moa.clusterers.streamkm

Class StreamKM

java.lang.Object

moa.AbstractMOAObject

moa.options.AbstractOptionHandler

moa.clusterers.AbstractClusterer

moa.clusterers.streamkm.StreamKM

All Implemented Interfaces:

Serializable, Clusterer, AWTRenderable, MOAObject, OptionHandler

public class StreamKM
extends AbstractClusterer

Author:

Marcel R. Ackermann, Christiane Lammersen, Marcus Maertens, Christoph Raupach, Christian Sohler, Kamil Swierkot Citation: Marcel R. Ackermann, Christiane Lammersen, Marcus Märtens, Christoph Raupach, Christian Sohler, Kamil Swierkot: StreamKM++: A Clustering Algorithms for Data Streams. ALENEX 2010: 173-187

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected Point[]	centresStreamingCoreset
protected MTRandom	clustererRandom
protected int	coresetsize
protected int	dimension
protected boolean	initialized
protected int	length
protected BucketManager	manager
protected int	numberInstances
protected int	numberOfCentres
IntOption	numClustersOption
IntOption	randomSeedOption
IntOption	sizeCoresetOption
IntOption	widthOption

Fields inherited from class moa.clusterers.AbstractClusterer

clustering, evaluateMicroClusteringOption, modelContext, randomSeed, trainingWeightSeenByModel

Fields inherited from class moa.options.AbstractOptionHandler

classOptionNamesToPreparedObjects, options

Constructor Summary

Constructors

Constructor and Description
StreamKM()

Method Summary

Methods

Modifier and Type	Method and Description
Clustering	getClusteringResult()
void	getModelDescription(StringBuilder out, int indent)
protected Measurement[]	getModelMeasurementsImpl()
double[]	getVotesForInstance(weka.core.Instance inst)
boolean	isRandomizable()
double	lloydPlusPlus(int k, int n, int d, Point[] points, Point[] centres)
void	resetLearningImpl()
double	targetFunctionValue(int k, int n, Point[] centres, Point[] points) computes the target function for the given pointarray points[] (of size n) with the given array of centres centres[] (of size k)
void	trainOnInstanceImpl(weka.core.Instance inst)

Methods inherited from class moa.clusterers.AbstractClusterer

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

sizeCoresetOption

public IntOption sizeCoresetOption

numClustersOption

public IntOption numClustersOption

widthOption

public IntOption widthOption

randomSeedOption

public IntOption randomSeedOption

clustererRandom

protected MTRandom clustererRandom

centresStreamingCoreset

protected Point[] centresStreamingCoreset

numberInstances

protected int numberInstances

dimension

protected int dimension

length

protected int length

numberOfCentres

protected int numberOfCentres

coresetsize

protected int coresetsize

manager

protected BucketManager manager

initialized

protected boolean initialized

Constructor Detail

StreamKM

public StreamKM()

Method Detail

resetLearningImpl

public void resetLearningImpl()

Specified by:

resetLearningImpl in class AbstractClusterer

trainOnInstanceImpl

public void trainOnInstanceImpl(weka.core.Instance inst)

Specified by:

trainOnInstanceImpl in class AbstractClusterer

getModelMeasurementsImpl

protected Measurement[] getModelMeasurementsImpl()

Specified by:

getModelMeasurementsImpl in class AbstractClusterer

getModelDescription

public void getModelDescription(StringBuilder out,
                       int indent)

Specified by:

getModelDescription in class AbstractClusterer

isRandomizable

public boolean isRandomizable()

getVotesForInstance

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

getClusteringResult

public Clustering getClusteringResult()

lloydPlusPlus

public double lloydPlusPlus(int k,
                   int n,
                   int d,
                   Point[] points,
                   Point[] centres)

targetFunctionValue

public double targetFunctionValue(int k,
                         int n,
                         Point[] centres,
                         Point[] points)

computes the target function for the given pointarray points[] (of size n) with the given array of centres centres[] (of size k)