weka.clusterers

Class AbstractDensityBasedClusterer

java.lang.Object

weka.clusterers.AbstractClusterer

weka.clusterers.AbstractDensityBasedClusterer

All Implemented Interfaces:

java.io.Serializable, java.lang.Cloneable, Clusterer, DensityBasedClusterer, CapabilitiesHandler, CapabilitiesIgnorer, CommandlineRunnable, OptionHandler, RevisionHandler

Direct Known Subclasses:

MakeDensityBasedClusterer, RandomizableDensityBasedClusterer

public abstract class AbstractDensityBasedClusterer
extends AbstractClusterer
implements DensityBasedClusterer

Abstract clustering model that produces (for each test instance) an estimate of the membership in each cluster (ie. a probability distribution).

Version:

$Revision: 8034 $

Author:

Mark Hall (mhall@cs.waikato.ac.nz), Eibe Frank (eibe@cs.waikato.ac.nz)

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractDensityBasedClusterer()

Method Summary

Modifier and Type	Method and Description
abstract double[]	clusterPriors() Returns the prior probability of each cluster.
double[]	distributionForInstance(Instance instance) Returns the cluster probability distribution for an instance.
double	logDensityForInstance(Instance instance) Computes the density for a given instance.
abstract double[]	logDensityPerClusterForInstance(Instance instance) Computes the log of the conditional density (per cluster) for a given instance.
double[]	logJointDensitiesForInstance(Instance inst) Returns the logs of the joint densities for a given instance.
static DensityBasedClusterer[]	makeCopies(DensityBasedClusterer model, int num) Creates copies of the current clusterer.

Methods inherited from class weka.clusterers.AbstractClusterer

buildClusterer, clusterInstance, debugTipText, doNotCheckCapabilitiesTipText, forName, getCapabilities, getDebug, getDoNotCheckCapabilities, getOptions, getRevision, listOptions, makeCopies, makeCopy, numberOfClusters, postExecution, preExecution, run, runClusterer, setDebug, setDoNotCheckCapabilities, setOptions

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface weka.clusterers.Clusterer

buildClusterer, clusterInstance, getCapabilities, numberOfClusters

Methods inherited from interface weka.core.OptionHandler

makeCopy

Constructor Detail

AbstractDensityBasedClusterer

public AbstractDensityBasedClusterer()

Method Detail

clusterPriors

public abstract double[] clusterPriors()
                                throws java.lang.Exception

Returns the prior probability of each cluster.

Specified by:

clusterPriors in interface DensityBasedClusterer

Returns:

the prior probability for each cluster

Throws:

java.lang.Exception - if priors could not be returned successfully

logDensityPerClusterForInstance

public abstract double[] logDensityPerClusterForInstance(Instance instance)
                                                  throws java.lang.Exception

Computes the log of the conditional density (per cluster) for a given instance.

Specified by:

logDensityPerClusterForInstance in interface DensityBasedClusterer

Parameters:

instance - the instance to compute the density for

Returns:

an array containing the estimated densities

Throws:

java.lang.Exception - if the density could not be computed successfully

logDensityForInstance

public double logDensityForInstance(Instance instance)
                             throws java.lang.Exception

Computes the density for a given instance.

Specified by:

logDensityForInstance in interface DensityBasedClusterer

Parameters:

instance - the instance to compute the density for

Returns:

the density.

Throws:

java.lang.Exception - if the density could not be computed successfully

distributionForInstance

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

Returns the cluster probability distribution for an instance.

Specified by:

distributionForInstance in interface Clusterer

Specified by:

distributionForInstance in interface DensityBasedClusterer

Overrides:

distributionForInstance in class AbstractClusterer

Parameters:

instance - the instance to be clustered

Returns:

the probability distribution

Throws:

java.lang.Exception - if computation fails

logJointDensitiesForInstance

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

Returns the logs of the joint densities for a given instance.

Specified by:

logJointDensitiesForInstance in interface DensityBasedClusterer

Parameters:

inst - the instance

Returns:

the array of values

Throws:

java.lang.Exception - if values could not be computed

makeCopies

public static DensityBasedClusterer[] makeCopies(DensityBasedClusterer model,
                                                 int num)
                                          throws java.lang.Exception

Creates copies of the current clusterer. Note that this method now uses Serialization to perform a deep copy, so the Clusterer object must be fully Serializable. Any currently built model will now be copied as well.

Parameters:

model - an example clusterer to copy

num - the number of clusterer copies to create.

Returns:

an array of clusterers.

Throws:

java.lang.Exception - if an error occurs