weka.classifiers.meta
Class RandomCommittee

java.lang.Object
  weka.classifiers.AbstractClassifier
      weka.classifiers.SingleClassifierEnhancer
          weka.classifiers.IteratedSingleClassifierEnhancer
              weka.classifiers.ParallelIteratedSingleClassifierEnhancer
                  weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer
                      weka.classifiers.meta.RandomCommittee

All Implemented Interfaces:

Serializable, Cloneable, Classifier, CapabilitiesHandler, OptionHandler, PartitionGenerator, Randomizable, RevisionHandler, WeightedInstancesHandler

public class RandomCommittee
extends RandomizableParallelIteratedSingleClassifierEnhancer
implements WeightedInstancesHandler, PartitionGenerator

Class for building an ensemble of randomizable base classifiers. Each base classifiers is built using a different random number seed (but based one the same data). The final prediction is a straight average of the predictions generated by the individual base classifiers.

Valid options are:

 -S <num>
  Random number seed.
  (default 1)

 -I <num>
  Number of iterations.
  (default 10)

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

 -W
  Full name of base classifier.
  (default: weka.classifiers.trees.RandomTree)

 
 Options specific to classifier weka.classifiers.trees.RandomTree:
 

 -K <number of attributes>
  Number of attributes to randomly investigate
  (<1 = int(log(#attributes)+1)).

 -M <minimum number of instances>
  Set minimum number of instances per leaf.

 -S <num>
  Seed for random number generator.
  (default 1)

 -depth <num>
  The maximum depth of the tree, 0 for unlimited.
  (default 0)

 -D
  If set, classifier is run in debug mode and
  may output additional info to the console

Options after -- are passed to the designated classifier.

Version:

$Revision: 9317 $

Author:

Eibe Frank ([email protected])

See Also:

Serialized Form

Constructor Summary

RandomCommittee()
Constructor.

Method Summary

void	buildClassifier(Instances data) Builds the committee of randomizable classifiers.
double[]	distributionForInstance(Instance instance) Calculates the class membership probabilities for the given test instance.
void	generatePartition(Instances data) Builds the classifier to generate a partition.
double[]	getMembershipValues(Instance inst) Computes an array that indicates leaf membership
String	getRevision() Returns the revision string.
String	globalInfo() Returns a string describing classifier
static void	main(String[] argv) Main method for testing this class.
int	numElements() Returns the number of elements in the partition.
String	toString() Returns description of the committee.

Methods inherited from class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

getOptions, getSeed, listOptions, seedTipText, setOptions, setSeed

Methods inherited from class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

getNumExecutionSlots, numExecutionSlotsTipText, setNumExecutionSlots

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

getNumIterations, numIterationsTipText, setNumIterations

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, getCapabilities, getClassifier, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

classifyInstance, debugTipText, forName, getDebug, makeCopies, makeCopy, runClassifier, setDebug

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.CapabilitiesHandler

getCapabilities

Constructor Detail

RandomCommittee

public RandomCommittee()

Constructor.

Method Detail

globalInfo

public String globalInfo()

Returns a string describing classifier

Returns:

a description suitable for displaying in the explorer/experimenter gui

buildClassifier

public void buildClassifier(Instances data)
                     throws Exception

Builds the committee of randomizable classifiers.

Specified by:

buildClassifier in interface Classifier

Overrides:

buildClassifier in class ParallelIteratedSingleClassifierEnhancer

Parameters:

data - the training data to be used for generating the bagged classifier.

Throws:

Exception - if the classifier could not be built successfully

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws Exception

Calculates the class membership probabilities for the given test instance.

Specified by:

distributionForInstance in interface Classifier

Overrides:

distributionForInstance in class AbstractClassifier

Parameters:

instance - the instance to be classified

Returns:

preedicted class probability distribution

Throws:

Exception - if distribution can't be computed successfully

toString

public String toString()

Returns description of the committee.

Overrides:

toString in class Object

Returns:

description of the committee as a string

generatePartition

public void generatePartition(Instances data)
                       throws Exception

Builds the classifier to generate a partition.

Specified by:

generatePartition in interface PartitionGenerator

Throws:

Exception

getMembershipValues

public double[] getMembershipValues(Instance inst)
                             throws Exception

Computes an array that indicates leaf membership

Specified by:

getMembershipValues in interface PartitionGenerator

Throws:

Exception

numElements

public int numElements()
                throws Exception

Returns the number of elements in the partition.

Specified by:

numElements in interface PartitionGenerator

Throws:

Exception

getRevision

public String getRevision()

Returns the revision string.

Specified by:

getRevision in interface RevisionHandler

Overrides:

getRevision in class AbstractClassifier

Returns:

the revision

main

public static void main(String[] argv)

Main method for testing this class.

Parameters:

argv - the options