moa.classifiers.multilabel

Class MultilabelHoeffdingTree

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.classifiers.AbstractClassifier

moa.classifiers.trees.HoeffdingTree

moa.classifiers.multilabel.HoeffdingTreeClassifLeaves

moa.classifiers.multilabel.MultilabelHoeffdingTree

All Implemented Interfaces:

Serializable, Classifier, AWTRenderable, MOAObject, OptionHandler

public class MultilabelHoeffdingTree
extends HoeffdingTreeClassifLeaves

Hoeffding Tree for classifying multi-label data. A Hoeffding tree is an incremental, anytime decision tree induction algorithm that is capable of learning from massive data streams, assuming that the distribution generating examples does not change over time.

See Also:

Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	MultilabelHoeffdingTree.MultilabelInactiveLearningNode
class	MultilabelHoeffdingTree.MultilabelLearningNodeClassifier

Nested classes/interfaces inherited from class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves

HoeffdingTreeClassifLeaves.LearningNodeClassifier

Nested classes/interfaces inherited from class moa.classifiers.trees.HoeffdingTree

HoeffdingTree.ActiveLearningNode, HoeffdingTree.FoundNode, HoeffdingTree.InactiveLearningNode, HoeffdingTree.LearningNode, HoeffdingTree.LearningNodeNB, HoeffdingTree.LearningNodeNBAdaptive, HoeffdingTree.Node, HoeffdingTree.SplitNode

Field Summary

Fields

Modifier and Type	Field and Description
protected Converter	converter
int	m_L

Fields inherited from class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves

learnerOption

Fields inherited from class moa.classifiers.trees.HoeffdingTree

activeLeafByteSizeEstimate, activeLeafNodeCount, binarySplitsOption, byteSizeEstimateOverheadFraction, decisionNodeCount, gracePeriodOption, growthAllowed, inactiveLeafByteSizeEstimate, inactiveLeafNodeCount, leafpredictionOption, maxByteSizeOption, memoryEstimatePeriodOption, nbThresholdOption, nominalEstimatorOption, noPrePruneOption, numericEstimatorOption, removePoorAttsOption, splitConfidenceOption, splitCriterionOption, stopMemManagementOption, tieThresholdOption, treeRoot

Fields inherited from class moa.classifiers.AbstractClassifier

classifierRandom, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel

Fields inherited from class moa.options.AbstractOptionHandler

classOptionNamesToPreparedObjects, options

Constructor Summary

Constructors

Constructor and Description
MultilabelHoeffdingTree()

Method Summary

Methods

Modifier and Type	Method and Description
protected void	deactivateLearningNode(HoeffdingTree.ActiveLearningNode toDeactivate, HoeffdingTree.SplitNode parent, int parentBranch)
double[]	getVotesForInstance(weka.core.Instance inst) Predicts the class memberships for a given instance.
protected HoeffdingTree.LearningNode	newLearningNode(double[] initialClassObservations)
protected HoeffdingTree.LearningNode	newLearningNode(double[] initialClassObservations, Classifier cl)
void	setModelContext(InstancesHeader raw_header) Sets the reference to the header of the data stream.

Methods inherited from class moa.classifiers.multilabel.HoeffdingTreeClassifLeaves

attemptToSplit

Methods inherited from class moa.classifiers.trees.HoeffdingTree

activateLearningNode, calcByteSize, computeHoeffdingBound, deactivateAllLeaves, enforceTrackerLimit, estimateModelByteSizes, findLearningNodes, findLearningNodes, getModelDescription, getModelMeasurementsImpl, getPurposeString, isRandomizable, measureByteSize, measureTreeDepth, newLearningNode, newNominalClassObserver, newNumericClassObserver, newSplitNode, newSplitNode, resetLearningImpl, trainOnInstanceImpl

Methods inherited from class moa.classifiers.AbstractClassifier

contextIsCompatible, copy, correctlyClassifies, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModelContext, getModelMeasurements, getNominalValueString, getSubClassifiers, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, resetLearning, setRandomSeed, trainingHasStarted, trainingWeightSeenByModel, trainOnInstance

Methods inherited from class moa.options.AbstractOptionHandler

discoverOptionsViaReflection, getCLICreationString, getOptions, getPreparedClassOption, getPreparedClassOption, prepareClassOptions, prepareForUse, prepareForUse

Methods inherited from class moa.AbstractMOAObject

copy, measureByteSize, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface moa.options.OptionHandler

getCLICreationString, getOptions, prepareForUse, prepareForUse

Field Detail

m_L

public int m_L

converter

protected Converter converter

Constructor Detail

MultilabelHoeffdingTree

public MultilabelHoeffdingTree()

Method Detail

setModelContext

public void setModelContext(InstancesHeader raw_header)

Description copied from interface: Classifier

Sets the reference to the header of the data stream. The header of the data stream is extended from WEKA Instances. This header is needed to know the number of classes and attributes

Specified by:

setModelContext in interface Classifier

Overrides:

setModelContext in class AbstractClassifier

Parameters:

raw_header - the reference to the data stream header

newLearningNode

protected HoeffdingTree.LearningNode newLearningNode(double[] initialClassObservations)

Overrides:

newLearningNode in class HoeffdingTreeClassifLeaves

newLearningNode

protected HoeffdingTree.LearningNode newLearningNode(double[] initialClassObservations,
                                         Classifier cl)

Overrides:

newLearningNode in class HoeffdingTreeClassifLeaves

deactivateLearningNode

protected void deactivateLearningNode(HoeffdingTree.ActiveLearningNode toDeactivate,
                          HoeffdingTree.SplitNode parent,
                          int parentBranch)

Overrides:

deactivateLearningNode in class HoeffdingTree

getVotesForInstance

public double[] getVotesForInstance(weka.core.Instance inst)

Description copied from interface: Classifier

Predicts the class memberships for a given instance. If an instance is unclassified, the returned array elements must be all zero.

Specified by:

getVotesForInstance in interface Classifier

Overrides:

getVotesForInstance in class HoeffdingTree

Parameters:

inst - the instance to be classified

Returns:

an array containing the estimated membership probabilities of the test instance in each class