A B C D E F G H I J L M O P R S T U V W

A

AbstractForecaster - Class in weka.classifiers.timeseries

Abstract base class implementing TSForecaster that concrete subclasses can extend.

AbstractForecaster() - Constructor for class weka.classifiers.timeseries.AbstractForecaster

AbstractTimeSeriesFilter - Class in weka.classifiers.timeseries.core

Re-written version of weka.filters.unsupervised.attribute.AbstractTimeSeriesFilter that adds new methods and uses java.utils collection classes.

AbstractTimeSeriesFilter() - Constructor for class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

acceptDataSet(DataSetEvent) - Method in class weka.gui.beans.TimeSeriesForecasting

Accept an incoming data set

acceptForecaster(WekaForecaster, Instances) - Method in interface weka.gui.knowledgeflow.TimeSeriesPerspective.TimeSeriesModelListener

acceptInstance(InstanceEvent) - Method in class weka.gui.beans.TimeSeriesForecasting

Accept an incoming instance

acceptsInstances() - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Returns true if this perspective accepts instances

acceptsInstances() - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

Returns true, as this panel sends instances into the python environment

addCustomPeriodic(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Add a custom date-derived periodic attribute

addCustomPeriodic(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

Add a custom date-derived periodic

addInstanceListener(InstanceListener) - Method in class weka.gui.beans.TimeSeriesForecasting

Add an listener to be notified of outgoing InstanceEvents

addPropertyChangeListener(PropertyChangeListener) - Method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Adds a PropertyChangeListener who will be notified of value changes.

AdvancedConfigPanel - Class in weka.classifiers.timeseries.gui

AdvancedConfigPanel(SimpleConfigPanel, boolean) - Constructor for class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Constructor

AdvancedConfigPanel(SimpleConfigPanel) - Constructor for class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Constructor

advanceSuppliedTimeValue(double, TSLagMaker.PeriodicityHandler) - Static method in class weka.classifiers.timeseries.core.Utils

Utility method to advance a supplied time value by one unit.

advanceSuppliedTimeValue(double) - Method in class weka.filters.supervised.attribute.TSLagMaker

Utility method to advance a supplied time value by one unit according to the periodicity set for this LagMaker.

applyToEvaluation(TSEvaluation, WekaForecaster) - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Apply the configuration defined in this panel to the supplied evaluation object

applyToEvaluation(TSEvaluation, WekaForecaster) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Apply the selected settings of this panel to the supplied evaluation module with respect to the supplied forecaster

applyToForecaster(WekaForecaster) - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Apply the configuration defined in this panel to the supplied forecaster

applyToForecaster(WekaForecaster) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Apply the selected settings of this panel to the supplied WekaForecaster.

attributeIndicesTipText() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Returns the tip text for this property

B

baseModelHasSerializer() - Method in interface weka.classifiers.timeseries.TSForecaster

Check whether the base learner requires special serialization

baseModelHasSerializer() - Method in class weka.classifiers.timeseries.WekaForecaster

Check whether the base learner requires special serialization

BaseModelSerializer - Interface in weka.classifiers.timeseries.core

An interface for predictors which implement methods for serializing the base model.

batchFinished() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Signifies that this batch of input to the filter is finished.

batchFinished() - Method in class weka.filters.supervised.attribute.TSLagMaker

buildClassifier(Instances) - Method in class weka.classifiers.timeseries.HoltWinters

buildForecaster(Instances, PrintStream...) - Method in class weka.classifiers.timeseries.AbstractForecaster

Builds a new forecasting model using the supplied training data.

buildForecaster(Instances, PrintStream...) - Method in interface weka.classifiers.timeseries.TSForecaster

Builds a new forecasting model using the supplied training data.

buildForecaster(Instances, PrintStream...) - Method in class weka.classifiers.timeseries.WekaForecaster

Builds a new forecasting model using the supplied training data.

C

calculateConfidenceOffsets(TSForecaster, Instances, int, int, double, PrintStream...) - Method in class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

Computes confidence intervals using the supplied forecster and training data.

calculateConfidenceOffsets(TSForecaster, Instances, int, int, int, double, PrintStream...) - Method in class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

Computes confidence intervals using the supplied forecaster and training data.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.DACModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.MAEModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.MAPEModule

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.MSEModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.RAEModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.RMSEModule

Calculate the measure that this module represents.

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.RRSEModule

calculateMeasure() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Calculate the measure that this module represents.

classifyInstance(Instance) - Method in class weka.classifiers.timeseries.HoltWinters

clearCustomPeriodics() - Method in class weka.classifiers.timeseries.WekaForecaster

clear the list of custom date-derived periodic attributes

clearCustomPeriodics() - Method in class weka.filters.supervised.attribute.TSLagMaker

Clear all custom date-derived periodic fields.

clearLagHistories() - Method in class weka.filters.supervised.attribute.TSLagMaker

Clears any history accumulated in the lag creating filters.

clearPreviousState() - Method in interface weka.classifiers.timeseries.core.StateDependentPredictor

Clear/reset state of the model.

clearPreviousState() - Method in interface weka.classifiers.timeseries.TSForecaster

Reset model state.

clearPreviousState() - Method in class weka.classifiers.timeseries.WekaForecaster

Reset model state.

ConfidenceIntervalForecaster - Interface in weka.classifiers.timeseries.core

Interface to a forecaster that can compute confidence intervals for its forecasts

connectionAllowed(EventSetDescriptor) - Method in class weka.gui.beans.TimeSeriesForecasting

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.TimeSeriesForecasting

Returns true if, at this time, the object will accept a connection with respect to the named event

connectionNotification(String, Object) - Method in class weka.gui.beans.TimeSeriesForecasting

Notify this object that it has been registered as a listener with a source with respect to the named event

countsForTargets() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Gets the number of predicted, actual pairs for each target.

createTimeLagCrossProducts(Instances) - Method in class weka.filters.supervised.attribute.TSLagMaker

customizerClosing() - Method in class weka.gui.beans.TimeSeriesForecastingCustomizer

Called when the window containing the customizer is closed

CustomPeriodicEditor - Class in weka.classifiers.timeseries.gui

Provides a gui editor for a custom periodic test

CustomPeriodicEditor() - Constructor for class weka.classifiers.timeseries.gui.CustomPeriodicEditor

CustomPeriodicEditor(List<CustomPeriodicTest>) - Constructor for class weka.classifiers.timeseries.gui.CustomPeriodicEditor

Constructor

CustomPeriodicTest - Class in weka.classifiers.timeseries.core

Class that evaluates a supplied date against user-specified date constant fields.

CustomPeriodicTest(String) - Constructor for class weka.classifiers.timeseries.core.CustomPeriodicTest

Constructor.

CustomPeriodicTest.Operator - Enum in weka.classifiers.timeseries.core

Enum defining inequality operations

CustomPeriodicTest.TestPart - Class in weka.classifiers.timeseries.core

Inner class defining one boundary of an interval

CustomPeriodicTest.TestPart() - Constructor for class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

CustomPeriodicTestEditor - Class in weka.classifiers.timeseries.gui

Provides an editor for a single interval from a custom periodic test.

CustomPeriodicTestEditor(boolean) - Constructor for class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Constructor

D

DACModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the accuracy of the direction of forecasted values.

DACModule() - Constructor for class weka.classifiers.timeseries.eval.DACModule

dateInSkipList(Date) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Checks to see if the supplied date is in the list of time units to skip (i.e.

decrementSuppliedTimeValue(double, TSLagMaker.PeriodicityHandler) - Static method in class weka.classifiers.timeseries.core.Utils

Utility method to decrement a supplied time value by one unit.

decrementSuppliedTimeValue(double) - Method in class weka.filters.supervised.attribute.TSLagMaker

deltaTime() - Method in enum weka.filters.supervised.attribute.TSLagMaker.Periodicity

deltaTime() - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Get the delta time of the periodicity being managed

determinePeriodicity(Instances, String, TSLagMaker.Periodicity) - Static method in class weka.filters.supervised.attribute.TSLagMaker

Utility method that uses heuristics to identify the periodicity of the data with respect to a time stamp.

disconnectionNotification(String, Object) - Method in class weka.gui.beans.TimeSeriesForecasting

Notify this object that it has been deregistered as a listener with a source with respect to the supplied event name

E

enableDateDerivedPeriodics(boolean) - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Set the enabled/disabled status of date-derived periodic panel and its associated widgets.

encodeForecasterToBase64(WekaForecaster, Instances) - Static method in class weka.gui.beans.TimeSeriesForecasting

Encode the model and header into a base 64 string.

encodeForecasterToBase64(WekaForecaster, Instances) - Static method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Encode the model and header into a base 64 string.

ErrorBasedConfidenceIntervalEstimator - Class in weka.classifiers.timeseries.core

Class that computes confidence intervals for a time series forecaster using errors computed on the training data.

ErrorBasedConfidenceIntervalEstimator() - Constructor for class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

ErrorModule - Class in weka.classifiers.timeseries.eval

Superclass of error-based evaluation modules.

ErrorModule() - Constructor for class weka.classifiers.timeseries.eval.ErrorModule

eval(Date, CustomPeriodicTest.TestPart) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Evaluate the supplied date against this bound.

evaluate(Date) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Evaluate the supplied date with respect to this custom periodic test interval

evaluateForecaster(TSForecaster, PrintStream...) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Evaluate the supplied forecaster.

evaluateForecaster(TSForecaster, boolean, PrintStream...) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Evaluate a forecaster on training and/or test data.

evaluateForecaster(TSForecaster, String[]) - Static method in class weka.classifiers.timeseries.eval.TSEvaluation

Evaluate the supplied forecaster using the supplied command-line options.

evaluateForInstance(List<NumericPrediction>, Instance) - Method in class weka.classifiers.timeseries.eval.DACModule

Evaluate the given forecast(s) with respect to the given test instance.

evaluateForInstance(List<NumericPrediction>, Instance) - Method in class weka.classifiers.timeseries.eval.ErrorModule

Evaluate the given forecast(s) with respect to the given test instance.

evaluateForInstance(List<NumericPrediction>, Instance) - Method in class weka.classifiers.timeseries.eval.RAEModule

Evaluate the given forecast(s) with respect to the given test instance.

evaluateForInstance(List<NumericPrediction>, Instance) - Method in class weka.classifiers.timeseries.eval.RRSEModule

Evaluate the given forecast(s) with respect to the given test instance.

evaluateForInstance(List<NumericPrediction>, Instance) - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Evaluate the given forecast(s) with respect to the given test instance.

eventGeneratable(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Returns true, if at the current time, the named event could be generated.

excludeSeasonalCorrectionTipText() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

excludeTrendCorrection() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

ExplorerTSPanel - Class in weka.classifiers.timeseries.gui.explorer

GUI class that provides a time series forecasting plugin tab for the Weka Explorer.

ExplorerTSPanel() - Constructor for class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Constructor

F

fillWithMissingTipText() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Returns the tip text for this property

forecast(int, PrintStream...) - Method in class weka.classifiers.timeseries.AbstractForecaster

Produce a forecast for the target field(s).

forecast(int, Instances, PrintStream...) - Method in interface weka.classifiers.timeseries.core.OverlayForecaster

Produce a forecast for the target field(s).

forecast() - Method in class weka.classifiers.timeseries.HoltWinters

Generates a one-step ahead forecast.

forecast(int, PrintStream...) - Method in interface weka.classifiers.timeseries.TSForecaster

Produce a forecast for the target field(s).

forecast(int, PrintStream...) - Method in class weka.classifiers.timeseries.WekaForecaster

Produce a forecast for the target field(s).

forecast(int, Instances, PrintStream...) - Method in class weka.classifiers.timeseries.WekaForecaster

Produce a forecast for the target field(s).

ForecastingPanel - Class in weka.classifiers.timeseries.gui

Main GUI panel for the forecasting environment.

ForecastingPanel(LogPanel, boolean) - Constructor for class weka.classifiers.timeseries.gui.ForecastingPanel

Constructor.

ForecastingPanel(LogPanel, boolean, boolean, boolean) - Constructor for class weka.classifiers.timeseries.gui.ForecastingPanel

Constructor

G

getAddAMIndicator() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return true if an AM indicator attribute is to be created.

getAddDayOfMonth() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return true if a day of the month attribute is to be created.

getAddDayOfWeek() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return true if a day of the week attribute is to be created.

getAddMonthOfYear() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if a month of the year attribute is to be created.

getAddNumDaysInMonth() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return true if a num days in the month attribute is to be created.

getAddQuarterOfYear() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if a quarter attribute is to be created.

getAddWeekendIndicator() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if a weekend indicator attribute is to be created.

getAdjustForTrends() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if we are adjusting for trends via a real or artificial time stamp.

getAdjustForVariance() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if we are adjusting for variance by taking the log of the target(s).

getAlgorithmName() - Method in interface weka.classifiers.timeseries.TSForecaster

Provides a short name that describes the underlying algorithm in some way.

getAlgorithmName() - Method in class weka.classifiers.timeseries.WekaForecaster

Provides a short name that describes the underlying algorithm in some way.

getArtificialTimeStartOffset() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the offset, from the value associated with the last training instance, for the artificial time stamp.

getArtificialTimeStartOffset() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the offset, from the value associated with the last training instance, for the artificial time stamp.

getArtificialTimeStartValue() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns the current value of the artificial time stamp.

getAttributeIndices() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Get the current range selection

getAverageConsecutiveLongLags() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if consecutive long lagged variables are to be averaged.

getAverageLagsAfter() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return the point after which long lagged variables will be averaged.

getBaseClassifier() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Get the underlying Weka classifier that will be used to make the predictions

getBaseForecaster() - Method in class weka.classifiers.timeseries.WekaForecaster

Get the base Weka regression scheme being used to make forecasts

getBeanDescriptor() - Method in class weka.gui.beans.TimeSeriesForecastingBeanInfo

Get the bean descriptor for this bean

getCalculateConfIntervalsForForecasts() - Method in interface weka.classifiers.timeseries.core.ConfidenceIntervalForecaster

Return the number of steps for which confidence intervals will be computed.

getCalculateConfIntervalsForForecasts() - Method in class weka.classifiers.timeseries.WekaForecaster

Return the number of steps for which confidence intervals will be computed.

getCapabilities() - Method in class weka.classifiers.timeseries.core.TimeSeriesTranslate

Returns the Capabilities of this filter.

getCapabilities() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns the Capabilities of this filter.

getConfidenceLevel() - Method in interface weka.classifiers.timeseries.core.ConfidenceIntervalForecaster

Get the confidence level in use for computing confidence intervals.

getConfidenceLevel() - Method in class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

Get the confidence level in use

getConfidenceLevel() - Method in class weka.classifiers.timeseries.WekaForecaster

Get the confidence level in use for computing confidence intervals.

getConfidenceLimitsForTarget(String, double, int) - Method in class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

Get the confidence limits (upper and lower bounds) for the named target at the given step number

getConfidenceOffsets(double, List<List<NumericPrediction>>) - Method in class weka.classifiers.timeseries.core.ErrorBasedConfidenceIntervalEstimator

Get the confidence bound offsets for each target at the supplied confidence level

getCurrentTimeStampValue() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns the current (i.e.

getCustomEditorForStep() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the fully qualified name of the GUI editor for this step

getCustomizeDateDerivedPeriodics() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if the date-derived periodics check box is selected.

getCustomName() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the custom (descriptive) name for this bean (if one has been set)

getCustomPeriodics() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the date-derived custom periodic attributes in use.

getDateTimeStampFinal() - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Get the last date timestamp value in the batch training data

getDateTimeStampInitial() - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Get the first date time stamp value in the batch training data

getDayString() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Get the day of the week as a string.

getDefaultDriver() - Static method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Get the default graph driver (currently uses the JFreeChart library)

getDefaultSettings() - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

getDefinition() - Method in class weka.classifiers.timeseries.eval.DACModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.MAEModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.MAPEModule

getDefinition() - Method in class weka.classifiers.timeseries.eval.MSEModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.RAEModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.RMSEModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.RRSEModule

Return the mathematical formula that this evaluation module computes.

getDefinition() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Return the mathematical formula that this evaluation module computes.

getDeltaTime() - Method in class weka.filters.supervised.attribute.TSLagMaker

Return the difference between time values.

getDescription() - Method in class weka.classifiers.timeseries.eval.DACModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.MAEModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.MAPEModule

getDescription() - Method in class weka.classifiers.timeseries.eval.MSEModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.RAEModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.RMSEModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.RRSEModule

Return the longer (single sentence) description of this evaluation module

getDescription() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Return the longer (single sentence) description of this evaluation module

getDriver(String) - Static method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Factory method for obtaining a named graph driver for producing graphs

getEncodedForecaster() - Method in class weka.gui.beans.TimeSeriesForecasting

Gets the base 64 encoded forecaster

getEncodedForecaster() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Gets the base 64 encoded forecaster

getErrorsForTarget(String) - Method in class weka.classifiers.timeseries.eval.ErrorModule

Get a list of the errors for the supplied target

getEvalName() - Method in class weka.classifiers.timeseries.eval.DACModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.MAEModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.MAPEModule

getEvalName() - Method in class weka.classifiers.timeseries.eval.MSEModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.RAEModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.RMSEModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.RRSEModule

Return the short identifying name of this evaluation module

getEvalName() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Return the short identifying name of this evaluation module

getEvaluateOnTestData() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get whether evaluation is to be performed on the test data.

getEvaluateOnTrainingData() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get whether evaluation is to be performed on the training data

getEvaluationModules() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get the evaluation modules in use

getEventSetDescriptors() - Method in class weka.gui.beans.TimeSeriesForecastingBeanInfo

getExcludeSeasonalCorrection() - Method in class weka.classifiers.timeseries.HoltWinters

Get whether to exclude the seasonal correction

getExcludeTrendCorrection() - Method in class weka.classifiers.timeseries.HoltWinters

Get whether to exclude the trend correction

getExplorer() - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Unused - just returns null

getFieldName() - Method in class weka.classifiers.timeseries.gui.CustomPeriodicEditor

Get the name for this custom periodic test (will be used as the field name)

getFieldsToForecast() - Method in class weka.classifiers.timeseries.AbstractForecaster

Get the fields to forecast.

getFieldsToForecast() - Method in interface weka.classifiers.timeseries.TSForecaster

Get the fields to forecast.

getFieldsToLag() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the names of the fields to create lagged variables for.

getFieldsToLagAsString() - Method in class weka.filters.supervised.attribute.TSLagMaker

getFilename() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the filename to load from.

getFilename() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the filename to load from.

getFillWithMissing() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Gets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).

getForecaster() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the WekaForecaster that is being configured.

getForecaster() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the forecaster.

getForecaster(String) - Static method in class weka.gui.beans.TimeSeriesForecasting

Decodes and returns a forecasting model (list containing the forecaster and Instances object containing the structure of the data used to train the forecaster) from a base 64 string.

getForecaster() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the forecaster.

getForecaster(String) - Static method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Decodes and returns a forecasting model (list containing the forecaster and Instances object containing the structure of the data used to train the forecaster) from a base 64 string.

getForecastFuture() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get whether future forecasts beyond the end of the training and/or test data will be generated.

getGraphFuturePredictions() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if the user has opted to graph future predictions

getGraphPanelSteps(TSForecaster, List<ErrorModule>, String, List<Integer>, int, Instances) - Method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Return the graph encapsulated in a JPanel.

getGraphPanelSteps(TSForecaster, List<ErrorModule>, String, List<Integer>, int, Instances) - Method in class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

Return the graph encapsulated in a JPanel.

getGraphPanelTargets(TSForecaster, ErrorModule, List<String>, int, int, Instances) - Method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Return the graph encapsulated in a panel.

getGraphPanelTargets(TSForecaster, ErrorModule, List<String>, int, int, Instances) - Method in class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

Return the graph encapsulated in a panel.

getGraphPredictionsAtStep() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Get the step number to graph all the targets at.

getGraphTargetForSteps() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if the user has opted to graph a target at specified steps

getGraphTargetForStepsStepList() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

If the user has opted to graph a target a various steps, then this method returns the list of steps that they have selected.

getGraphTargetForStepsTarget() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Return the target that is to be graphed at various steps

getHoldoutSetSize() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Gets the size of the holdout set.

getHorizon() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the horizon (i.e.

getHorizonValue() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the value in the horizon spinner (i.e.

getImageFromChart(JPanel, int, int) - Method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Get an image representation of the supplied chart.

getImageFromChart(JPanel, int, int) - Method in class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

Get an image representation of the supplied chart.

getIncludePowersOfTime() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get whether to include powers of time in the transformed data

getIncludeTimeLagProducts() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get whether to include products between time and the lagged variables

getIncomingConnectionTypes() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

getInstanceRange() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Gets the number of instances forward to translate values between.

getInvertSelection() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Get whether the supplied columns are to be removed or kept

getLabel() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Get the optional label for this interval.

getLagRange() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the ranges used to fine tune lag selection

getLowerTest() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Get the lower bound test

getMaxLag() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the maximum lag to create.

getMinLag() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the minimum lag to create.

getMinRequiredTrainingPoints() - Method in class weka.classifiers.timeseries.HoltWinters

Return the minimum number of training/priming data points required before a forecast can be made

getMinRequiredTrainingPoints() - Method in interface weka.classifiers.timeseries.PrimingDataLearner

Return the minimum number of training/priming data points required before a forecast can be made

getModule(String) - Static method in class weka.classifiers.timeseries.eval.TSEvalModule

Factory method for obtaining a named evaluation module.

getModuleList() - Static method in class weka.classifiers.timeseries.eval.TSEvalModule

Gets a list of known evaluation modules.

getMonthString() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Get the month as a String.

getNumConsecutiveLongLagsToAverage() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the number of consecutive long lagged variables to average.

getNumStepsToForecast() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the number of time steps to forecast beyond the end of the incoming priming data.

getNumStepsToForecast() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the number of time steps to forecast beyond the end of the incoming priming data.

getOptions() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Gets the current settings of the filter.

getOptions() - Method in class weka.classifiers.timeseries.HoltWinters

getOptions() - Method in class weka.classifiers.timeseries.WekaForecaster

Gets the current settings of this Forecaster.

getOptions() - Method in class weka.filters.supervised.attribute.TSLagMaker

Gets the current settings of the LagMaker.

getOutgoingConnectionTypes() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

getOutputFuturePredictions() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if the user has opted to output future predictions

getOutputPredictionsAtStep() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns at which step to output predictions.

getOutputPredictionsTarget() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Get the selected target to output predictions for.

getOverlayFields() - Method in interface weka.classifiers.timeseries.core.OverlayForecaster

Get a comma-separated list of fields that considered to be overlay fields

getOverlayFields() - Method in class weka.classifiers.timeseries.WekaForecaster

Get a comma-separated list of fields that considered to be overlay fields

getOverlayFields() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get overlay fields

getPanelFutureForecast(TSForecaster, List<List<NumericPrediction>>, List<String>, Instances) - Method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Return the graph encapsulated in a JPanel

getPanelFutureForecast(TSForecaster, List<List<NumericPrediction>>, List<String>, Instances) - Method in class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

Return the graph encapsulated in a JPanel

getPeriodicity() - Method in class weka.filters.supervised.attribute.TSLagMaker

Gets the Periodicity representing the time stamp in use for this lag maker.

getPeriodicity() - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Get periodicity being managed

getPerspectiveIcon() - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Get the icon for this perspective.

getPerspectiveTipText() - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Get the tool tip text for this perspective.

getPerspectiveTitle() - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Get the title of this perspective

getPredictionsForAllTargets() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Gets the predictions for all targets

getPredictionsForTarget(String) - Method in class weka.classifiers.timeseries.eval.ErrorModule

Get a list of predictions (plus actuals if known) for the supplied target

getPredictionsForTestData(int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get predictions for all targets for the specified step number on the test data

getPredictionsForTrainingData(int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get predictions for all targets for the specified step number on the training data

getPreviousActual() - Method in class weka.classifiers.timeseries.eval.RAEModule

Get the actual target values from the immediately preceding time step.

getPreviousActual() - Method in class weka.classifiers.timeseries.eval.RRSEModule

Get the actual target values from the immediately preceding time step.

getPreviousState() - Method in interface weka.classifiers.timeseries.core.StateDependentPredictor

Get the last set state of the model.

getPreviousState() - Method in interface weka.classifiers.timeseries.TSForecaster

Get the last set state of the model.

getPreviousState() - Method in class weka.classifiers.timeseries.WekaForecaster

Get the last set state of the model.

getPrimaryPeriodicFieldName() - Method in class weka.filters.supervised.attribute.TSLagMaker

The name of the primary periodic attribute or null if one hasn't been specified.

getPrimeForTestDataWithTestData() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Gets whether evaluation for the test data will begin by priming with the first x instances from the test data and then forecasting from step x + 1.

getPrimeWindowSize() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get the size of the priming window - i.e.

getRebuildForecaster() - Method in class weka.gui.beans.TimeSeriesForecasting

Get whether the forecaster will be rebuilt/re-estimated on the incoming data.

getRebuildForecaster() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get whether the forecaster will be rebuilt/re-estimated on the incoming data.

getRemoveLeadingInstancesWithUnknownLagValues() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get whether to drop instances at the start of the transformed data where lag values are unknown/missing

getRevision() - Method in class weka.classifiers.timeseries.core.TimeSeriesTranslate

Returns the revision string.

getSaveFilename() - Method in class weka.gui.beans.TimeSeriesForecasting

Get the name of the file to save the forecasting model to if the user has opted to rebuild the forecaster using the incoming data.

getSaveFilename() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Get the name of the file to save the forecasting model to if the user has opted to rebuild the forecaster using the incoming data.

getSeasonalSmoothingFactor() - Method in class weka.classifiers.timeseries.HoltWinters

Get the seasonal smoothing factor

getSeasonCycleLength() - Method in class weka.classifiers.timeseries.HoltWinters

Get the length of a "year", i.e.

getSelectedTimeStampField() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the selected time stamp field name.

getSkipEntries() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get a list of time units to be 'skipped' - i.e.

getTabTitle() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Get a title for displaying in the tab that will hold this panel

getTabTitle() - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Get the title for this tab

getTabTitle() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the title for this panel suitable for displaying in a tab.

getTabTitleToolTip() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Get the tool tip for this configuration panel

getTabTitleToolTip() - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Get the tool tip for this tab

getTabTitleToolTip() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Get the tool tip for this panel.

getTargetFields() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Get the list of target field names.

getTestBeingEdited() - Method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Get the test being edited

getTestData() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get the test data (if any)

getTimeStampField() - Method in class weka.filters.supervised.attribute.TSLagMaker

Get the name of the time stamp field.

getTrainingData() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Get the training data (if any)

getTransformedData(Instances) - Method in class weka.filters.supervised.attribute.TSLagMaker

Creates a transformed data set based on the user's settings

getTrendSmoothingFactor() - Method in class weka.classifiers.timeseries.HoltWinters

Get the trend smoothing factor

getTSLagMaker() - Method in interface weka.classifiers.timeseries.core.TSLagUser

Get the TSLagMaker that we are using.

getTSLagMaker() - Method in class weka.classifiers.timeseries.WekaForecaster

Get the TSLagMaker that we are using.

getUpperTest() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Get the upper bound test

getValueSmoothingFactor() - Method in class weka.classifiers.timeseries.HoltWinters

Get the value smoothing factor

getVisual() - Method in class weka.gui.beans.TimeSeriesForecasting

Gets the visual appearance of this wrapper bean

globalInfo() - Method in class weka.classifiers.timeseries.core.TimeSeriesTranslate

Returns a string describing this classifier

globalInfo() - Method in class weka.classifiers.timeseries.HoltWinters

Description of this forecaster.

globalInfo() - Method in class weka.filters.supervised.attribute.TSLagMaker

globalInfo() - Method in class weka.gui.beans.TimeSeriesForecasting

Global about information for this component.

GraphDriver - Class in weka.classifiers.timeseries.eval.graph

Abstract base class for graph drivers.

GraphDriver() - Constructor for class weka.classifiers.timeseries.eval.graph.GraphDriver

graphFutureForecastOnTesting(GraphDriver, TSForecaster, List<String>) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph historical and future forecasted values using a graph driver for the test.

graphFutureForecastOnTraining(GraphDriver, TSForecaster, List<String>) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph historical and future forecasted values using a graph driver for the training data.

graphPredictionsForStepsOnTesting(GraphDriver, TSForecaster, String, List<Integer>, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph predicted values at the given step-ahead levels for a single target on the test data.

graphPredictionsForStepsOnTraining(GraphDriver, TSForecaster, String, List<Integer>, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph predicted values at the given step-ahead levels for a single target on the training data.

graphPredictionsForTargetsOnTesting(GraphDriver, TSForecaster, List<String>, int, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph predicted values at the given step-ahead level for the supplied targets on the test data.

graphPredictionsForTargetsOnTraining(GraphDriver, TSForecaster, List<String>, int, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Graph predicted values at the given step-ahead level for the supplied targets on the training data.

H

HoltWinters - Class in weka.classifiers.timeseries

Class implementing the Holt-Winters triple exponential smoothing method for time series forecasting.

HoltWinters() - Constructor for class weka.classifiers.timeseries.HoltWinters

I

ID - Static variable in class weka.gui.knowledgeflow.TimeSeriesPerspective.TimeSeriesDefaults

IncrementallyPrimeable - Interface in weka.classifiers.timeseries.core

An interface to a forecaster that can be primed incrementally.

incrementArtificialTimeValue(int) - Method in class weka.filters.supervised.attribute.TSLagMaker

Increment the artificial time value with the supplied incrememt value.

input(Instance) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Input an instance for filtering.

input(Instance) - Method in class weka.filters.supervised.attribute.TSLagMaker

inputOneTemporarily(Instance) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Input a single instance for filtering without placing it into the history queue.

insertMissing(Instances, Attribute, TSLagMaker.PeriodicityHandler, String, List<String>) - Static method in class weka.classifiers.timeseries.core.Utils

Check to see if there are any instances (time steps) that are missing entirely from the data (and are not in the skip list).

instanceRangeTipText() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Returns the tip text for this property

invertSelectionTipText() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Returns the tip text for this property

isBusy() - Method in class weka.gui.beans.TimeSeriesForecasting

Returns true if.

isDateBased() - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Returns true if the periodicity being managed is date timestamp-based

isEmpty(String) - Static method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Utility method to check if a String is null or empty ("").

isEnabledCustomizeDateDerivedPeriodics() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if date-derived periodics is enabled

isProducingConfidenceIntervals() - Method in interface weka.classifiers.timeseries.core.ConfidenceIntervalForecaster

Returns true if this forecaster is computing confidence limits for some or all of its future forecasts (i.e.

isProducingConfidenceIntervals() - Method in class weka.classifiers.timeseries.WekaForecaster

Returns true if this forecaster is computing confidence limits for some or all of its future forecasts (i.e.

isUpper() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Returns true if this is the upper bound.

isUsingAnArtificialTimeIndex() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns true if an artificial time index is in use.

isUsingANativeTimeStamp() - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Returns true if the forecaster is using a time stamp defined in the data (rather than no time stamp or an artificially generated one)

isUsingCustomLags() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Returns true if the user has opted to customize the lags.

isUsingOverlayData() - Method in interface weka.classifiers.timeseries.core.OverlayForecaster

Returns true if this forecaster has been trained with data containing overlay fields, and thus will expect to be provided with future values for these fields when making a forecast.

isUsingOverlayData() - Method in class weka.classifiers.timeseries.WekaForecaster

Returns true if overlay data has been used to train this forecaster, and thus is expected to be supplied for future time steps when making a forecast.

J

JFreeChartDriver - Class in weka.classifiers.timeseries.eval.graph

A Graph driver that uses the JFreeChart library.

JFreeChartDriver() - Constructor for class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

L

listOptions() - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Returns an enumeration describing the available options.

listOptions() - Method in class weka.classifiers.timeseries.HoltWinters

listOptions() - Method in class weka.classifiers.timeseries.WekaForecaster

Returns an enumeration describing the available options.

listOptions() - Method in class weka.filters.supervised.attribute.TSLagMaker

Returns an enumeration describing the available options.

loadBaseModel(String) - Method in interface weka.classifiers.timeseries.TSForecaster

Load serialized classifier

loadBaseModel(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Load serialized classifier

loadSerializedModel(String) - Method in interface weka.classifiers.timeseries.core.BaseModelSerializer

De-serialize model

loadSerializedState(String) - Method in interface weka.classifiers.timeseries.core.StateDependentPredictor

Load serialized model state

loadSerializedState(String) - Method in interface weka.classifiers.timeseries.TSForecaster

Load serialized model state

loadSerializedState(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Load serialized model state

M

m_boundOperator - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

the operator for this bound

m_day_of_month - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_day_of_yr - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_hour_of_day - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_min_of_hour - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_second - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_week_of_month - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_week_of_yr - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

m_year - Variable in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

date fields

MAEModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the mean absolute error of forecasted values.

MAEModule() - Constructor for class weka.classifiers.timeseries.eval.MAEModule

main(String[]) - Static method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Main method for testing this class

main(String[]) - Static method in class weka.classifiers.timeseries.core.TimeSeriesTranslate

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Tests the Weka advanced config panel from the command line.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.CustomPeriodicEditor

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Main method for testing this class.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.ForecastingPanel

Tests the Weka Forecasting panel from the command line.

main(String[]) - Static method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Tests the simple config panel from the command line.

main(String[]) - Static method in class weka.classifiers.timeseries.HoltWinters

Main method for running this class

main(String[]) - Static method in class weka.classifiers.timeseries.WekaForecaster

Main method for running this class from the command line

main(String[]) - Static method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Main method for testing this class

makeCopy(TSForecaster) - Static method in class weka.classifiers.timeseries.AbstractForecaster

Creates a deep copy of the given forecaster using serialization.

MAPEModule - Class in weka.classifiers.timeseries.eval

Computes the mean absolute percentage error

MAPEModule() - Constructor for class weka.classifiers.timeseries.eval.MAPEModule

MSEModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the mean squared error of forecasted values.

MSEModule() - Constructor for class weka.classifiers.timeseries.eval.MSEModule

O

okPressed() - Method in class weka.gui.knowledgeflow.steps.TimeSeriesForecastingStepEditorDialog

okToBeActive() - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

OverlayForecaster - Interface in weka.classifiers.timeseries.core

Interface to a forecaster that has been trained with data containing "overlay" attributes.

P

postExecution() - Method in class weka.classifiers.timeseries.AbstractForecaster

preExecution() - Method in class weka.classifiers.timeseries.AbstractForecaster

primeForecaster(Instances) - Method in class weka.classifiers.timeseries.AbstractForecaster

Supply the (potentially) trained model with enough historical data, up to and including the current time point, in order to produce a forecast.

primeForecaster(Instances) - Method in interface weka.classifiers.timeseries.TSForecaster

Supply the (potentially) trained model with enough historical data, up to and including the current time point, in order to produce a forecast.

primeForecaster(Instances) - Method in class weka.classifiers.timeseries.WekaForecaster

Supply the (potentially) trained model with enough historical data, up to and including the current time point, in order to produce a forecast.

primeForecasterIncremental(Instance) - Method in interface weka.classifiers.timeseries.core.IncrementallyPrimeable

Update the priming information incrementally, i.e.

primeForecasterIncremental(Instance) - Method in class weka.classifiers.timeseries.WekaForecaster

Update the priming information incrementally, i.e.

PrimingDataLearner - Interface in weka.classifiers.timeseries

Interface to a forecaster that learns from the priming data

printFutureTestForecast(TSForecaster) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the target values from the test data followed by the future forecast from the end of the test data.

printFutureTrainingForecast(TSForecaster) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the forecasted values (for all targets) beyond the end of the training data

printPredictionsForTestData(String, String, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the predictions for a given target at a given step-ahead level on the training data.

printPredictionsForTestData(String, String, int, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the predictions for a given target at a given step-ahead level from a given offset on the training data.

printPredictionsForTrainingData(String, String, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the predictions for a given target at a given step-ahead level on the training data.

printPredictionsForTrainingData(String, String, int, int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Print the predictions for a given target at a given step-ahead level from a given offset on the training data.

printUsage() - Static method in class weka.classifiers.timeseries.HoltWinters

Print usage information

processIncoming(Data) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

processInstance(Instance, boolean, boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

processInstance(Instance, boolean, boolean, boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Process an instance in the original format and produce a transformed instance as output.

processInstancePreview(Instance, boolean, boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

R

RAEModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the relative absolute error of forecasted values.

RAEModule() - Constructor for class weka.classifiers.timeseries.eval.RAEModule

remapDateTimeStamp(Instance, Instance, String) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Remaps a date timestamp to an integer starting (from the first time stamp seen in the data) at 0.

removeInstanceListener(InstanceListener) - Method in class weka.gui.beans.TimeSeriesForecasting

Deregister and remove a listener of InstanceEvents

removePropertyChangeListener(PropertyChangeListener) - Method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Removes a PropertyChangeListener.

replaceMissing(Instances, List<String>, String, boolean, TSLagMaker.Periodicity, String, Object...) - Static method in class weka.classifiers.timeseries.core.Utils

Replace missing target values by interpolation.

requiresLog() - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

Requires a log when running in the Workbench application

reset() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Reset this module

reset() - Method in class weka.classifiers.timeseries.eval.RAEModule

Reset this module

reset() - Method in class weka.classifiers.timeseries.eval.RRSEModule

Reset this module

reset() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Reset the module

reset() - Method in class weka.classifiers.timeseries.HoltWinters

reset() - Method in interface weka.classifiers.timeseries.PrimingDataLearner

Reset this forecaster ready to learn from a new set of priming data

reset() - Method in interface weka.classifiers.timeseries.TSForecaster

Reset this forecaster so that it is ready to construct a new model.

reset() - Method in class weka.classifiers.timeseries.WekaForecaster

Reset the forecaster.

reset() - Method in class weka.filters.supervised.attribute.TSLagMaker

Reset the lag maker.

RMSEModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the root mean squared error of forecasted values.

RMSEModule() - Constructor for class weka.classifiers.timeseries.eval.RMSEModule

RRSEModule - Class in weka.classifiers.timeseries.eval

An evaluation module that computes the root relative squared error of forecasted values.

RRSEModule() - Constructor for class weka.classifiers.timeseries.eval.RRSEModule

run(Object, String[]) - Method in class weka.classifiers.timeseries.AbstractForecaster

Run the supplied object using the supplied options on the command line.

runForecaster(TSForecaster, String[]) - Method in class weka.classifiers.timeseries.AbstractForecaster

Run the supplied forecaster with the supplied options on the command line.

runForecaster(TSForecaster, String[]) - Method in interface weka.classifiers.timeseries.TSForecaster

Run the supplied forecaster with the supplied options on the command line.

S

saveBaseModel(String) - Method in interface weka.classifiers.timeseries.TSForecaster

Save underlying classifier

saveBaseModel(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Save underlying classifier

saveChartToFile(JPanel, String, int, int) - Method in class weka.classifiers.timeseries.eval.graph.GraphDriver

Save a chart to a file.

saveChartToFile(JPanel, String, int, int) - Method in class weka.classifiers.timeseries.eval.graph.JFreeChartDriver

Save a chart to a file.

seasonalSmoothingFactorTipText() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

seasonCycleLengthTipText() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

serializeModel(String) - Method in interface weka.classifiers.timeseries.core.BaseModelSerializer

Serialize model

serializeState(String) - Method in interface weka.classifiers.timeseries.core.StateDependentPredictor

Serialize model state

serializeState(String) - Method in interface weka.classifiers.timeseries.TSForecaster

Serialize model state

serializeState(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Serialize model state

setActive(boolean) - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Make this perspective the active (visible) one in the KF

setAddAMIndicator(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create an AM indicator attribute.

setAddDayOfMonth(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a day of the month attribute.

setAddDayOfWeek(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a day of the week attribute.

setAddMonthOfYear(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a month of the year attribute.

setAddNumDaysInMonth(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a numeric attribute that holds the number of days in the month.

setAddQuarterOfYear(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a quarter attribute.

setAddWeekendIndicator(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to create a weekend indicator attribute.

setAdjustForTrends(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to adjust for trends or not.

setAdjustForVariance(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to adjust for variance in the data by taking the log of the target(s).

setAdvancedConfig(AdvancedConfigPanel) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Set a reference to the advanced configuration panel.

setArtificialTimeStartOffset(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the offset, from the value associated with the last training instance, for the artificial time stamp.

setArtificialTimeStartOffset(String) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set the offset, from the value associated with the last training instance, for the artificial time stamp.

setArtificialTimeStartValue(double) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the starting value for the artificial time stamp.

setAttributeIndices(String) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Set which attributes are to be copied (or kept if invert is true)

setAttributeIndicesArray(int[]) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Set which attributes are to be copied (or kept if invert is true)

setAverageConsecutiveLongLags(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Sets whether to average consecutive long lagged variables.

setAverageLagsAfter(int) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set at which point consecutive long lagged variables are to be averaged (default = 2, i.e.

setBaseForecaster(Classifier) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the base Weka regression scheme to use.

setCalculateConfIntervalsForForecasts(int) - Method in interface weka.classifiers.timeseries.core.ConfidenceIntervalForecaster

Set the number of steps for which to compute confidence intervals for.

setCalculateConfIntervalsForForecasts(int) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the number of steps for which to compute confidence intervals for.

setClipboard(TimeSeriesForecasting) - Static method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Sets the knowledge flow's paste buffer equal to the supplied configured TimeSeriesForecasting component.

setConfidenceLevel(double) - Method in interface weka.classifiers.timeseries.core.ConfidenceIntervalForecaster

Set the confidence level for confidence intervals.

setConfidenceLevel(double) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the confidence level for confidence intervals.

setCustomName(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set a custom (descriptive) name for this bean

setCustomPeriodics(Map<String, ArrayList<CustomPeriodicTest>>) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the date-derived custom periodic fields to use/compute

setDateTimeStampFinal(long) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set the last date timestamp value in the batch training data

setDateTimeStampInitial(long) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set the first date time stamp value in the batch training data

setDayOfMonth(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the day of the month for this bound.

setDayOfWeek(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the day of the week for this bound.

setDayOfYear(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the day of the year for this bound.

setDeltaTime(double) - Method in enum weka.filters.supervised.attribute.TSLagMaker.Periodicity

setDeltaTime(double) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set the delta time for the periodicity being managed

setEnabled(boolean) - Method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Set the enabled status of all the GUI elements

setEncodedForecaster(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the base 64 encoded forecaster.

setEncodedForecaster(String) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set the base 64 encoded forecaster.

setEnvironment(Environment) - Method in class weka.gui.beans.TimeSeriesForecasting

Set environment variables to use.

setEnvironment(Environment) - Method in class weka.gui.beans.TimeSeriesForecastingCustomizer

Set the environment variables to use.

setEvaluateOnTestData(boolean) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set whether to perform evaluation on the training data

setEvaluateOnTrainingData(boolean) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set whether to perform evaluation on the training data

setEvaluationModules(String) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set the evaluation modules to use/

setExcludeSeasonalCorrection(boolean) - Method in class weka.classifiers.timeseries.HoltWinters

Set whether to exclude the seasonal correction

setExcludeTrendCorrection(boolean) - Method in class weka.classifiers.timeseries.HoltWinters

Set whether to exclude the trend correction

setExplorer(Explorer) - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Unused

setFieldName(String) - Method in class weka.classifiers.timeseries.gui.CustomPeriodicEditor

Set the name for this custom periodic test

setFieldsToForecast(String) - Method in class weka.classifiers.timeseries.AbstractForecaster

Set the names of the fields/attributes in the data to forecast.

setFieldsToForecast(String) - Method in interface weka.classifiers.timeseries.TSForecaster

Set the names of the fields/attributes in the data to forecast.

setFieldsToForecast(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the names of the fields/attributes in the data to forecast.

setFieldsToLag(List<String>) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the names of the fields to create lagged variables for

setFieldsToLagAsString(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

setFilename(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the filename to load from.

setFilename(File) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set the filename to load from.

setFillWithMissing(boolean) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Sets whether missing values should be used rather than removing instances where the translated value is not known (due to border effects).

setForecaster(WekaForecaster) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Set the WekaForecaster that is to be configured by this panel.

setForecastFuture(boolean) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set whether we should generate a future forecast beyond the end of the training and/or test data.

setHorizon(int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set the horizon - i.e.

setHorizon(int) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Set the horizon (i.e.

setHourOfDay(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the hour of the day for this bound.

setIncludePowersOfTime(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to include powers of time in the transformed data

setIncludeTimeLagProducts(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to include products between time and the lagged variables

setInputFormat(Instances) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.classifiers.timeseries.core.TimeSeriesTranslate

Sets the format of the input instances.

setInputFormat(Instances) - Method in class weka.filters.supervised.attribute.TSLagMaker

setInstanceRange(int) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Sets the number of instances forward to translate values between.

setInstances(Instances) - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Set the instances that will be used in the training and evaluation of the forecaster

setInstances(Instances) - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Set the working instances for this panel.

setInstances(Instances) - Method in class weka.classifiers.timeseries.gui.ForecastingPanel

Set the training instances to use

setInstances(Instances) - Method in class weka.classifiers.timeseries.gui.SimpleConfigPanel

Set the instances that will be used to train and/or test the forecaster.

setInstances(Instances) - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Set instances (if the perspective accepts them)

setInstances(Instances) - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

setInvertSelection(boolean) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Set whether selected columns should be removed or kept.

setIsDateBased(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set whether the periodicity being managed is date timestamp-based

setIsUpper(boolean) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set whether this is the upper bound or not.

setLabel(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Set the label for this interval

setLagRange(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set ranges to fine tune lag selection.

setLoaded(boolean) - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Tell this perspective whether or not it is part of the users perspectives toolbar in the KnowledgeFlow.

setLog(Logger) - Method in class weka.classifiers.timeseries.gui.explorer.ExplorerTSPanel

Set the logging object to use

setLog(Logger) - Method in class weka.classifiers.timeseries.gui.ForecastingPanel

Set the log to use

setLog(Logger) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the logging object to use

setLog(Logger) - Method in class weka.gui.knowledgeflow.TimeSeriesPerspective

setMainKFPerspective(KnowledgeFlowApp.MainKFPerspective) - Method in class weka.gui.beans.TimeSeriesForecastingKFPerspective

Set a reference to the main KnowledgeFlow perspective - i.e.

setMaxLag(int) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the maximum lag to create (default = 12, i.e.

setMinLag(int) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the minimum lag to create (default = 1, i.e.

setMinuteOfHour(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the minute of the hour for this bound.

setMonth(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the month for this bound.

setNumConsecutiveLongLagsToAverage(int) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the number of long lagged variables to average for each averaged variable created (default = 2, e.g.

setNumStepsToForecast(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the number of time steps to forecast beyond the end of the incoming priming data.

setNumStepsToForecast(String) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set the number of time steps to forecast beyond the end of the incoming priming data.

setObject(Object) - Method in class weka.gui.beans.TimeSeriesForecastingCustomizer

Set the object to edit

setOperator(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the operator for this bound

setOptions(String[]) - Method in class weka.classifiers.timeseries.core.AbstractTimeSeriesFilter

Parses a given list of options controlling the behaviour of this object.

setOptions(String[]) - Method in class weka.classifiers.timeseries.HoltWinters

setOptions(String[]) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the options for the forecaster

setOptions(String[]) - Method in class weka.filters.supervised.attribute.TSLagMaker

Parses a given list of options.

setOverlayFields(String) - Method in interface weka.classifiers.timeseries.core.OverlayForecaster

Set the fields to consider as overlay fields

setOverlayFields(String) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the fields to consider as overlay fields

setOverlayFields(List<String>) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the names of fields in the data that are to be considered "overlay" fields - i.e.

setParentWindow(Window) - Method in class weka.gui.beans.TimeSeriesForecastingCustomizer

Set the Window that contains this customizer

setPeriodicity(TSLagMaker.Periodicity) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set periodicity to manage

setPeriodicity(TSLagMaker.Periodicity) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the periodicity for the data.

setPreviousState(Object) - Method in interface weka.classifiers.timeseries.core.StateDependentPredictor

Load state into model.

setPreviousState(List<Object>) - Method in interface weka.classifiers.timeseries.TSForecaster

Load state into model.

setPreviousState(List<Object>) - Method in class weka.classifiers.timeseries.WekaForecaster

Load state into model.

setPrimaryPeriodicFieldName(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the name of a periodic attribute in the data.

setPrimeForTestDataWithTestData(boolean) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set whether evaluation for test data should begin by priming with the first x test data instances and then forecasting from step x + 1.

setPrimeWindowSize(int) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set the size of the priming window - i.e.

setRebuildForecaster(boolean) - Method in class weka.gui.beans.TimeSeriesForecasting

Set whether the forecaster should be rebuilt/re-estimated on the incoming data.

setRebuildForecaster(boolean) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set whether the forecaster should be rebuilt/re-estimated on the incoming data.

setRebuildModelAfterEachTestForecastStep(boolean) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set whether the forecasting model should be rebuilt after each forecasting step on the test data using both the training data and test data up to the current instance.

setRelativeRAEModule(RAEModule) - Method in class weka.classifiers.timeseries.eval.RAEModule

Set a RAEModule to use for the relative calculations - i.e.

setRelativeRRSEModule(RRSEModule) - Method in class weka.classifiers.timeseries.eval.RRSEModule

Set a RRSEModule to use for the relative calculations - i.e.

setRemoveLeadingInstancesWithUnknownLagValues(boolean) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set whether to drop instances at the start of the transformed data where lag values are unknown/missing

setSaveFilename(String) - Method in class weka.gui.beans.TimeSeriesForecasting

Set the name of the file to save the forecasting model out to if the user has opted to rebuild the forecaster using the incoming data.

setSaveFilename(File) - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

Set the name of the file to save the forecasting model out to if the user has opted to rebuild the forecaster using the incoming data.

setSeasonalSmoothingFactor(double) - Method in class weka.classifiers.timeseries.HoltWinters

Set the seasonal smoothing factor

setSeasonCycleLength(int) - Method in class weka.classifiers.timeseries.HoltWinters

Set the length of a "year", i.e.

setSecond(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the second for this bound.

setSkipEntries(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the list of time units to be 'skipped' - i.e.

setSkipList(String, String) - Method in class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

Set a list of skip entries

setTargetFields(List<String>) - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Set a list of target field names.

setTest(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Set the test as a String

setTestData(Instances) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set the test data to use

setTestToEdit(CustomPeriodicTest) - Method in class weka.classifiers.timeseries.gui.CustomPeriodicTestEditor

Set the test to edit

setTimeSeriesModelListener(TimeSeriesPerspective.TimeSeriesModelListener) - Method in class weka.classifiers.timeseries.gui.ForecastingPanel

Set a listener that accepts WekaForecaster models.

setTimeStampField(String) - Method in class weka.filters.supervised.attribute.TSLagMaker

Set the name of the time stamp field in the data

setTrainingData(Instances) - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Set the training data to use

setTrendSmoothingFactor(double) - Method in class weka.classifiers.timeseries.HoltWinters

Set the trend smoothing factor

setTSLagMaker(TSLagMaker) - Method in interface weka.classifiers.timeseries.core.TSLagUser

Set the TSLagMaker to use.

setTSLagMaker(TSLagMaker) - Method in class weka.classifiers.timeseries.WekaForecaster

Set the TSLagMaker to use.

setValueSmoothingFactor(double) - Method in class weka.classifiers.timeseries.HoltWinters

Set the value smoothing factor

setVisual(BeanVisual) - Method in class weka.gui.beans.TimeSeriesForecasting

Sets the visual appearance of this wrapper bean

setWeekOfMonth(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the week of the month for this bound.

setWeekOfYear(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the week of the year for this bound.

setYear(String) - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Set the year for this bound.

SHOW_CLIPBOARD_POPUP - Static variable in class weka.gui.knowledgeflow.TimeSeriesPerspective.TimeSeriesDefaults

SHOW_CLIPBOARD_POPUP_KEY - Static variable in class weka.gui.knowledgeflow.TimeSeriesPerspective.TimeSeriesDefaults

SimpleConfigPanel - Class in weka.classifiers.timeseries.gui

Class that renders a simple configuration panel for configuring a time series forecaster.

SimpleConfigPanel(ForecastingPanel) - Constructor for class weka.classifiers.timeseries.gui.SimpleConfigPanel

Constructor

StateDependentPredictor - Interface in weka.classifiers.timeseries.core

An interface for state-dependent predictors.

stepInit() - Method in class weka.knowledgeflow.steps.TimeSeriesForecasting

stop() - Method in class weka.gui.beans.TimeSeriesForecasting

Stop the component from executing.

stringToList(String) - Static method in class weka.classifiers.timeseries.AbstractForecaster

A utility method for converting a List of Strings to a single comma separated String.

T

TimeSeriesForecasting - Class in weka.gui.beans

KnowledgeFlow component for producing a forecast using a time series forecasting model.

TimeSeriesForecasting() - Constructor for class weka.gui.beans.TimeSeriesForecasting

Constructor

TimeSeriesForecasting - Class in weka.knowledgeflow.steps

Knowledge Flow step that encapsulates a time series forecasting model and uses it to produce forecasts given incoming historical data.

TimeSeriesForecasting() - Constructor for class weka.knowledgeflow.steps.TimeSeriesForecasting

TimeSeriesForecastingBeanInfo - Class in weka.gui.beans

BeanInfo class for the TimeSeriesForecasting bean

TimeSeriesForecastingBeanInfo() - Constructor for class weka.gui.beans.TimeSeriesForecastingBeanInfo

TimeSeriesForecastingCustomizer - Class in weka.gui.beans

Customizer for the TimeSeriesForecasting bean

TimeSeriesForecastingCustomizer() - Constructor for class weka.gui.beans.TimeSeriesForecastingCustomizer

Constructor

TimeSeriesForecastingKFPerspective - Class in weka.gui.beans

KnowledgeFlow perspective provides the time series environment.

TimeSeriesForecastingKFPerspective() - Constructor for class weka.gui.beans.TimeSeriesForecastingKFPerspective

Constructor

TimeSeriesForecastingStepEditorDialog - Class in weka.gui.knowledgeflow.steps

Editor dialog for the time series forecasting step

TimeSeriesForecastingStepEditorDialog() - Constructor for class weka.gui.knowledgeflow.steps.TimeSeriesForecastingStepEditorDialog

TimeSeriesPerspective - Class in weka.gui.knowledgeflow

Knowledge Flow Perspective for the time series forecasting environment

TimeSeriesPerspective() - Constructor for class weka.gui.knowledgeflow.TimeSeriesPerspective

TimeSeriesPerspective.TimeSeriesDefaults - Class in weka.gui.knowledgeflow

TimeSeriesPerspective.TimeSeriesDefaults() - Constructor for class weka.gui.knowledgeflow.TimeSeriesPerspective.TimeSeriesDefaults

TimeSeriesPerspective.TimeSeriesModelListener - Interface in weka.gui.knowledgeflow

TimeSeriesTranslate - Class in weka.classifiers.timeseries.core

Re-written version of weka.filters.unsupervised.attribute.TimeSeriesTranslate.

TimeSeriesTranslate() - Constructor for class weka.classifiers.timeseries.core.TimeSeriesTranslate

toString() - Method in enum weka.classifiers.timeseries.core.CustomPeriodicTest.Operator

toString() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest.TestPart

Provides a textual representation of this test bound

toString() - Method in class weka.classifiers.timeseries.core.CustomPeriodicTest

Returns a textual description of this test

toString() - Method in class weka.classifiers.timeseries.eval.ErrorModule

Gets a textual description of this module : getDescription() + getEvalName()

toString() - Method in class weka.classifiers.timeseries.HoltWinters

toString() - Method in class weka.classifiers.timeseries.WekaForecaster

toSummaryString() - Method in class weka.classifiers.timeseries.eval.ErrorModule

toSummaryString() - Method in class weka.classifiers.timeseries.eval.TSEvalModule

Return the summary description of the computed measure for each target.

toSummaryString() - Method in class weka.classifiers.timeseries.eval.TSEvaluation

Generates a String containing the results of evaluating the forecaster.

trendSmoothingFactorTipText() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

TSEvalModule - Class in weka.classifiers.timeseries.eval

Abstract superclass of all evaluation modules.

TSEvalModule() - Constructor for class weka.classifiers.timeseries.eval.TSEvalModule

TSEvaluation - Class in weka.classifiers.timeseries.eval

Main evaluation routines for time series forecasting models.

TSEvaluation(Instances, double) - Constructor for class weka.classifiers.timeseries.eval.TSEvaluation

Constructor.

TSEvaluation(Instances, Instances) - Constructor for class weka.classifiers.timeseries.eval.TSEvaluation

Constructor.

TSForecaster - Interface in weka.classifiers.timeseries

Interface for something that can produce time series predictions.

TSLagMaker - Class in weka.filters.supervised.attribute

A class for creating lagged versions of target variable(s) for use in time series forecasting.

TSLagMaker() - Constructor for class weka.filters.supervised.attribute.TSLagMaker

TSLagMaker.Periodicity - Enum in weka.filters.supervised.attribute

Enum defining periodicity

TSLagMaker.PeriodicityHandler - Class in weka.filters.supervised.attribute

Helper class to manage time stamp manipulation with respect to various periodicities.

TSLagMaker.PeriodicityHandler() - Constructor for class weka.filters.supervised.attribute.TSLagMaker.PeriodicityHandler

TSLagUser - Interface in weka.classifiers.timeseries.core

Interface to something that uses the TSLagMaker class.

U

updateForecaster(double) - Method in class weka.classifiers.timeseries.HoltWinters

Update the smoothed estimates using the supplied value

updateForecaster(double) - Method in interface weka.classifiers.timeseries.PrimingDataLearner

Update the forecaster on a priming instance or predicted value (for closed-loop projection)

updateOutputPanel() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Updates the status/selection of various widgets on the output panel

updateOverlayPanel() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Updates the status/selection of widgets on the overlay panel

updatePanel() - Method in class weka.classifiers.timeseries.gui.AdvancedConfigPanel

Updates various enabled/selected status of widgets based on the current configuration

useDefaultVisual() - Method in class weka.gui.beans.TimeSeriesForecasting

Use the default images for a data source

usesState() - Method in interface weka.classifiers.timeseries.TSForecaster

Check whether the base learner requires operations regarding state

usesState() - Method in class weka.classifiers.timeseries.WekaForecaster

Check whether the base learner requires operations regarding state

Utils - Class in weka.classifiers.timeseries.core

Static utility routines.

Utils() - Constructor for class weka.classifiers.timeseries.core.Utils

V

valueOf(String) - Static method in enum weka.classifiers.timeseries.core.CustomPeriodicTest.Operator

Returns the enum constant of this type with the specified name.

valueOf(String) - Static method in enum weka.filters.supervised.attribute.TSLagMaker.Periodicity

Returns the enum constant of this type with the specified name.

values() - Static method in enum weka.classifiers.timeseries.core.CustomPeriodicTest.Operator

Returns an array containing the constants of this enum type, in the order they are declared.

values() - Static method in enum weka.filters.supervised.attribute.TSLagMaker.Periodicity

Returns an array containing the constants of this enum type, in the order they are declared.

valueSmoothingFactorTipText() - Method in class weka.classifiers.timeseries.HoltWinters

Tip text for this property

W

weka.classifiers.timeseries - package weka.classifiers.timeseries

weka.classifiers.timeseries.core - package weka.classifiers.timeseries.core

weka.classifiers.timeseries.eval - package weka.classifiers.timeseries.eval

weka.classifiers.timeseries.eval.graph - package weka.classifiers.timeseries.eval.graph

weka.classifiers.timeseries.gui - package weka.classifiers.timeseries.gui

weka.classifiers.timeseries.gui.explorer - package weka.classifiers.timeseries.gui.explorer

weka.filters.supervised.attribute - package weka.filters.supervised.attribute

weka.gui.beans - package weka.gui.beans

weka.gui.knowledgeflow - package weka.gui.knowledgeflow

weka.gui.knowledgeflow.steps - package weka.gui.knowledgeflow.steps

weka.knowledgeflow.steps - package weka.knowledgeflow.steps

WekaForecaster - Class in weka.classifiers.timeseries

Class that implements time series forecasting using a Weka regression scheme.

WekaForecaster() - Constructor for class weka.classifiers.timeseries.WekaForecaster

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