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:

java.io.Serializable, java.lang.Cloneable, Classifier, BatchPredictor, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, 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.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected Instances	m_data training data

Fields inherited from class weka.classifiers.RandomizableParallelIteratedSingleClassifierEnhancer

m_Seed

Fields inherited from class weka.classifiers.ParallelIteratedSingleClassifierEnhancer

m_numExecutionSlots

Fields inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

m_Classifiers, m_NumIterations

Fields inherited from class weka.classifiers.SingleClassifierEnhancer

m_Classifier

Fields inherited from class weka.classifiers.AbstractClassifier

BATCH_SIZE_DEFAULT, m_BatchSize, m_Debug, m_DoNotCheckCapabilities, m_numDecimalPlaces, NUM_DECIMAL_PLACES_DEFAULT

Constructor Summary

Constructors

Constructor and Description
RandomCommittee() Constructor.

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(Instances data) Builds the committee of randomizable classifiers.
protected java.lang.String	defaultClassifierString() String describing default classifier.
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
java.lang.String	getRevision() Returns the revision string.
protected Instances	getTrainingSet(int iteration) Returns a training set for a particular iteration.
java.lang.String	globalInfo() Returns a string describing classifier
static void	main(java.lang.String[] argv) Main method for testing this class.
int	numElements() Returns the number of elements in the partition.
java.lang.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

buildClassifiers, getNumExecutionSlots, numExecutionSlotsTipText, setNumExecutionSlots

Methods inherited from class weka.classifiers.IteratedSingleClassifierEnhancer

defaultNumberOfIterations, getM_Classifiers, getNumIterations, numIterationsTipText, setNumIterations

Methods inherited from class weka.classifiers.SingleClassifierEnhancer

classifierTipText, defaultClassifierOptions, getCapabilities, getClassifier, getClassifierSpec, postExecution, preExecution, setClassifier

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, classifyInstance, debugTipText, distributionsForInstances, doNotCheckCapabilitiesTipText, forName, getBatchSize, getDebug, getDoNotCheckCapabilities, getNumDecimalPlaces, implementsMoreEfficientBatchPrediction, makeCopies, makeCopy, numDecimalPlacesTipText, run, runClassifier, setBatchSize, setDebug, setDoNotCheckCapabilities, setNumDecimalPlaces

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface weka.core.CapabilitiesHandler

getCapabilities

Field Detail

m_data

protected Instances m_data

training data

Constructor Detail

RandomCommittee

public RandomCommittee()

Constructor.

Method Detail

defaultClassifierString

protected java.lang.String defaultClassifierString()

String describing default classifier.

Overrides:

defaultClassifierString in class SingleClassifierEnhancer

Returns:

the default classifier classname

globalInfo

public java.lang.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 java.lang.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:

java.lang.Exception - if the classifier could not be built successfully

getTrainingSet

protected Instances getTrainingSet(int iteration)
                            throws java.lang.Exception

Returns a training set for a particular iteration.

Specified by:

getTrainingSet in class ParallelIteratedSingleClassifierEnhancer

Parameters:

iteration - the number of the iteration for the requested training set.

Returns:

the training set for the supplied iteration number

Throws:

java.lang.Exception - if something goes wrong when generating a training set.

distributionForInstance

public double[] distributionForInstance(Instance instance)
                                 throws java.lang.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:

java.lang.Exception - if distribution can't be computed successfully

toString

public java.lang.String toString()

Returns description of the committee.

Overrides:

toString in class java.lang.Object

Returns:

description of the committee as a string

generatePartition

public void generatePartition(Instances data)
                       throws java.lang.Exception

Builds the classifier to generate a partition.

Specified by:

generatePartition in interface PartitionGenerator

Throws:

java.lang.Exception

getMembershipValues

public double[] getMembershipValues(Instance inst)
                             throws java.lang.Exception

Computes an array that indicates leaf membership

Specified by:

getMembershipValues in interface PartitionGenerator

Throws:

java.lang.Exception

numElements

public int numElements()
                throws java.lang.Exception

Returns the number of elements in the partition.

Specified by:

numElements in interface PartitionGenerator

Throws:

java.lang.Exception

getRevision

public java.lang.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(java.lang.String[] argv)

Main method for testing this class.

Parameters:

argv - the options