ai.libs.jaicore.ml.tsc.classifier.ensemble

Class MajorityConfidenceVote

java.lang.Object

weka.classifiers.AbstractClassifier

weka.classifiers.MultipleClassifiersCombiner

weka.classifiers.RandomizableMultipleClassifiersCombiner

weka.classifiers.meta.Vote

ai.libs.jaicore.ml.tsc.classifier.ensemble.MajorityConfidenceVote

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, weka.classifiers.Classifier, weka.core.Aggregateable<weka.classifiers.Classifier>, weka.core.BatchPredictor, weka.core.CapabilitiesHandler, weka.core.CapabilitiesIgnorer, weka.core.CommandlineRunnable, weka.core.EnvironmentHandler, weka.core.OptionHandler, weka.core.Randomizable, weka.core.RevisionHandler, weka.core.TechnicalInformationHandler

public class MajorityConfidenceVote
extends weka.classifiers.meta.Vote

Vote implementation for majority confidence. The ensemble's distributions of each classifier are aggregated using the sum of each unique values times classifier weights. The classifier weights are determined during training using a CV.

See Also:

Serialized Form

Field Summary

Fields inherited from class weka.classifiers.meta.Vote

AVERAGE_RULE, m_classifiersToLoad, m_CombinationRule, m_dontPrintModels, m_env, m_preBuiltClassifiers, m_structure, MAJORITY_VOTING_RULE, MAX_RULE, MEDIAN_RULE, MIN_RULE, PRODUCT_RULE, TAGS_RULES

Fields inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner

m_Seed

Fields inherited from class weka.classifiers.MultipleClassifiersCombiner

m_Classifiers

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
MajorityConfidenceVote(int numFolds, int seed) Constructor for a majority confidence vote ensemble classifier.

Method Summary

Modifier and Type	Method and Description
void	buildClassifier(weka.core.Instances data) Builds the ensemble by assessing the classifier weights using a cross validation of each classifier of the ensemble and then training the classifiers using the complete data.
double	classifyInstance(weka.core.Instance instance)
double[]	distributionForInstance(weka.core.Instance instance) Function calculating the distribution for a instance by predicting the distributions for each classifier and multiplying the result by the classifier weights.

Methods inherited from class weka.classifiers.meta.Vote

addPreBuiltClassifier, aggregate, classifyInstanceMedian, combinationRuleTipText, distributionForInstanceAverage, distributionForInstanceMajorityVoting, distributionForInstanceMax, distributionForInstanceMin, distributionForInstanceProduct, doNotPrintModelsTipText, finalizeAggregation, getCapabilities, getCombinationRule, getDoNotPrintModels, getOptions, getPreBuiltClassifiers, getRevision, getTechnicalInformation, globalInfo, listOptions, main, preBuiltClassifiersTipText, removePreBuiltClassifier, setCombinationRule, setDoNotPrintModels, setEnvironment, setOptions, setPreBuiltClassifiers, toString

Methods inherited from class weka.classifiers.RandomizableMultipleClassifiersCombiner

getSeed, seedTipText, setSeed

Methods inherited from class weka.classifiers.MultipleClassifiersCombiner

classifiersTipText, getClassifier, getClassifiers, getClassifierSpec, postExecution, preExecution, setClassifiers

Methods inherited from class weka.classifiers.AbstractClassifier

batchSizeTipText, 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

Constructor Detail

MajorityConfidenceVote

public MajorityConfidenceVote(int numFolds,
                              int seed)

Constructor for a majority confidence vote ensemble classifier.

Parameters:

numFolds - See numFolds

seed - See seed

Method Detail

buildClassifier

public void buildClassifier(weka.core.Instances data)
                     throws java.lang.Exception

Builds the ensemble by assessing the classifier weights using a cross validation of each classifier of the ensemble and then training the classifiers using the complete data.

Specified by:

buildClassifier in interface weka.classifiers.Classifier

Overrides:

buildClassifier in class weka.classifiers.meta.Vote

Parameters:

data - Training instances

Throws:

java.lang.Exception

distributionForInstance

public double[] distributionForInstance(weka.core.Instance instance)
                                 throws java.lang.Exception

Function calculating the distribution for a instance by predicting the distributions for each classifier and multiplying the result by the classifier weights. The final result is the sum of each probabilities for each class.

Specified by:

distributionForInstance in interface weka.classifiers.Classifier

Overrides:

distributionForInstance in class weka.classifiers.meta.Vote

Parameters:

instace - Instance to be predicted

Returns:

Returns the final probability distribution for each class for the given instance

Throws:

java.lang.Exception

classifyInstance

public double classifyInstance(weka.core.Instance instance)
                        throws java.lang.Exception

Specified by:

classifyInstance in interface weka.classifiers.Classifier

Overrides:

classifyInstance in class weka.classifiers.meta.Vote

Throws:

java.lang.Exception