weka.classifiers.meta
Class TestEnsembleClassifier

java.lang.Object
  extended byweka.classifiers.Classifier
      extended byweka.classifiers.DistributionClassifier
          extended byweka.classifiers.EnsembleClassifier
              extended byweka.classifiers.meta.TestEnsembleClassifier
All Implemented Interfaces:
AdditionalMeasureProducer, java.lang.Cloneable, java.io.Serializable

public class TestEnsembleClassifier
extends EnsembleClassifier

This class is for testing Ensemble evaluation

See Also:
Serialized Form

Field Summary
protected  int m_NumIterations
           
protected  java.util.Random random
           
 
Fields inherited from class weka.classifiers.EnsembleClassifier
m_EnsembleWts, m_SumEnsembleWts, m_TrainEnsembleDiversity, m_TrainEnsembleError, m_TrainError
 
Constructor Summary
TestEnsembleClassifier()
           
 
Method Summary
 void buildClassifier(Instances data)
          Generates a classifier.
 double[] distributionForInstance(Instance instance)
          Calculates the class membership probabilities for the given test instance.
 double[] getEnsemblePredictions(Instance instance)
          Returns class predictions of each ensemble member
 double getEnsembleSize()
          Returns size of ensemble
 double[] getEnsembleWts()
          Returns vote weights of ensemble members.
static void main(java.lang.String[] argv)
          Main method for testing this class.
 
Methods inherited from class weka.classifiers.EnsembleClassifier
computeEnsembleMeasures, enumerateMeasures, getMeasure, initMeasures, measureTrainEnsembleDiversity, measureTrainEnsembleError, measureTrainError, updateEnsembleStats
 
Methods inherited from class weka.classifiers.DistributionClassifier
calculateEntropy, calculateLabeledInstanceMargin, calculateMargin, classifyInstance
 
Methods inherited from class weka.classifiers.Classifier
forName, makeCopies
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Field Detail

m_NumIterations

protected int m_NumIterations

random

protected java.util.Random random
Constructor Detail

TestEnsembleClassifier

public TestEnsembleClassifier()
Method Detail

buildClassifier

public void buildClassifier(Instances data)
                     throws java.lang.Exception
Description copied from class: Classifier
Generates a classifier. Must initialize all fields of the classifier that are not being set via options (ie. multiple calls of buildClassifier must always lead to the same result). Must not change the dataset in any way.

Specified by:
buildClassifier in class Classifier
Parameters:
data - the training data to be used for generating the bagged classifier.
Throws:
java.lang.Exception - if the classifier could not be built successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.Exception
Calculates the class membership probabilities for the given test instance.

Specified by:
distributionForInstance in class DistributionClassifier
Parameters:
instance - the instance to be classified
Returns:
preedicted class probability distribution
Throws:
java.lang.Exception - if distribution can't be computed successfully

getEnsemblePredictions

public double[] getEnsemblePredictions(Instance instance)
                                throws java.lang.Exception
Returns class predictions of each ensemble member

Specified by:
getEnsemblePredictions in class EnsembleClassifier
Throws:
java.lang.Exception

getEnsembleWts

public double[] getEnsembleWts()
Returns vote weights of ensemble members.

Specified by:
getEnsembleWts in class EnsembleClassifier
Returns:
vote weights of ensemble members

getEnsembleSize

public double getEnsembleSize()
Returns size of ensemble

Specified by:
getEnsembleSize in class EnsembleClassifier

main

public static void main(java.lang.String[] argv)
Main method for testing this class.

Parameters:
argv - the options