moa.clusterers.outliers.AnyOut

Class AnyOutCore

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.clusterers.AbstractClusterer

moa.clusterers.clustree.ClusTree

moa.clusterers.outliers.AnyOut.AnyOutCore

All Implemented Interfaces:

Serializable, Clusterer, AWTRenderable, MOAObject, OptionHandler

public class AnyOutCore
extends ClusTree

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
IntOption	confidenceChoiceOption
IntOption	confKOption
IntOption	oScoreKOption
FloatOption	threshholdOption
IntOption	trainingSetSizeOption
FlagOption	UseMeanScoreOption

Fields inherited from class moa.clusterers.clustree.ClusTree

breadthFirstStrat, horizonOption, maxHeight, maxHeightOption, negLambda, root

Fields inherited from class moa.clusterers.AbstractClusterer

clustererRandom, clustering, evaluateMicroClusteringOption, modelContext, randomSeed, randomSeedOption, trainingWeightSeenByModel

Fields inherited from class moa.options.AbstractOptionHandler

classOptionNamesToPreparedObjects, options

Constructor Summary

Constructors

Constructor and Description
AnyOutCore()

Method Summary

Methods

Modifier and Type	Method and Description
double	getConfidence(int id)
double	getOutlierScore(int id)
void	improveObjectOnce(int objectId)
void	initObject(int objectId, double[] features)
boolean	isOutlier(int id)
void	learnObject(double[] features)
boolean	moreImprovementsPossible(int objectId, double depthPercentage)
void	removeObject(int objectId)
void	resetLearning()
void	train(DataSet trainingSet)

Methods inherited from class moa.clusterers.clustree.ClusTree

getClustering, getClusteringResult, getDefaultHeight, getHeight, getMicroClusteringResult, getModelDescription, getModelMeasurementsImpl, getNumRootSplits, getVotesForInstance, implementsMicroClusterer, insert, isRandomizable, resetLearningImpl, trainOnInstanceImpl

Methods inherited from class moa.clusterers.AbstractClusterer

contextIsCompatible, copy, getAttributeNameString, getAWTRenderer, getClassLabelString, getClassNameString, getDescription, getModelContext, getModelMeasurements, getNominalValueString, getPurposeString, getSubClusterers, keepClassLabel, modelAttIndexToInstanceAttIndex, modelAttIndexToInstanceAttIndex, prepareForUseImpl, setModelContext, 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, 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

Methods inherited from interface moa.MOAObject

measureByteSize

Field Detail

trainingSetSizeOption

public IntOption trainingSetSizeOption

oScoreKOption

public IntOption oScoreKOption

confKOption

public IntOption confKOption

confidenceChoiceOption

public IntOption confidenceChoiceOption

UseMeanScoreOption

public FlagOption UseMeanScoreOption

threshholdOption

public FloatOption threshholdOption

Constructor Detail

AnyOutCore

public AnyOutCore()

Method Detail

resetLearning

public void resetLearning()

Specified by:

resetLearning in interface Clusterer

Overrides:

resetLearning in class AbstractClusterer

train

public void train(DataSet trainingSet)

initObject

public void initObject(int objectId,
              double[] features)

learnObject

public void learnObject(double[] features)

removeObject

public void removeObject(int objectId)

moreImprovementsPossible

public boolean moreImprovementsPossible(int objectId,
                               double depthPercentage)

improveObjectOnce

public void improveObjectOnce(int objectId)

isOutlier

public boolean isOutlier(int id)

getOutlierScore

public double getOutlierScore(int id)

getConfidence

public double getConfidence(int id)