public class WAODE
extends weka.classifiers.AbstractClassifier
implements weka.core.TechnicalInformationHandler
@inproceedings{Jiang2006, author = {L. Jiang and H. Zhang}, booktitle = {Proceedings of the 9th Biennial Pacific Rim International Conference on Artificial Intelligence, PRICAI 2006}, pages = {970-974}, series = {LNAI}, title = {Weightily Averaged One-Dependence Estimators}, volume = {4099}, year = {2006} }Valid options are:
-D If set, classifier is run in debug mode and may output additional info to the console
-I Whether to print some more internals. (default: no)
Constructor and Description |
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WAODE() |
Modifier and Type | Method and Description |
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void |
buildClassifier(weka.core.Instances instances)
Generates the classifier.
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double[] |
distributionForInstance(weka.core.Instance instance)
Calculates the class membership probabilities for the given test instance
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weka.core.Capabilities |
getCapabilities()
Returns default capabilities of the classifier.
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boolean |
getInternals()
Gets whether more internals of the classifier are printed.
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java.lang.String[] |
getOptions()
Gets the current settings of the filter.
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java.lang.String |
getRevision()
Returns the revision string.
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weka.core.TechnicalInformation |
getTechnicalInformation()
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.
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java.lang.String |
globalInfo()
Returns a string describing this classifier
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java.lang.String |
internalsTipText()
Returns the tip text for this property
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java.util.Enumeration |
listOptions()
Gets an enumeration describing the available options.
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static void |
main(java.lang.String[] argv)
Main method for testing this class.
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void |
setInternals(boolean value)
Sets whether internals about classifier are printed via toString().
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void |
setOptions(java.lang.String[] options)
Parses a given list of options.
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java.lang.String |
toString()
returns a string representation of the classifier
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batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, postExecution, preExecution, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces
public java.lang.String globalInfo()
public java.util.Enumeration listOptions()
listOptions
in interface weka.core.OptionHandler
listOptions
in class weka.classifiers.AbstractClassifier
public void setOptions(java.lang.String[] options) throws java.lang.Exception
-D If set, classifier is run in debug mode and may output additional info to the console
-I Whether to print some more internals. (default: no)
setOptions
in interface weka.core.OptionHandler
setOptions
in class weka.classifiers.AbstractClassifier
options
- the list of options as an array of stringsjava.lang.Exception
- if an option is not supportedpublic java.lang.String[] getOptions()
getOptions
in interface weka.core.OptionHandler
getOptions
in class weka.classifiers.AbstractClassifier
public java.lang.String internalsTipText()
public void setInternals(boolean value)
value
- if internals should be printedtoString()
public boolean getInternals()
public weka.core.TechnicalInformation getTechnicalInformation()
getTechnicalInformation
in interface weka.core.TechnicalInformationHandler
public weka.core.Capabilities getCapabilities()
getCapabilities
in interface weka.classifiers.Classifier
getCapabilities
in interface weka.core.CapabilitiesHandler
getCapabilities
in class weka.classifiers.AbstractClassifier
public void buildClassifier(weka.core.Instances instances) throws java.lang.Exception
buildClassifier
in interface weka.classifiers.Classifier
instances
- set of instances serving as training datajava.lang.Exception
- if the classifier has not been generated successfullypublic double[] distributionForInstance(weka.core.Instance instance) throws java.lang.Exception
distributionForInstance
in interface weka.classifiers.Classifier
distributionForInstance
in class weka.classifiers.AbstractClassifier
instance
- the instance to be classifiedjava.lang.Exception
- if there is a problem generating the predictionpublic java.lang.String toString()
toString
in class java.lang.Object
public java.lang.String getRevision()
getRevision
in interface weka.core.RevisionHandler
getRevision
in class weka.classifiers.AbstractClassifier
public static void main(java.lang.String[] argv)
argv
- the commandline options, use -h to list all options