Interface in weka.classifiers: Interface to incremental classification models that can learn using one instance at a time.
UpdateableClusterer - Interface in weka.clusterers: Interface to incremental cluster models that can learn using one instance at a time.
updateChildPropertySheet() - Method in class weka.gui.GenericObjectEditor.GOEPanel: Updates the child property sheet, and creates if needed.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.BayesNet: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayes: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.bayes.NaiveBayesMultinomialUpdateable: Updates the classifier with information from one training instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BayesNetEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.BMAEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.MultiNomialBMAEstimator: Updates the classifier with the given instance.
updateClassifier(BayesNet, Instance) - Method in class weka.classifiers.bayes.net.estimate.SimpleEstimator: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.functions.SGD: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.functions.SGDText: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.lazy.IBk: Adds the supplied instance to the training set.
updateClassifier(Instance) - Method in class weka.classifiers.lazy.KStar: Adds the supplied instance to the training set
updateClassifier(Instance) - Method in class weka.classifiers.lazy.LWL: Adds the supplied instance to the training set.
updateClassifier(Instance) - Method in class weka.classifiers.meta.MultiClassClassifierUpdateable: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in class weka.classifiers.trees.HoeffdingTree: Updates the classifier with the given instance.
updateClassifier(Instance) - Method in interface weka.classifiers.UpdateableClassifier: Updates a classifier using the given instance.
updateClusterer(Instance) - Method in class weka.clusterers.Canopy
updateClusterer(Instance) - Method in class weka.clusterers.Cobweb: Adds an instance to the clusterer.
updateClusterer(Instance) - Method in interface weka.clusterers.UpdateableClusterer: Adds an instance to the clusterer.
upDateCounter(Instance) - Method in class weka.associations.ItemSet: Updates counter of item set with respect to given transaction.
upDateCounter(Instance, Instance) - Method in class weka.associations.LabeledItemSet: Updates counter of item set with respect to given transaction.
upDateCounters(ArrayList<Object>, Instances) - Static method in class weka.associations.ItemSet: Updates counters for a set of item sets and a set of instances.
upDateCounters(ArrayList<Object>, Instances, Instances) - Static method in class weka.associations.LabeledItemSet: Updates counter of a specific item set
upDateCountersTreatZeroAsMissing(ArrayList<Object>, Instances) - Static method in class weka.associations.ItemSet: Updates counters for a set of item sets and a set of instances.
upDateCountersTreatZeroAsMissing(ArrayList<LabeledItemSet>, Instances, Instances) - Static method in class weka.associations.LabeledItemSet: Updates counter of a specific item set
updateCounterTreatZeroAsMissing(Instance) - Method in class weka.associations.ItemSet: Updates counter of item set with respect to given transaction.
upDateCounterTreatZeroAsMissing(Instance, Instance) - Method in class weka.associations.LabeledItemSet: Updates counter of item set with respect to given transaction.
updateDistribution(Instance) - Method in class weka.classifiers.trees.ht.HNode: Update the class frequency distribution with the supplied instance
updateEnd(Logger) - Method in class weka.gui.beans.StreamThroughput: Register a throughput measurement end point.
updateFinished() - Method in class weka.clusterers.Canopy
updateFinished() - Method in class weka.clusterers.Cobweb: Singals the end of the updating.
updateFinished() - Method in interface weka.clusterers.UpdateableClusterer: Signals the end of the updating.
updateFrameTitle() - Method in class weka.gui.arffviewer.ArffViewerMainPanel: sets the title of the parent frame, if one was provided
updateFromChild() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set of the child clique
updateFromParent() - Method in class weka.classifiers.bayes.net.MarginCalculator.JunctionTreeSeparator: marginalize junciontTreeNode node over all nodes outside the separator set of the parent clique
updateJavadoc() - Method in class weka.core.Javadoc: generates the Javadoc and returns it applied to the source file if one was provided, otherwise an empty string.
updateNode(Instance) - Method in class weka.classifiers.trees.ht.ActiveHNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.HNode: Update the node with the supplied instance
updateNode(Instance) - Method in class weka.classifiers.trees.ht.InactiveHNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.LeafNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.NBNode
updateNode(Instance) - Method in class weka.classifiers.trees.ht.NBNodeAdaptive
updateNode(Instance) - Method in class weka.classifiers.trees.ht.SplitNode
updatePanel() - Method in class weka.gui.visualize.MatrixPanel: Update the display.
updatePointCount(int) - Method in class weka.core.neighboursearch.PerformanceStats: adds the given number to the point count.
updatePriors(Instance) - Method in class weka.classifiers.evaluation.Evaluation: Updates the class prior probabilities or the mean respectively (when incrementally training).
updatePriors(Instance) - Method in class weka.classifiers.Evaluation: Updates the class prior probabilities or the mean respectively (when incrementally training).
updateRanges(Instance, int, double[][]) - Method in class weka.core.NormalizableDistance: Updates the minimum and maximum and width values for all the attributes based on a new instance.
updateRanges(Instance, double[][]) - Method in class weka.core.NormalizableDistance: Updates the ranges given a new instance.
updateRanges(Instance) - Method in class weka.core.NormalizableDistance: Update the ranges with a new instance.
updateRangesFirst(Instance, int, double[][]) - Method in class weka.core.NormalizableDistance: Used to initialize the ranges.
updateResult(String) - Method in class weka.gui.ResultHistoryPanel: Tells any component currently displaying the named result that the contents of the result text in the StringBuffer have been updated.
updateStart() - Method in class weka.gui.beans.StreamThroughput: Register a throughput measurement start point
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.InformationRetrievalEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForClassifier(double[], Instance) - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Updates the statistics about a classifiers performance for the current test instance.
updateStatsForConditionalDensityEstimator(ConditionalDensityEstimator, Instance, double) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates stats for conditional density estimator based on current test instance.
updateStatsForIntervalEstimator(IntervalEstimator, Instance, double) - Method in interface weka.classifiers.evaluation.IntervalBasedEvaluationMetric: Updates stats for interval estimator based on current test instance.
updateStatsForModelCVSplit(Instances, ASEvaluation, ASSearch, int[], boolean) - Method in class weka.attributeSelection.AttributeSelection: Update the attribute selection stats for a cross-validation fold of the data.
updateStatsForPredictor(double, Instance) - Method in interface weka.classifiers.evaluation.InformationTheoreticEvaluationMetric: Updates the statistics about a predictors performance for the current test instance.
updateStatsForPredictor(double, Instance) - Method in interface weka.classifiers.evaluation.StandardEvaluationMetric: Updates the statistics about a predictors performance for the current test instance.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.LinearUnit: This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in interface weka.classifiers.functions.neural.NeuralMethod: This function will calculate what the change in weights should be and also update them.
updateWeights(double, double) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this function to update the weight values at this unit.
updateWeights(NeuralNode, double, double) - Method in class weka.classifiers.functions.neural.SigmoidUnit: This function will calculate what the change in weights should be and also update them.
updateWidth() - Method in class weka.estimators.UnivariateKernelEstimator: Updates bandwidth: the sample standard deviation is multiplied by the total weight to the power of the given exponent.
uplus(Node) - Static method in class weka.core.expressionlanguage.common.Operators: '+' unary plus operator
UPLUS - Static variable in interface weka.core.expressionlanguage.parser.sym
upperBoundMinSupportTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
upperBoundMinSupportTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
upperNumericBoundIsOpen() - Method in class weka.core.Attribute: Returns whether the upper numeric bound of the attribute is open.
upperSizeTipText() - Method in class weka.experiment.LearningRateResultProducer: Returns the tip text for this property
URLSourcedLoader - Interface in weka.core.converters: Interface to a loader that can load from a http url
urlTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
urlTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
USE_DYNAMIC - Static variable in class weka.gui.GenericPropertiesCreator: name of property whether to use the dynamic approach or the old GenericObjectEditor.props file
useADTreeTipText() - Method in class weka.classifiers.bayes.BayesNet
useAICTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
useAICTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.global.HillClimber
useArcReversalTipText() - Method in class weka.classifiers.bayes.net.search.local.HillClimber
useAverageTipText() - Method in class weka.classifiers.meta.IterativeClassifierOptimizer: Returns the tip text for this property
useBetterEncodingTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useBinNumbersTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useBinNumbersTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
useConjugateGradientDescentTipText() - Method in class weka.classifiers.functions.Logistic: Returns the tip text for this property
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useCrossOverTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useCrossValidationTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
used() - Method in class weka.core.expressionlanguage.weka.StatsHelper: Whether Stats fields are accessed in the program
used(String) - Method in class weka.core.expressionlanguage.weka.StatsHelper: Returns whether the Stats field is used in the program
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSink: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractDataSource: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.AbstractEvaluator: Use the default images for an evaluator
useDefaultVisual() - Method in class weka.gui.beans.AbstractTestSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainAndTestSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.AbstractTrainingSetProducer: Use the default visual for this bean
useDefaultVisual() - Method in class weka.gui.beans.Appender: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.Associator: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.AttributeSummarizer: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassAssigner
useDefaultVisual() - Method in class weka.gui.beans.Classifier: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ClassValuePicker
useDefaultVisual() - Method in class weka.gui.beans.Clusterer: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.CostBenefitAnalysis
useDefaultVisual() - Method in class weka.gui.beans.DataVisualizer: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.Filter: Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.FlowByExpression
useDefaultVisual() - Method in class weka.gui.beans.GraphViewer: Use the default visual appearance
useDefaultVisual() - Method in class weka.gui.beans.ImageSaver
useDefaultVisual() - Method in class weka.gui.beans.ImageViewer
useDefaultVisual() - Method in class weka.gui.beans.InstanceStreamToBatchMaker: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.Join: Use the default visual for this step
useDefaultVisual() - Method in class weka.gui.beans.MetaBean: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.ModelPerformanceChart: Use the default appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.PredictionAppender: Use the default images for a data source
useDefaultVisual() - Method in class weka.gui.beans.SerializedModelSaver: Use the default images for this bean.
useDefaultVisual() - Method in class weka.gui.beans.Sorter: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.StripChart: Use the default visual appearance for this bean
useDefaultVisual() - Method in class weka.gui.beans.SubstringLabeler: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.SubstringReplacer: Use the default visual representation
useDefaultVisual() - Method in class weka.gui.beans.TextSaver
useDefaultVisual() - Method in class weka.gui.beans.TextViewer: Use the default visual appearance for this bean
useDefaultVisual() - Method in interface weka.gui.beans.Visible: Use the default visual representation
useDoubleTipText() - Method in class weka.core.converters.MatlabSaver: Returns the tip text for this property.
useDynamic() - Method in class weka.gui.GenericPropertiesCreator: gets whether the dynamic approach should be used or not
useEqualFrequencyTipText() - Method in class weka.classifiers.meta.RegressionByDiscretization: Returns the tip text for this property
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.Discretize: Returns the tip text for this property
useEqualFrequencyTipText() - Method in class weka.filters.unsupervised.attribute.PKIDiscretize: Returns the tip text for this property
useEstimatedPriorsTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
useFilter(Instances, Filter) - Static method in class weka.filters.Filter: Filters an entire set of instances through a filter and returns the new set.
useIBkTipText() - Method in class weka.classifiers.rules.DecisionTable: Returns the tip text for this property
useKernelEstimatorTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
useKononenkoTipText() - Method in class weka.filters.supervised.attribute.Discretize: Returns the tip text for this property
useLaplaceTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
useLeastValuesTipText() - Method in class weka.filters.unsupervised.instance.RemoveFrequentValues: Returns the tip text for this property
useLowerOrderTipText() - Method in class weka.classifiers.functions.supportVector.PolyKernel: Returns the tip text for this property
useMDLcorrectionTipText() - Method in class weka.classifiers.rules.PART: Returns the tip text for this property
useMDLcorrectionTipText() - Method in class weka.classifiers.trees.J48: Returns the tip text for this property
useMissingTipText() - Method in class weka.filters.unsupervised.attribute.AddNoise: Returns the tip text for this property
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useMutationTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useNoPriors() - Method in class weka.classifiers.evaluation.Evaluation: disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
useNoPriors() - Method in class weka.classifiers.Evaluation: disables the use of priors, e.g., in case of de-serialized schemes that have no access to the original training set, but are evaluated on a set set.
useNormalizationTipText() - Method in class weka.classifiers.functions.supportVector.StringKernel: Returns the tip text for this property
useORForMustContainListTipText() - Method in class weka.associations.FPGrowth: Returns the tip text for this property
usePairwiseCouplingTipText() - Method in class weka.classifiers.meta.MultiClassClassifier
usePercentageSplitTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
useProbTipText() - Method in class weka.classifiers.bayes.net.search.global.GlobalScoreSearchAlgorithm
usePruningTipText() - Method in class weka.classifiers.rules.JRip: Returns the tip text for this property
useQRDecompositionTipText() - Method in class weka.classifiers.functions.LinearRegression: Returns the tip text for this property.
user_init() - Method in class weka.core.json.Parser: User initialization code.
userCommand(TreeDisplayEvent) - Method in interface weka.gui.treevisualizer.TreeDisplayListener: Gets called when the user selects something, in the tree display.
userDataEvent(VisualizePanelEvent) - Method in interface weka.gui.visualize.VisualizePanelListener: This method receives an object containing the shapes, instances inside and outside these shapes and the attributes these shapes were created in.
useRelativePathTipText() - Method in class weka.core.converters.AbstractFileLoader: Tip text suitable for displaying int the GUI
useRelativePathTipText() - Method in class weka.core.converters.AbstractFileSaver: Tip text suitable for displaying int the GUI
useResamplingTipText() - Method in class weka.classifiers.meta.AdaBoostM1: Returns the tip text for this property
useResamplingTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
usernameTipText() - Method in class weka.experiment.DatabaseUtils: Returns the tip text for this property.
UserRequestAcceptor - Interface in weka.gui.beans: Interface to something that can accept requests from a user to perform some action
userRequestedPerspectiveToolbarVisibleOnStartup(Settings) - Method in class weka.gui.PerspectiveManager: Returns true if the user has requested that the perspective toolbar is visible when the application starts up
userTipText() - Method in class weka.core.converters.DatabaseLoader: the tip text for this property
userTipText() - Method in class weka.core.converters.DatabaseSaver: Returns the tip text for this property.
useShortIdentifiersTipText() - Method in class weka.filters.supervised.attribute.MergeNominalValues: Returns the tip text for this property
useShortIDsTipText() - Method in class weka.filters.unsupervised.attribute.MergeInfrequentNominalValues: Returns the tip text for this property
useStemmer(Stemmer, String[]) - Static method in class weka.core.stemmers.Stemming: Applies the given stemmer according to the given options.
useSupervisedDiscretizationTipText() - Method in class weka.classifiers.bayes.NaiveBayes: Returns the tip text for this property
useTabsTipText() - Method in class weka.core.converters.MatlabSaver: Returns the tip text for this property.
useTabTipText() - Method in class weka.classifiers.evaluation.output.prediction.CSV: Returns the tip text for this property.
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.global.GeneticSearch
useTournamentSelectionTipText() - Method in class weka.classifiers.bayes.net.search.local.GeneticSearch
useTrainingTipText() - Method in class weka.attributeSelection.ClassifierSubsetEval: Returns the tip text for this property
useUnsmoothedTipText() - Method in class weka.classifiers.trees.m5.M5Base: Returns the tip text for this property
useVariant1TipText() - Method in class weka.classifiers.functions.supportVector.RegSMOImproved: Returns the tip text for this property
useWordFrequenciesTipText() - Method in class weka.classifiers.bayes.NaiveBayesMultinomialText: Returns the tip text for this property
useWordFrequenciesTipText() - Method in class weka.classifiers.functions.SGDText: Returns the tip text for this property
Utils - Class in weka.core: Class implementing some simple utility methods.
Utils() - Constructor for class weka.core.Utils

V

VAL_ANIMATEDICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the animatedIconPath property
VAL_ASSOCIATEDCONNECTIONS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the associatedConnections property
VAL_BEAN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the bean property
VAL_BEANCONTEXT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the beanContext property
VAL_BLUE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the blue property
VAL_CELLS - Static variable in class weka.core.xml.XMLBasicSerialization: the matrix cells
VAL_COLOR - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the color property
VAL_CUSTOM_NAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the customName property
VAL_DATE - Static variable in class weka.core.xml.XMLInstances: the value for date
VAL_DIR - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the dir property
VAL_EVENTNAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the eventname property
VAL_FILE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the file property
VAL_FONT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the font property
VAL_GREEN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the green property
VAL_HEIGHT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the height property
VAL_HIDDEN - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the hidden property
VAL_ICONPATH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the iconpath property
VAL_ID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the id property
VAL_INPUTS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the input property
VAL_INPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the input id property
VAL_KEY - Static variable in class weka.core.xml.XMLBasicSerialization: the value for a mapping-key, e.g., Maps
VAL_LOADER - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the loader property
VAL_LOCATION - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the location property
VAL_MAPPING - Static variable in class weka.core.xml.XMLBasicSerialization: the value for mapping, e.g., Maps
VAL_NAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the value property
VAL_NO - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the value "no".
VAL_NO - Static variable in class weka.core.xml.XMLDocument: the value "no".
VAL_NO - Static variable in class weka.core.xml.XMLSerialization: the value "no" for the primitive and array attribute
VAL_NOMINAL - Static variable in class weka.core.xml.XMLInstances: the value for nominal
VAL_NORMAL - Static variable in class weka.core.xml.XMLInstances: the value for normal
VAL_NUMERIC - Static variable in class weka.core.xml.XMLInstances: the value for numeric
VAL_OPTIONS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the options property
VAL_ORIGINALCOORDS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the originalCoords property
VAL_OUTPUTS - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the outputs id property
VAL_OUTPUTSID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the outputs property
VAL_PREFIX - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the prefix property
VAL_RED - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the red property
VAL_RELATIONAL - Static variable in class weka.core.xml.XMLInstances: the value for relational
VAL_RELATIONNAMEFORFILENAME - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the relationNameForFilename property (Saver)
VAL_RELATIVE_PATH - Static variable in class weka.gui.beans.xml.XMLBeans
VAL_ROOT - Static variable in class weka.core.xml.XMLSerialization: the value of the name for the root node
VAL_SAVER - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the saver property
VAL_SIZE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the size property
VAL_SOURCEID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the source property
VAL_SPARSE - Static variable in class weka.core.xml.XMLInstances: the value for sparse
VAL_STRING - Static variable in class weka.core.xml.XMLInstances: the value for string
VAL_STYLE - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the style property
VAL_SUBFLOW - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the subFlow property
VAL_TARGETID - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the target property
VAL_TEXT - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the text property
VAL_TYPE_CLASSIFIER - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_FLAG - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_HYPHENS - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_OPTIONHANDLER - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_QUOTES - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_TYPE_SINGLE - Static variable in class weka.core.xml.XMLOptions: a value of the type attribute.
VAL_VALUE - Static variable in class weka.core.xml.XMLBasicSerialization: the value for mapping-value, e.g., Maps
VAL_WIDTH - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the width property
VAL_X - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the x property
VAL_Y - Static variable in class weka.gui.beans.xml.XMLBeans: the value of the y property
VAL_YES - Static variable in class weka.classifiers.evaluation.output.prediction.XML: the value "yes".
VAL_YES - Static variable in class weka.core.xml.XMLDocument: the value "yes".
VAL_YES - Static variable in class weka.core.xml.XMLSerialization: the value "yes" for the primitive and array attribute
validateFileFormat(Tag) - Method in class weka.gui.beans.SerializedModelSaver: Validate the file format.
validationSetSizeTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
validationThresholdTipText() - Method in class weka.classifiers.functions.MultilayerPerceptron
VALIDTIMESPEC - Enum in weka.core.pmml.jaxbbindings: Java class for VALID-TIME-SPEC.
value - Variable in class weka.classifiers.lazy.kstar.KStarCache.TableEntry: scale factor or stop parameter
value(Attribute) - Method in class weka.core.AbstractInstance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.Attribute: Returns a value of a nominal or string attribute.
value(int) - Method in class weka.core.BinarySparseInstance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.DenseInstance: Returns an instance's attribute value in internal format.
value(int) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format.
value(Attribute) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format.
value(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array.
value() - Method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC
value() - Method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.DATATYPE
value() - Method in enum weka.core.pmml.jaxbbindings.DELIMITER2
value() - Method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE
value() - Method in enum weka.core.pmml.jaxbbindings.GAP
value() - Method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION
value() - Method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY
value() - Method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY
value() - Method in enum weka.core.pmml.jaxbbindings.OPTYPE
value() - Method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE
value() - Method in enum weka.core.pmml.jaxbbindings.RULEFEATURE
value() - Method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD
value() - Method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION
value() - Method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2
value() - Method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE
value() - Method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM
value() - Method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE
value() - Method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC
Value - Class in weka.core.pmml.jaxbbindings: Java class for Value element declaration.
Value() - Constructor for class weka.core.pmml.jaxbbindings.Value
Value(String) - Constructor for class weka.core.pmml.jaxbbindings.Value
value(int) - Method in class weka.core.pmml.SparseArray: Gets the value at index from the array.
value(int) - Method in class weka.core.SparseInstance: Returns an instance's attribute value in internal format.
value - Variable in class weka.experiment.PropertyNode: The current property value
valueDouble(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a double.
valueFloat(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a float.
valueFromString(String, String) - Static method in class weka.core.EnumHelper: Helper method to recover an enum value given the fully qualified name of the enum and the value in question as strings
valueFromString(Class<?>, String) - Static method in class weka.core.EnumHelper: Helper method to recover an enum value given the fully qualified name of the enum and the value in question as strings
valueIndicesTipText() - Method in class weka.filters.unsupervised.attribute.MakeIndicator
valueInt(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as an int.
valueIsSmallerEqual(Instance, int, double) - Method in class weka.core.EuclideanDistance: Returns true if the value of the given dimension is smaller or equal the value to be compared with.
valueOf(String) - Static method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.associations.NumericItem.Comparison: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.Capabilities.Capability: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.json.JSONNode.NodeType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.logging.Logger.Level: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.packageManagement.VersionPackageConstraint.VersionComparison: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.Array.ArrayType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Optype: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.FieldMetaInfo.Value.Property: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.GAP: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.RevisionUtils.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.TechnicalInformation.Field: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.core.TechnicalInformation.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.filters.unsupervised.attribute.InterquartileRange.ValueType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.explorer.AttributeSelectionPanel.TestMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.explorer.ClassifierPanel.TestMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.explorer.ClustererPanel.TestMode: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.GUIChooser.GUIChooserMenuPlugin.Menu: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.knowledgeflow.MainKFPerspectiveToolBar.Widgets: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.scripting.event.ScriptExecutionEvent.Type: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.gui.scripting.SyntaxDocument.ATTR_TYPE: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.knowledgeflow.LoggingLevel: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.knowledgeflow.steps.FlowByExpression.ExpressionClause.ExpressionType: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum weka.Run.SchemeType: Returns the enum constant of this type with the specified name.
valueReplacementsTipText() - Method in class weka.filters.unsupervised.attribute.RenameNominalValues: Returns the tip text for this property
values() - Static method in enum weka.associations.DefaultAssociationRule.METRIC_TYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.associations.NumericItem.Comparison: Returns an array containing the constants of this enum type, in the order they are declared.
Values - Class in weka.classifiers.trees.m5: Stores some statistics.
Values(int, int, int, Instances) - Constructor for class weka.classifiers.trees.m5.Values: Constructs an object which stores some statistics of the instances such as sum, squared sum, variance, standard deviation
values() - Static method in enum weka.core.Capabilities.Capability: Returns an array containing the constants of this enum type, in the order they are declared.
VALUES - Static variable in class weka.core.json.JSONInstances: the values attribute.
values() - Static method in enum weka.core.json.JSONNode.NodeType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.logging.Logger.Level: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.packageManagement.VersionPackageConstraint.VersionComparison: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.Array.ArrayType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Interval.Closure: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Optype: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.FieldMetaInfo.Value.Property: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.ACTIVATIONFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.BASELINETESTSTATISTIC: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CATSCORINGMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.COMPAREFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CONTSCORINGMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.CUMULATIVELINKFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.DATATYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.DELIMITER2: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.FIELDUSAGETYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.GAP: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.INTERPOLATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.INVALIDVALUETREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.LINKFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MININGFUNCTION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUESTRATEGY: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MISSINGVALUETREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.MULTIPLEMODELMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.NNNORMALIZATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.NOTRUECHILDSTRATEGY: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.OPTYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.OUTLIERTREATMENTMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.REGRESSIONNORMALIZATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.RESULTFEATURE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.RULEFEATURE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.SVMCLASSIFICATIONMETHOD: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.SVMREPRESENTATION: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMEANCHOR2: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMEEXCEPTIONTYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESALGORITHM: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.TIMESERIESUSAGE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.pmml.jaxbbindings.VALIDTIMESPEC: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.RevisionUtils.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.TechnicalInformation.Field: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.core.TechnicalInformation.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.filters.unsupervised.attribute.InterquartileRange.ValueType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.explorer.AttributeSelectionPanel.TestMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.explorer.ClassifierPanel.TestMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.explorer.ClustererPanel.TestMode: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.GUIChooser.GUIChooserMenuPlugin.Menu: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.knowledgeflow.MainKFPerspectiveToolBar.Widgets: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.scripting.event.ScriptExecutionEvent.Type: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.gui.scripting.SyntaxDocument.ATTR_TYPE: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.knowledgeflow.LoggingLevel: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.knowledgeflow.steps.FlowByExpression.ExpressionClause.ExpressionType: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum weka.Run.SchemeType: Returns an array containing the constants of this enum type, in the order they are declared.
valuesListTipText() - Method in class weka.datagenerators.clusterers.SubspaceClusterDefinition: Returns the tip text for this property
valueSparse(int) - Method in class weka.core.AbstractInstance: Returns an instance's attribute value in internal format, given an index in the sparse representation.
valueSparse(int) - Method in class weka.core.BinarySparseInstance: Returns an instance's attribute value in internal format.
valueSparse(int) - Method in interface weka.core.Instance: Returns an instance's attribute value in internal format, given an index in the sparse representation.
valueSparse(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseDouble(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseFloat(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseInt(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueSparseString(int) - Method in class weka.core.pmml.Array: Gets the value at indexOfIndex from the array.
valueString(int) - Method in class weka.core.pmml.Array: Gets the value at index from the array as a String.
VariableDeclarations - Interface in weka.core.expressionlanguage.core: Interface to expose variables to a program.
VariableDeclarationsCompositor - Class in weka.core.expressionlanguage.common: A helper class that allows to combine several variable declarations together.
VariableDeclarationsCompositor(VariableDeclarations...) - Constructor for class weka.core.expressionlanguage.common.VariableDeclarationsCompositor: Constructs a VariableDeclarationsCompositor containing the provided declarations
VariableInitializer() - Constructor for class weka.core.expressionlanguage.common.SimpleVariableDeclarations.VariableInitializer
variance(int) - Method in class weka.core.Instances: Computes the variance for a numeric attribute.
variance(Attribute) - Method in class weka.core.Instances: Computes the variance for a numeric attribute.
variance(double[]) - Static method in class weka.core.Utils: Computes the variance for an array of doubles.
varianceCoveredTipText() - Method in class weka.attributeSelection.PrincipalComponents: Returns the tip text for this property
varianceCoveredTipText() - Method in class weka.filters.unsupervised.attribute.PrincipalComponents: Returns the tip text for this property.
variances() - Method in class weka.core.Instances: Computes the variance for all numeric attributes simultaneously.
VaryNode - Class in weka.classifiers.bayes.net: Part of ADTree implementation.
VaryNode(int) - Constructor for class weka.classifiers.bayes.net.VaryNode: Creates new VaryNode
VectorDictionary - Class in weka.core.pmml.jaxbbindings: Java class for VectorDictionary element declaration.
VectorDictionary() - Constructor for class weka.core.pmml.jaxbbindings.VectorDictionary
VectorDictionary - Class in weka.core.pmml: Class encapsulating the PMML VectorDictionary construct.
VectorDictionary(Element, MiningSchema) - Constructor for class weka.core.pmml.VectorDictionary: Constructor.
VectorFields - Class in weka.core.pmml.jaxbbindings: Java class for VectorFields element declaration.
VectorFields() - Constructor for class weka.core.pmml.jaxbbindings.VectorFields
VectorInstance - Class in weka.core.pmml.jaxbbindings: Java class for VectorInstance element declaration.
VectorInstance() - Constructor for class weka.core.pmml.jaxbbindings.VectorInstance
VectorInstance - Class in weka.core.pmml: Class encapsulating a PMML VectorInstance construct
VectorInstance(Array, List<FieldRef>) - Constructor for class weka.core.pmml.VectorInstance: Constructor
VectorInstance(Element, List<FieldRef>) - Constructor for class weka.core.pmml.VectorInstance: Constructor
vectorizeBatch(Instances, boolean) - Method in class weka.core.DictionaryBuilder: Convert a batch of instances
vectorizeInstance(Instance) - Method in class weka.core.DictionaryBuilder: Convert an input instance.
vectorizeInstance(Instance, boolean) - Method in class weka.core.DictionaryBuilder: Convert an input instance.
VERBOSE - Static variable in class weka.core.ClassCache: whether to output some debug information.
VERBOSE - Static variable in class weka.core.ClassDiscovery: whether to output some debug information.
VERBOSE - Static variable in class weka.gui.GenericPropertiesCreator: whether to output some debug information
verboseTipText() - Method in class weka.associations.Apriori: Returns the tip text for this property
VerificationField - Class in weka.core.pmml.jaxbbindings: Java class for VerificationField element declaration.
VerificationField() - Constructor for class weka.core.pmml.jaxbbindings.VerificationField
VerificationFields - Class in weka.core.pmml.jaxbbindings: Java class for VerificationFields element declaration.
VerificationFields() - Constructor for class weka.core.pmml.jaxbbindings.VerificationFields
Version - Class in weka.core: This class contains the version number of the current WEKA release and some methods for comparing another version string.
Version() - Constructor for class weka.core.Version
VERSION - Static variable in class weka.core.Version: the complete version
VERSION_FILE - Static variable in class weka.core.Version: the version file
VERSION_KEY - Static variable in class weka.core.packageManagement.VersionPackageConstraint: The meta data key for the version number
VERSION_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for version info
VersionPackageConstraint - Class in weka.core.packageManagement: Concrete implementation of PackageConstraint that encapsulates constraints related to version numbers.
VersionPackageConstraint(Package) - Constructor for class weka.core.packageManagement.VersionPackageConstraint
VersionPackageConstraint.VersionComparison - Enum in weka.core.packageManagement: Enumeration encapsulating version comparison operations
VersionRangePackageConstraint - Class in weka.core.packageManagement: A concrete implementation of PackgageConstraint that encapsulates ranged version number constraints.
VersionRangePackageConstraint(Package) - Constructor for class weka.core.packageManagement.VersionRangePackageConstraint: Constructor
ViewerDialog - Class in weka.gui: A downsized version of the ArffViewer, displaying only one Instances-Object.
ViewerDialog(Frame) - Constructor for class weka.gui.ViewerDialog: initializes the dialog with the given parent
Visible - Interface in weka.gui.beans: Interface to something that has a visible (via BeanVisual) reprentation
VISIBLE_PERSPECTIVES_KEY - Static variable in class weka.gui.PerspectiveManager: Settings key for visible perspectives in an application
VisibleLayout - Class in weka.gui.knowledgeflow: Panel that wraps a flow and makes it visible in the KnowledgeFlow, along with it's associated log panel
VisibleLayout(MainKFPerspective) - Constructor for class weka.gui.knowledgeflow.VisibleLayout: Constructor
VisualizableErrorEvent - Class in weka.gui.beans: Event encapsulating error information for a learning scheme that can be visualized in the DataVisualizer
VisualizableErrorEvent(Object, PlotData2D) - Constructor for class weka.gui.beans.VisualizableErrorEvent
VisualizableErrorListener - Interface in weka.gui.beans: Interface to something that can accept VisualizableErrorEvents
VisualizeDefaults() - Constructor for class weka.gui.visualize.VisualizeUtils.VisualizeDefaults: Constructor
VisualizePanel - Class in weka.gui.explorer: A slightly extended MatrixPanel for better support in the Explorer.
VisualizePanel() - Constructor for class weka.gui.explorer.VisualizePanel
VisualizePanel - Class in weka.gui.visualize: This panel allows the user to visualize a dataset (and if provided) a classifier's/clusterer's predictions in two dimensions.
VisualizePanel(VisualizePanelListener) - Constructor for class weka.gui.visualize.VisualizePanel: This constructor allows a VisualizePanelListener to be set.
VisualizePanel() - Constructor for class weka.gui.visualize.VisualizePanel: Constructor
VisualizePanel.ScatterDefaults - Class in weka.gui.explorer: Default settings specific to the MatrixPanel that provides the scatter plot matrix
VisualizePanelEvent - Class in weka.gui.visualize: This event Is fired to a listeners 'userDataEvent' function when The user on the VisualizePanel clicks submit.
VisualizePanelEvent(ArrayList<ArrayList<Double>>, Instances, Instances, int, int) - Constructor for class weka.gui.visualize.VisualizePanelEvent: This constructor creates the event with all the parameters set.
VisualizePanelListener - Interface in weka.gui.visualize: Interface implemented by a class that is interested in receiving submited shapes from a visualize panel.
VisualizePlugin - Interface in weka.gui.visualize.plugins: Interface implemented by classes loaded dynamically to visualize classifier results in the explorer.
VisualizeUtils - Class in weka.gui.visualize: This class contains utility routines for visualization
VisualizeUtils() - Constructor for class weka.gui.visualize.VisualizeUtils
VisualizeUtils.VisualizeDefaults - Class in weka.gui.visualize: Defaults for the 2D scatter plot and attribute bars
VLINE - Static variable in class weka.gui.visualize.VisualizePanelEvent
VM_VERSION_KEY - Static variable in class weka.core.WekaPackageManager: Package metadata key for JVM version.
vmVersionCheck(Package, PrintStream...) - Static method in class weka.core.WekaPackageManager: Checks the supplied package against the JVM version running Weka.
Vote - Class in weka.classifiers.meta: Class for combining classifiers.
Vote() - Constructor for class weka.classifiers.meta.Vote
VotedPerceptron - Class in weka.classifiers.functions: Implementation of the voted perceptron algorithm by Freund and Schapire.
VotedPerceptron() - Constructor for class weka.classifiers.functions.VotedPerceptron
voteFlagTipText() - Method in class weka.datagenerators.classifiers.classification.RDG1: Returns the tip text for this property

W

waitUntilFinished() - Method in class weka.gui.beans.FlowRunner: Waits until all flows have finished executing before returning
waitUntilFinished() - Method in interface weka.knowledgeflow.FlowExecutor: Block until all steps are no longer busy
waitUntilFinished() - Method in class weka.knowledgeflow.FlowRunner: Wait until all the steps are no longer busy
WARNING - Static variable in class weka.core.Debug: the log level Warning
wasCancelPressed() - Method in class weka.gui.GenericObjectEditor: True if the cancel button was used to close the editor.
wasStopped() - Method in interface weka.knowledgeflow.FlowExecutor: Returns true if execution was stopped via the stopProcessing() method
wasStopped() - Method in class weka.knowledgeflow.FlowRunner: Returns true if execution was stopped via the stopProcessing() method
weight() - Method in class weka.classifiers.evaluation.NominalPrediction: Gets the weight assigned to this prediction.
weight() - Method in class weka.classifiers.evaluation.NumericPrediction: Gets the weight assigned to this prediction.
weight() - Method in interface weka.classifiers.evaluation.Prediction: Gets the weight assigned to this prediction.
weight(Instance) - Method in class weka.classifiers.rules.part.ClassifierDecList: Returns the weight a rule assigns to an instance.
weight() - Method in class weka.core.AbstractInstance: Returns the instance's weight.
weight() - Method in class weka.core.Attribute: Returns the attribute's weight.
weight() - Method in interface weka.core.Instance: Returns the instance's weight.
WEIGHT - Static variable in class weka.core.json.JSONInstances: the weight attribute.
WEIGHT_INVERSE - Static variable in class weka.classifiers.lazy.IBk: weight by 1/distance.
WEIGHT_NONE - Static variable in class weka.classifiers.lazy.IBk: no weighting.
WEIGHT_SIMILARITY - Static variable in class weka.classifiers.lazy.IBk: weight by 1-distance.
weightByDistanceTipText() - Method in class weka.attributeSelection.ReliefFAttributeEval: Returns the tip text for this property
weightedAreaUnderPRC() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) AUPRC.
weightedAreaUnderPRC() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) AUPRC.
weightedAreaUnderROC() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) AUROC.
weightedAreaUnderROC() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) AUC.
WeightedAttributesHandler - Interface in weka.core: Interface to something that makes use of the information provided by attribute weights.
weightedFalseNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) false negative rate.
weightedFalseNegativeRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) false negative rate.
weightedFalsePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) false positive rate.
weightedFalsePositiveRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) false positive rate.
weightedFMeasure() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the macro weighted (by class size) average F-Measure.
weightedFMeasure() - Method in class weka.classifiers.Evaluation: Calculates the macro weighted (by class size) average F-Measure.
WeightedInstancesHandler - Interface in weka.core: Interface to something that makes use of the information provided by instance weights.
WeightedInstancesHandlerWrapper - Class in weka.classifiers.meta: Generic wrapper around any classifier to enable weighted instances support.
Uses resampling with weights if the base classifier is not implementing the weka.core.WeightedInstancesHandler interface and there are instance weights other 1.0 present.
WeightedInstancesHandlerWrapper() - Constructor for class weka.classifiers.meta.WeightedInstancesHandlerWrapper
weightedMatthewsCorrelation() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) matthews correlation coefficient.
weightedMatthewsCorrelation() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) matthews correlation coefficient.
weightedPrecision() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) precision.
weightedPrecision() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) precision.
weightedRecall() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) recall.
weightedRecall() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) recall.
weightedTrueNegativeRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) true negative rate.
weightedTrueNegativeRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) true negative rate.
weightedTruePositiveRate() - Method in class weka.classifiers.evaluation.Evaluation: Calculates the weighted (by class size) true positive rate.
weightedTruePositiveRate() - Method in class weka.classifiers.Evaluation: Calculates the weighted (by class size) true positive rate.
weightingKernelTipText() - Method in class weka.classifiers.lazy.LWL: Returns the tip text for this property.
WeightMass - Class in weka.classifiers.trees.ht: Simple container for a weight
WeightMass() - Constructor for class weka.classifiers.trees.ht.WeightMass
weights(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.C45Split: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns weights if instance is assigned to more than one subset.
weights(Instance) - Method in class weka.classifiers.trees.j48.NoSplit: Always returns null because there is only one subset.
weights(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit: Method not in use
weightThresholdTipText() - Method in class weka.classifiers.meta.AdaBoostM1: Returns the tip text for this property
weightThresholdTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property
weightTipText() - Method in class weka.filters.unsupervised.attribute.Add: Returns the tip text for this property.
weightTrimBetaTipText() - Method in class weka.classifiers.functions.SimpleLogistic: Returns the tip text for this property
weightTrimBetaTipText() - Method in class weka.classifiers.trees.LMT: Returns the tip text for this property
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralConnection: Call this to get the weight value on a particular connection.
weightValue(int) - Method in class weka.classifiers.functions.neural.NeuralNode: Call this to get the weight value on a particular connection.
weka - package weka
weka.associations - package weka.associations
weka.attributeSelection - package weka.attributeSelection
weka.classifiers - package weka.classifiers
weka.classifiers.bayes - package weka.classifiers.bayes
weka.classifiers.bayes.net - package weka.classifiers.bayes.net
weka.classifiers.bayes.net.estimate - package weka.classifiers.bayes.net.estimate
weka.classifiers.bayes.net.search - package weka.classifiers.bayes.net.search
weka.classifiers.bayes.net.search.ci - package weka.classifiers.bayes.net.search.ci
weka.classifiers.bayes.net.search.fixed - package weka.classifiers.bayes.net.search.fixed
weka.classifiers.bayes.net.search.global - package weka.classifiers.bayes.net.search.global
weka.classifiers.bayes.net.search.local - package weka.classifiers.bayes.net.search.local
weka.classifiers.evaluation - package weka.classifiers.evaluation
weka.classifiers.evaluation.output.prediction - package weka.classifiers.evaluation.output.prediction
weka.classifiers.functions - package weka.classifiers.functions
weka.classifiers.functions.neural - package weka.classifiers.functions.neural
weka.classifiers.functions.supportVector - package weka.classifiers.functions.supportVector
weka.classifiers.lazy - package weka.classifiers.lazy
weka.classifiers.lazy.kstar - package weka.classifiers.lazy.kstar
weka.classifiers.meta - package weka.classifiers.meta
weka.classifiers.misc - package weka.classifiers.misc
weka.classifiers.pmml.consumer - package weka.classifiers.pmml.consumer
weka.classifiers.pmml.producer - package weka.classifiers.pmml.producer
weka.classifiers.rules - package weka.classifiers.rules
weka.classifiers.rules.part - package weka.classifiers.rules.part
weka.classifiers.trees - package weka.classifiers.trees
weka.classifiers.trees.ht - package weka.classifiers.trees.ht
weka.classifiers.trees.j48 - package weka.classifiers.trees.j48
weka.classifiers.trees.lmt - package weka.classifiers.trees.lmt
weka.classifiers.trees.m5 - package weka.classifiers.trees.m5
weka.classifiers.xml - package weka.classifiers.xml
weka.clusterers - package weka.clusterers
weka.core - package weka.core
weka.core.converters - package weka.core.converters
weka.core.expressionlanguage - package weka.core.expressionlanguage: Package for a framework for simple, flexible and performant expression languages
weka.core.expressionlanguage.common - package weka.core.expressionlanguage.common
weka.core.expressionlanguage.core - package weka.core.expressionlanguage.core
weka.core.expressionlanguage.parser - package weka.core.expressionlanguage.parser
weka.core.expressionlanguage.weka - package weka.core.expressionlanguage.weka
weka.core.json - package weka.core.json
weka.core.logging - package weka.core.logging
weka.core.matrix - package weka.core.matrix
weka.core.metastore - package weka.core.metastore
weka.core.neighboursearch - package weka.core.neighboursearch
weka.core.neighboursearch.balltrees - package weka.core.neighboursearch.balltrees
weka.core.neighboursearch.covertrees - package weka.core.neighboursearch.covertrees
weka.core.neighboursearch.kdtrees - package weka.core.neighboursearch.kdtrees
weka.core.packageManagement - package weka.core.packageManagement
weka.core.pmml - package weka.core.pmml
weka.core.pmml.jaxbbindings - package weka.core.pmml.jaxbbindings
weka.core.scripting - package weka.core.scripting
weka.core.stemmers - package weka.core.stemmers
weka.core.stopwords - package weka.core.stopwords
weka.core.tokenizers - package weka.core.tokenizers
weka.core.xml - package weka.core.xml
weka.datagenerators - package weka.datagenerators
weka.datagenerators.classifiers.classification - package weka.datagenerators.classifiers.classification
weka.datagenerators.classifiers.regression - package weka.datagenerators.classifiers.regression
weka.datagenerators.clusterers - package weka.datagenerators.clusterers
weka.estimators - package weka.estimators
weka.experiment - package weka.experiment
weka.experiment.xml - package weka.experiment.xml
weka.filters - package weka.filters
weka.filters.supervised.attribute - package weka.filters.supervised.attribute
weka.filters.supervised.instance - package weka.filters.supervised.instance
weka.filters.unsupervised.attribute - package weka.filters.unsupervised.attribute
weka.filters.unsupervised.instance - package weka.filters.unsupervised.instance
weka.gui - package weka.gui
weka.gui.arffviewer - package weka.gui.arffviewer
weka.gui.beans - package weka.gui.beans
weka.gui.beans.xml - package weka.gui.beans.xml
weka.gui.boundaryvisualizer - package weka.gui.boundaryvisualizer
weka.gui.experiment - package weka.gui.experiment
weka.gui.explorer - package weka.gui.explorer
weka.gui.filters - package weka.gui.filters
weka.gui.graphvisualizer - package weka.gui.graphvisualizer
weka.gui.hierarchyvisualizer - package weka.gui.hierarchyvisualizer
weka.gui.knowledgeflow - package weka.gui.knowledgeflow
weka.gui.knowledgeflow.steps - package weka.gui.knowledgeflow.steps
weka.gui.scripting - package weka.gui.scripting
weka.gui.scripting.event - package weka.gui.scripting.event
weka.gui.simplecli - package weka.gui.simplecli
weka.gui.sql - package weka.gui.sql
weka.gui.sql.event - package weka.gui.sql.event
weka.gui.streams - package weka.gui.streams
weka.gui.treevisualizer - package weka.gui.treevisualizer
weka.gui.visualize - package weka.gui.visualize
weka.gui.visualize.plugins - package weka.gui.visualize.plugins
weka.knowledgeflow - package weka.knowledgeflow
weka.knowledgeflow.steps - package weka.knowledgeflow.steps
WEKA_HOME - Static variable in class weka.core.WekaPackageManager: Default path to where Weka's configuration and packages are stored
WekaAlgorithmWrapper - Class in weka.knowledgeflow.steps: A step that wraps a class of standard Weka algorithm (e.g.
WekaAlgorithmWrapper() - Constructor for class weka.knowledgeflow.steps.WekaAlgorithmWrapper
WekaEnumeration<E> - Class in weka.core: Class for enumerating an array list's elements.
WekaEnumeration(List<E>) - Constructor for class weka.core.WekaEnumeration: Constructs an enumeration.
WekaEnumeration(List<E>, int) - Constructor for class weka.core.WekaEnumeration: Constructs an enumeration with a special element.
WekaException - Exception in weka.core: Class for Weka-specific exceptions.
WekaException() - Constructor for exception weka.core.WekaException: Creates a new WekaException with no message.
WekaException(String) - Constructor for exception weka.core.WekaException: Creates a new WekaException.
WekaException(String, Throwable) - Constructor for exception weka.core.WekaException: Constructor with message and cause
WekaException(Throwable) - Constructor for exception weka.core.WekaException: Constructor with cause argument
WekaFileChooser - Class in weka.gui: Customized WekaFileChooser with support for bookmarks.
WekaFileChooser() - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser pointing to the user's default directory.
WekaFileChooser(String) - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser using the given path.
WekaFileChooser(File) - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser using the given File as the path.
WekaFileChooser(FileSystemView) - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser using the given FileSystemView.
WekaFileChooser(File, FileSystemView) - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser using the given current directory and FileSystemView.
WekaFileChooser(String, FileSystemView) - Constructor for class weka.gui.WekaFileChooser: Constructs a WekaFileChooser using the given current directory path and FileSystemView.
WekaFileChooser.Factory - Class in weka.gui
WekaFileChooser.FileChooserBookmarksPanel - Class in weka.gui
WekaFileChooser.PropertiesHandler - Class in weka.gui
WekaOffscreenChartRenderer - Class in weka.gui.beans: Default OffscreenChartRenderer that uses Weka's built-in chart and graph classes.
WekaOffscreenChartRenderer() - Constructor for class weka.gui.beans.WekaOffscreenChartRenderer
WekaPackageClassLoaderManager - Class in weka.core: Class that manages classloaders from individual Weka plugin packages.
WekaPackageLibIsolatingClassLoader - Class in weka.core: A ClassLoader that loads/finds classes from one Weka plugin package.
WekaPackageLibIsolatingClassLoader(WekaPackageClassLoaderManager, File) - Constructor for class weka.core.WekaPackageLibIsolatingClassLoader: Constructor
WekaPackageManager - Class in weka.core: Class providing package management and manipulation routines.
WekaPackageManager() - Constructor for class weka.core.WekaPackageManager
wekaStaticWrapper(Sourcable, String) - Static method in class weka.classifiers.evaluation.Evaluation: Wraps a static classifier in enough source to test using the weka class libraries.
wekaStaticWrapper(Sourcable, String) - Static method in class weka.classifiers.Evaluation: Wraps a static classifier in enough source to test using the weka class libraries.
wekaStaticWrapper(Sourcable, String, Instances, Instances) - Static method in class weka.filters.Filter: generates source code from the filter
WekaTaskMonitor - Class in weka.gui: This panel records the number of weka tasks running and displays a simple bird animation while their are active tasks
WekaTaskMonitor() - Constructor for class weka.gui.WekaTaskMonitor: Constructor
WekaWrapper - Interface in weka.gui.beans: Interface to something that can wrap around a class of Weka algorithms (classifiers, filters etc).
WEST_CONNECTOR - Static variable in class weka.gui.beans.BeanVisual
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.BinC45Split: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.C45Split: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.ClassifierSplitModel: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeNoSplit: Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NBTreeSplit: Returns index of subset instance is assigned to.
whichSubset(Instance) - Method in class weka.classifiers.trees.j48.NoSplit: Always returns 0 because only there is only one subset.
whichSubset(Instance) - Method in class weka.classifiers.trees.lmt.ResidualSplit
WideComboBox() - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
WideComboBox(Object[]) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
WideComboBox(Vector<Object>) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
WideComboBox(ComboBoxModel) - Constructor for class weka.gui.beans.EnvironmentField.WideComboBox: Deprecated.
WideComboBox() - Constructor for class weka.gui.EnvironmentField.WideComboBox
WideComboBox(Object[]) - Constructor for class weka.gui.EnvironmentField.WideComboBox
WideComboBox(Vector<Object>) - Constructor for class weka.gui.EnvironmentField.WideComboBox
WideComboBox(ComboBoxModel) - Constructor for class weka.gui.EnvironmentField.WideComboBox
width() - Method in class weka.core.matrix.ExponentialFormat
width() - Method in class weka.core.matrix.FlexibleDecimalFormat
width() - Method in class weka.core.matrix.FloatingPointFormat
WIDTH - Static variable in class weka.core.neighboursearch.KDTree: The index of WIDTH (MAX-MIN) value in attributes' range array.
WIDTH - Static variable in class weka.core.neighboursearch.kdtrees.KDTreeNodeSplitter: Index of width value (max-min) in an array of attributes' range.
WIDTH - Static variable in class weka.gui.arffviewer.ArffViewerMainPanel: default width
WIDTH - Static variable in class weka.gui.sql.SqlViewer: the width property in the history file.
WIN_STRING - Variable in class weka.experiment.ResultMatrix: win string.
windowActivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is activated
windowClosed(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is closed
windowClosing(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is in the process of closing
windowDeactivated(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is deactivated
windowDeiconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is deiconified
windowIconified(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is iconified
windowListChanged() - Method in class weka.gui.Main: is called when window list changed somehow (add or remove).
windowOpened(WindowEvent) - Method in class weka.gui.arffviewer.ArffViewer: invoked when a window is has been opened
windowSizeTipText() - Method in class weka.classifiers.lazy.IBk: Returns the tip text for this property.
withClass() - Method in class weka.classifiers.evaluation.Evaluation: Gets the weight of the instances that had a non-missing class value
WITHIN_BATCH - Static variable in class weka.gui.beans.IncrementalClassifierEvent
WordsFromFile - Class in weka.core.stopwords: Uses the stopwords located in the specified file (ignored _if pointing to a directory).
WordsFromFile() - Constructor for class weka.core.stopwords.WordsFromFile
wordsToKeepTipText() - Method in class weka.core.DictionaryBuilder: Returns the tip text for this property.
wordsToKeepTipText() - Method in class weka.filters.unsupervised.attribute.StringToWordVector: Returns the tip text for this property.
WordTokenizer - Class in weka.core.tokenizers: A simple tokenizer that is using the java.util.StringTokenizer class to tokenize the strings.
WordTokenizer() - Constructor for class weka.core.tokenizers.WordTokenizer
Workbench - Class in weka.gui: Launcher class for the Weka workbench.
Workbench() - Constructor for class weka.gui.Workbench
WorkbenchApp - Class in weka.gui: One app to rule them all, one app to find them, one app to bring them all and with perspectives bind them.
WorkbenchApp() - Constructor for class weka.gui.WorkbenchApp: Constructor
WorkbenchDefaults - Class in weka.gui: Default settings for the Workbench app.
WorkbenchDefaults() - Constructor for class weka.gui.WorkbenchDefaults: Constructor
WrapLayout - Class in weka.gui: FlowLayout subclass that fully supports wrapping of components.
WrapLayout() - Constructor for class weka.gui.WrapLayout: Constructs a new WrapLayout with a left alignment and a default 5-unit horizontal and vertical gap.
WrapLayout(int) - Constructor for class weka.gui.WrapLayout: Constructs a new FlowLayout with the specified alignment and a default 5-unit horizontal and vertical gap.
WrapLayout(int, int, int) - Constructor for class weka.gui.WrapLayout: Creates a new flow layout manager with the indicated alignment and the indicated horizontal and vertical gaps.
WrapperSubsetEval - Class in weka.attributeSelection: WrapperSubsetEval:

Evaluates attribute sets by using a learning scheme.
WrapperSubsetEval() - Constructor for class weka.attributeSelection.WrapperSubsetEval: Constructor.
write(Writer) - Method in class weka.classifiers.CostMatrix: Writes out a matrix.
write(Instances) - Method in class weka.core.converters.ConverterUtils.DataSink: writes the given data either via the saver or to the defined output stream (depending on the constructor).
write(String, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data to the given file.
write(Saver, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data via the given saver.
write(OutputStream, Instances) - Static method in class weka.core.converters.ConverterUtils.DataSink: writes the data to the given stream (always in ARFF format).
write(int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Writes the byte to the stream.
write(byte[]) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Writes the bytes to the stream.
write(byte[], int, int) - Method in class weka.core.logging.OutputLogger.OutputPrintStream: Writes the bytes to the stream.
write(Writer) - Method in class weka.core.matrix.Matrix: Writes out a matrix.
write(Writer) - Method in class weka.core.Matrix: Deprecated.

Writes out a matrix.
write(String, Object) - Static method in class weka.core.SerializationHelper: serializes the given object to the specified file.
write(OutputStream, Object) - Static method in class weka.core.SerializationHelper: serializes the given object to the specified stream.
write(String) - Method in class weka.core.Stopwords: Writes the current stopwords to the given file
write(File) - Method in class weka.core.Stopwords: Writes the current stopwords to the given file
write(BufferedWriter) - Method in class weka.core.Stopwords: Writes the current stopwords to the given writer.
write(byte[], int, int) - Method in class weka.core.Tee: Writes len bytes from the specified byte array starting at offset off to this stream.
write(int) - Method in class weka.core.Tee: Writes the specified byte to this stream.
write(byte[]) - Method in class weka.core.Tee: Writes b.length bytes to this output stream.
write(String, Object) - Static method in class weka.core.xml.KOML: writes the XML-serialized object to the given file
write(File, Object) - Static method in class weka.core.xml.KOML: write the XML-serialized object to the given file
write(OutputStream, Object) - Static method in class weka.core.xml.KOML: writes the XML-serialized object to a stream
write(String) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given file.
write(File) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given file.
write(OutputStream) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given stream.
write(Writer) - Method in class weka.core.xml.XMLDocument: writes the current DOM document into the given writer.
write(String, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the file
write(File, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the file
write(OutputStream, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the stream
write(Writer, Object) - Method in class weka.core.xml.XMLSerialization: writes the given object into the writer
write() - Method in class weka.core.xml.XMLSerializationMethodHandler: returns the handler for write methods
write(String, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given file
write(File, Object) - Static method in class weka.core.xml.XStream: write the XML-serialized object to the given file
write(OutputStream, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given output stream
write(Writer, Object) - Static method in class weka.core.xml.XStream: writes the XML-serialized object to the given Writer.
write(String, Experiment) - Static method in class weka.experiment.Experiment: Writes the experiment to disk.
writeAll(String, Object[]) - Static method in class weka.core.SerializationHelper: serializes the given objects to the specified file.
writeAll(OutputStream, Object[]) - Static method in class weka.core.SerializationHelper: serializes the given objects to the specified stream.
writeBatch() - Method in class weka.core.converters.AbstractSaver: Writes to a file in batch mode To be overridden.
writeBatch() - Method in class weka.core.converters.ArffSaver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.C45Saver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.CSVSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.DatabaseSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.DictionarySaver
writeBatch() - Method in class weka.core.converters.JSONSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.LibSVMSaver: Writes a Batch of instances
writeBatch() - Method in class weka.core.converters.MatlabSaver: Writes a Batch of instances.
writeBatch() - Method in interface weka.core.converters.Saver: Writes to a destination in batch mode
writeBatch() - Method in class weka.core.converters.SerializedInstancesSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.SVMLightSaver: Writes a Batch of instances.
writeBatch() - Method in class weka.core.converters.XRFFSaver: Writes a Batch of instances
writeBeanConnection(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanConncetion to a DOM structure.
writeBeanInstance(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanInstance to a DOM structure.
writeBeanLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Loader (a bean) to a DOM structure.
writeBeanSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Saver (a bean) to a DOM structure.
writeBeanVisual(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given BeanVisual to a DOM structure.
writeCollection(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Collection to a DOM structure.
writeColor(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Color to a DOM structure.
writeColor(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Color to a DOM structure.
writeColorUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given ColorUIResource to a DOM structure.
writeCostMatrix(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given CostMatrix to a DOM structure.
writeCostMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given CostMatrix (old) to a DOM structure.
writeCurve(String, Estimator, double, double, int) - Static method in class weka.estimators.EstimatorUtils: Output of an n points of a density curve.
writeCurve(String, Estimator, Estimator, double, double, double, int) - Static method in class weka.estimators.EstimatorUtils: Output of an n points of a density curve.
WriteDataToResult - Class in weka.knowledgeflow.steps: Step that stores incoming non-incremental data in the job environment
WriteDataToResult() - Constructor for class weka.knowledgeflow.steps.WriteDataToResult
writeDefaultListModel(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given DefaultListModel to a DOM structure.
writeDimension(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Dimension to a DOM structure.
writeDOT(String, String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Static method in class weka.gui.graphvisualizer.DotParser: This method saves a graph in a file in DOT format.
writeFlow(Flow, Writer) - Static method in class weka.knowledgeflow.JSONFlowUtils: Serializes the supplied flow to JSON and writes out using the supplied writer
writeFlow(Flow, OutputStream) - Static method in class weka.knowledgeflow.JSONFlowUtils: Serializes the supplied flow to JSON and writes out using the supplied output stream
writeFlow(Flow, File) - Static method in class weka.knowledgeflow.JSONFlowUtils: Serializes the supplied flow to JSON and writes it out to the supplied file
writeFont(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Font to a DOM structure.
writeFontUIResource(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given FontUIResource to a DOM structure.
writeIncremental(Instance) - Method in class weka.core.converters.AbstractSaver: Method for incremental saving.
writeIncremental(Instance) - Method in class weka.core.converters.ArffSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.C45Saver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.CSVSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.DatabaseSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.DictionarySaver
writeIncremental(Instance) - Method in class weka.core.converters.LibSVMSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in class weka.core.converters.MatlabSaver: Saves an instances incrementally.
writeIncremental(Instance) - Method in interface weka.core.converters.Saver: Writes to a destination in incremental mode.
writeIncremental(Instance) - Method in class weka.core.converters.SVMLightSaver: Saves an instances incrementally.
writeLoader(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Loader to a DOM structure.
writeMap(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Map to a DOM structure.
writeMatrix(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Matrix to a DOM structure.
writeMatrixOld(Element, Object, String) - Method in class weka.core.xml.XMLBasicSerialization: adds the given Matrix (old) to a DOM structure.
writeMetaBean(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given MetaBean to a DOM structure.
writePoint(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Point to a DOM structure.
writePropertyNode(Element, Object, String) - Method in class weka.experiment.xml.XMLExperiment: adds the given PropertyNode to a DOM structure.
writeSaver(Element, Object, String) - Method in class weka.gui.beans.xml.XMLBeans: adds the given Saver to a DOM structure.
writeToFile(String, Object) - Static method in class weka.core.Debug: Writes the given object to the specified file.
writeToFile(String, String) - Static method in class weka.core.Debug: Writes the given message to the specified file.
writeToFile(String, Object, boolean) - Static method in class weka.core.Debug: Writes the given object to the specified file.
writeToFile(String, String, boolean) - Static method in class weka.core.Debug: Writes the given message to the specified file.
writeToXML(Element, Object, String) - Method in class weka.core.xml.XMLSerialization: adds the given Object to a DOM structure.
WriteWekaLog - Class in weka.knowledgeflow.steps: Step that takes incoming data and writes it to the Weka log
WriteWekaLog() - Constructor for class weka.knowledgeflow.steps.WriteWekaLog
writeXMLBIF03(String, String, ArrayList<GraphNode>, ArrayList<GraphEdge>) - Static method in class weka.gui.graphvisualizer.BIFParser: This method writes a graph in XMLBIF ver.

X

x - Variable in class weka.gui.graphvisualizer.GraphNode: The x and y position of the node
X_SHAPE - Static variable in class weka.gui.visualize.Plot2D
XCoordinates - Class in weka.core.pmml.jaxbbindings: Java class for XCoordinates element declaration.
XCoordinates() - Constructor for class weka.core.pmml.jaxbbindings.XCoordinates
xLabelFreqTipText() - Method in class weka.gui.beans.StripChart: GUI Tip text
xLabelFreqTipText() - Method in class weka.knowledgeflow.steps.StripChart: GUI Tip text
xlogx(int) - Static method in class weka.core.Utils: Returns c*log2(c) for a given integer value c.
XML - Class in weka.classifiers.evaluation.output.prediction: Outputs the predictions in XML.

The following DTD is used:

<!DOCTYPE predictions
[
<!ELEMENT predictions (prediction*)>
<!ATTLIST predictions version CDATA "3.5.8">
<!ATTLIST predictions name CDATA #REQUIRED>

<!ELEMENT prediction ((actual_label,predicted_label,error,(prediction|distribution),attributes?)|(actual_value,predicted_value,error,attributes?))>
<!ATTLIST prediction index CDATA #REQUIRED>

<!ELEMENT actual_label ANY>
<!ATTLIST actual_label index CDATA #REQUIRED>
<!ELEMENT predicted_label ANY>
<!ATTLIST predicted_label index CDATA #REQUIRED>
<!ELEMENT error ANY>
<!ELEMENT prediction ANY>
<!ELEMENT distribution (class_label+)>
<!ELEMENT class_label ANY>
<!ATTLIST class_label index CDATA #REQUIRED>
<!ATTLIST class_label predicted (yes|no) "no">
<!ELEMENT actual_value ANY>
<!ELEMENT predicted_value ANY>
<!ELEMENT attributes (attribute+)>
<!ELEMENT attribute ANY>
<!ATTLIST attribute index CDATA #REQUIRED>
<!ATTLIST attribute name CDATA #REQUIRED>
<!ATTLIST attribute type (numeric|date|nominal|string|relational) #REQUIRED>
]
>
Valid options are:
XML() - Constructor for class weka.classifiers.evaluation.output.prediction.XML
XMLBasicSerialization - Class in weka.core.xml: This serializer contains some read/write methods for common classes that are not beans-conform.
XMLBasicSerialization() - Constructor for class weka.core.xml.XMLBasicSerialization: initializes the serialization
XMLBeans - Class in weka.gui.beans.xml: This class serializes and deserializes a KnowledgeFlow setup to and fro XML.
XMLBeans(JComponent, BeanContextSupport, int) - Constructor for class weka.gui.beans.xml.XMLBeans: initializes the serialization for layouts
XMLBeans(JComponent, BeanContextSupport, int, int) - Constructor for class weka.gui.beans.xml.XMLBeans: initializes the serialization for different types of data
XMLClassifier - Class in weka.classifiers.xml: This class serializes and deserializes a Classifier instance to and fro XML.
XMLClassifier() - Constructor for class weka.classifiers.xml.XMLClassifier: initializes the serialization
XMLDocument - Class in weka.core.xml: This class offers some methods for generating, reading and writing XML documents.
It can only handle UTF-8.
XMLDocument() - Constructor for class weka.core.xml.XMLDocument: initializes the factory with non-validating parser.
XMLDocument(String) - Constructor for class weka.core.xml.XMLDocument: Creates a new instance of XMLDocument.
XMLDocument(File) - Constructor for class weka.core.xml.XMLDocument: Creates a new instance of XMLDocument.
XMLDocument(InputStream) - Constructor for class weka.core.xml.XMLDocument: Creates a new instance of XMLDocument.
XMLDocument(Reader) - Constructor for class weka.core.xml.XMLDocument: Creates a new instance of XMLDocument.
XMLExperiment - Class in weka.experiment.xml: This class serializes and deserializes an Experiment instance to and fro XML.
It omits the options from the Experiment, since these are handled by the get/set-methods.
XMLExperiment() - Constructor for class weka.experiment.xml.XMLExperiment: initializes the serialization
XMLFileBasedMetaStore - Class in weka.core.metastore: A simple default implementation of MetaStore that uses Weka's XML serialization mechanism to persist entries as XML files in ${WEKA_HOME}/wekaMetaStore
XMLFileBasedMetaStore() - Constructor for class weka.core.metastore.XMLFileBasedMetaStore
XMLInstances - Class in weka.core.xml: XML representation of the Instances class.
XMLInstances() - Constructor for class weka.core.xml.XMLInstances: the default constructor
XMLInstances(Instances) - Constructor for class weka.core.xml.XMLInstances: generates the XML structure based on the given data
XMLInstances(Reader) - Constructor for class weka.core.xml.XMLInstances: generates the Instances directly from the reader containing the XML data.
XMLOptions - Class in weka.core.xml: A class for transforming options listed in XML to a regular WEKA command line string.
XMLOptions() - Constructor for class weka.core.xml.XMLOptions: Creates a new instance of XMLOptions.
XMLOptions(String) - Constructor for class weka.core.xml.XMLOptions: Creates a new instance of XMLOptions.
XMLOptions(File) - Constructor for class weka.core.xml.XMLOptions: Creates a new instance of XMLOptions.
XMLOptions(InputStream) - Constructor for class weka.core.xml.XMLOptions: Creates a new instance of XMLOptions.
XMLOptions(Reader) - Constructor for class weka.core.xml.XMLOptions: Creates a new instance of XMLOptions.
XMLSerialization - Class in weka.core.xml: With this class objects can be serialized to XML instead into a binary format.
XMLSerialization() - Constructor for class weka.core.xml.XMLSerialization: initializes the serialization
XMLSerializationMethodHandler - Class in weka.core.xml: This class handles relationships between display names of properties (or classes) and Methods that are associated with them.
XMLSerializationMethodHandler(Object) - Constructor for class weka.core.xml.XMLSerializationMethodHandler: initializes the method handling, executes also clear(), which adds initial methods automatically.
XRFFLoader - Class in weka.core.converters: Reads a source that is in the XML version of the ARFF format.
XRFFLoader() - Constructor for class weka.core.converters.XRFFLoader
XRFFSaver - Class in weka.core.converters: Writes to a destination that is in the XML version of the ARFF format.
XRFFSaver() - Constructor for class weka.core.converters.XRFFSaver: Constructor
xStats - Variable in class weka.experiment.PairedStats: The stats associated with the data in column 1
XStream - Class in weka.core.xml: This class is a helper class for XML serialization using XStream .
XStream() - Constructor for class weka.core.xml.XStream
XSTREAM - Static variable in class weka.gui.beans.SerializedModelSaver
xySum - Variable in class weka.experiment.PairedStats: The sum of the products

Y

y - Variable in class weka.gui.graphvisualizer.GraphNode: The x and y position of the node
YCoordinates - Class in weka.core.pmml.jaxbbindings: Java class for YCoordinates element declaration.
YCoordinates() - Constructor for class weka.core.pmml.jaxbbindings.YCoordinates
YongSplitInfo - Class in weka.classifiers.trees.m5: Stores split information.
YongSplitInfo(int, int, int) - Constructor for class weka.classifiers.trees.m5.YongSplitInfo: Constructs an object which contains the split information
yStats - Variable in class weka.experiment.PairedStats: The stats associated with the data in column 2
yyatEOF() - Method in class weka.core.expressionlanguage.parser.Scanner: Returns whether the scanner has reached the end of the reader it reads from.
yyatEOF() - Method in class weka.core.json.Scanner: Returns whether the scanner has reached the end of the reader it reads from.
yybegin(int) - Method in class weka.core.expressionlanguage.parser.Scanner: Enters a new lexical state.
yybegin(int) - Method in class weka.core.json.Scanner: Enters a new lexical state.
yycharat(int) - Method in class weka.core.expressionlanguage.parser.Scanner: Returns the character at the given position from the matched text.
yycharat(int) - Method in class weka.core.json.Scanner: Returns the character at the given position from the matched text.
yyclose() - Method in class weka.core.expressionlanguage.parser.Scanner: Closes the input reader.
yyclose() - Method in class weka.core.json.Scanner: Closes the input reader.
YYEOF - Static variable in class weka.core.expressionlanguage.parser.Scanner: This character denotes the end of file.
YYEOF - Static variable in class weka.core.json.Scanner: This character denotes the end of file.
YYINITIAL - Static variable in class weka.core.expressionlanguage.parser.Scanner
YYINITIAL - Static variable in class weka.core.json.Scanner
yylength() - Method in class weka.core.expressionlanguage.parser.Scanner: How many characters were matched.
yylength() - Method in class weka.core.json.Scanner: How many characters were matched.
yypushback(int) - Method in class weka.core.expressionlanguage.parser.Scanner: Pushes the specified amount of characters back into the input stream.
yypushback(int) - Method in class weka.core.json.Scanner: Pushes the specified amount of characters back into the input stream.
yyreset(Reader) - Method in class weka.core.expressionlanguage.parser.Scanner: Resets the scanner to read from a new input stream.
yyreset(Reader) - Method in class weka.core.json.Scanner: Resets the scanner to read from a new input stream.
yystate() - Method in class weka.core.expressionlanguage.parser.Scanner: Returns the current lexical state.
yystate() - Method in class weka.core.json.Scanner: Returns the current lexical state.
yytext() - Method in class weka.core.expressionlanguage.parser.Scanner: Returns the text matched by the current regular expression.
yytext() - Method in class weka.core.json.Scanner: Returns the text matched by the current regular expression.

Z

ZeroR - Class in weka.classifiers.rules: Class for building and using a 0-R classifier.
ZeroR() - Constructor for class weka.classifiers.rules.ZeroR
zipit(String, String) - Method in class weka.experiment.OutputZipper: Saves a string to either an individual gzipped file or as an entry in a zip file.
ZMaxTipText() - Method in class weka.classifiers.meta.LogitBoost: Returns the tip text for this property

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z