Package elki.evaluation.clustering

Class ClusterContingencyTable

java.lang.Object

elki.evaluation.clustering.ClusterContingencyTable

public class ClusterContingencyTable
extends java.lang.Object

Class storing the contingency table and related data on two clusterings.

Since:

0.5.0

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field	Description
protected BCubed	bcubed	BCubed measures
protected boolean	breakNoiseClusters	Noise cluster handling
protected int[][]	contingency	Contingency matrix
protected EditDistance	edit	Edit-Distance measures
protected Entropy	entropy	Entropy-based measures
protected MaximumMatchingAccuracy	mmacc	Maximum Matching Accuracy
protected long[]	noise1	Noise flags
protected long[]	noise2	Noise flags
protected PairCounting	paircount	Pair counting measures
protected PairSetsIndex	psi	Pair Sets Index Measures
protected boolean	selfPairing	Self pairing
protected int	size1	Number of clusters.
protected int	size2	Number of clusters.
protected SetMatchingPurity	smp	Set matching purity measures

Constructor Summary

Constructors

Constructor	Description
ClusterContingencyTable(boolean selfPairing, boolean breakNoiseClusters, Clustering<?> result1, Clustering<?> result2)	Constructor.

Method Summary

Modifier and Type	Method	Description
MeanVariance	adjustedSymmetricGini()	Compute the adjusted average Gini for each cluster (in both clusterings - symmetric).
MeanVariance	averageSymmetricGini()	Compute the average Gini for each cluster (in both clusterings - symmetric).
BCubed	getBCubed()	The BCubed based measures
EditDistance	getEdit()	Get (compute) the edit-distance based measures
Entropy	getEntropy()	Get (compute) the entropy based measures
MaximumMatchingAccuracy	getMaximumMatchingAccuracy()	The Maximum Matching Accuracy
PairCounting	getPaircount()	Get (compute) the pair counting measures.
PairSetsIndex	getPairSetsIndex()	The Pair Sets Index measures
SetMatchingPurity	getSetMatchingPurity()	The set-matching purity measures
boolean	isStrictPartitioning()	Check whether the marginal cluster sizes both sum to the total size.
java.lang.String	toString()

Methods inherited from class java.lang.Object

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

Field Detail

breakNoiseClusters

protected boolean breakNoiseClusters

Noise cluster handling

selfPairing

protected boolean selfPairing

Self pairing

size1

protected int size1

Number of clusters.

size2

protected int size2

Number of clusters.

contingency

protected int[][] contingency

Contingency matrix

noise1

protected long[] noise1

Noise flags

noise2

protected long[] noise2

Noise flags

paircount

protected PairCounting paircount

Pair counting measures

entropy

protected Entropy entropy

Entropy-based measures

smp

protected SetMatchingPurity smp

Set matching purity measures

mmacc

protected MaximumMatchingAccuracy mmacc

Maximum Matching Accuracy

psi

protected PairSetsIndex psi

Pair Sets Index Measures

edit

protected EditDistance edit

Edit-Distance measures

bcubed

protected BCubed bcubed

BCubed measures

Constructor Detail

ClusterContingencyTable

public ClusterContingencyTable(boolean selfPairing,
                               boolean breakNoiseClusters,
                               Clustering<?> result1,
                               Clustering<?> result2)

Constructor.

Parameters:

selfPairing - Build self-pairs

breakNoiseClusters - Break noise clusters into individual objects

result1 - First clustering

result2 - Second clustering

Method Detail

isStrictPartitioning

public boolean isStrictPartitioning()

Check whether the marginal cluster sizes both sum to the total size.

Returns:

true when the clustering is a non-overlapping complete partitioning of the data set

toString

public java.lang.String toString()

Overrides:

toString in class java.lang.Object

getPaircount

public PairCounting getPaircount()

Get (compute) the pair counting measures.

Returns:

Pair counting measures

getEntropy

public Entropy getEntropy()

Get (compute) the entropy based measures

Returns:

Entropy based measures

getEdit

public EditDistance getEdit()

Get (compute) the edit-distance based measures

Returns:

Edit-distance based measures

getBCubed

public BCubed getBCubed()

The BCubed based measures

Returns:

BCubed measures

getSetMatchingPurity

public SetMatchingPurity getSetMatchingPurity()

The set-matching purity measures

Returns:

Set-Matching purity measures

getMaximumMatchingAccuracy

public MaximumMatchingAccuracy getMaximumMatchingAccuracy()

The Maximum Matching Accuracy

Returns:

Maximum Matching Accuracy

getPairSetsIndex

public PairSetsIndex getPairSetsIndex()

The Pair Sets Index measures

Returns:

Pair Sets Index measures

averageSymmetricGini

public MeanVariance averageSymmetricGini()

Compute the average Gini for each cluster (in both clusterings - symmetric).

Returns:

Mean and variance of Gini

adjustedSymmetricGini

public MeanVariance adjustedSymmetricGini()

Compute the adjusted average Gini for each cluster (in both clusterings - symmetric).

Returns:

Mean and variance of Gini