Package elki.similarity.cluster

Class ClusteringAdjustedRandIndexSimilarity

java.lang.Object

elki.similarity.cluster.ClusteringAdjustedRandIndexSimilarity

All Implemented Interfaces:

Distance<Clustering<?>>, PrimitiveDistance<Clustering<?>>, ClusteringDistanceSimilarity, NormalizedSimilarity<Clustering<?>>, PrimitiveSimilarity<Clustering<?>>, Similarity<Clustering<?>>

@Reference(authors="L. Hubert, P. Arabie",
           title="Comparing partitions",
           booktitle="Journal of Classification 2(193)",
           url="https://doi.org/10.1007/BF01908075",
           bibkey="doi:10.1007/BF01908075")
public class ClusteringAdjustedRandIndexSimilarity
extends java.lang.Object
implements ClusteringDistanceSimilarity, NormalizedSimilarity<Clustering<?>>

Measure the similarity of clusters via the Adjusted Rand Index.

References:

L. Hubert, P. Arabie
Comparing partitions.
Journal of Classification 2(193)

W. M. Rand
Objective Criteria for the Evaluation of Clustering Methods
Journal of the American Statistical Association, Vol. 66 Issue 336

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	ClusteringAdjustedRandIndexSimilarity.Par	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
static ClusteringAdjustedRandIndexSimilarity	STATIC	Static instance.

Constructor Summary

Constructors

Constructor	Description
ClusteringAdjustedRandIndexSimilarity()	Constructor - use the static instance STATIC!

Method Summary

Modifier and Type	Method	Description
double	distance(Clustering<?> o1, Clustering<?> o2)	Computes the distance between two given DatabaseObjects according to this distance function.
SimpleTypeInformation<? super Clustering<?>>	getInputTypeRestriction()	Get the input data type of the function.
<T extends Clustering<?>> DistanceSimilarityQuery<T>	instantiate(Relation<T> relation)	Instantiate with a representation to get the actual similarity query.
boolean	isMetric()	Is this distance function metric (satisfy the triangle inequality)
double	similarity(Clustering<?> o1, Clustering<?> o2)	Computes the similarity between two given DatabaseObjects according to this similarity function.

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.similarity.cluster.ClusteringDistanceSimilarity

isSymmetric

Methods inherited from interface elki.distance.Distance

isSquared

Field Detail

STATIC

public static final ClusteringAdjustedRandIndexSimilarity STATIC

Static instance.

Constructor Detail

ClusteringAdjustedRandIndexSimilarity

public ClusteringAdjustedRandIndexSimilarity()

Constructor - use the static instance STATIC!

Method Detail

similarity

public double similarity(Clustering<?> o1,
                         Clustering<?> o2)

Description copied from interface: PrimitiveSimilarity

Computes the similarity between two given DatabaseObjects according to this similarity function.

Specified by:

similarity in interface PrimitiveSimilarity<Clustering<?>>

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the similarity between two given DatabaseObjects according to this similarity function

distance

public double distance(Clustering<?> o1,
                       Clustering<?> o2)

Description copied from interface: PrimitiveDistance

Computes the distance between two given DatabaseObjects according to this distance function.

Specified by:

distance in interface PrimitiveDistance<Clustering<?>>

Parameters:

o1 - first DatabaseObject

o2 - second DatabaseObject

Returns:

the distance between two given DatabaseObjects according to this distance function

isMetric

public boolean isMetric()

Description copied from interface: Distance

Is this distance function metric (satisfy the triangle inequality)

Specified by:

isMetric in interface Distance<Clustering<?>>

Returns:

true when metric.

instantiate

public <T extends Clustering<?>> DistanceSimilarityQuery<T> instantiate(Relation<T> relation)

Description copied from interface: Similarity

Instantiate with a representation to get the actual similarity query.

Specified by:

instantiate in interface ClusteringDistanceSimilarity

Specified by:

instantiate in interface Distance<Clustering<?>>

Specified by:

instantiate in interface PrimitiveDistance<Clustering<?>>

Specified by:

instantiate in interface PrimitiveSimilarity<Clustering<?>>

Specified by:

instantiate in interface Similarity<Clustering<?>>

Parameters:

relation - Representation to use

Returns:

Actual distance query.

getInputTypeRestriction

public SimpleTypeInformation<? super Clustering<?>> getInputTypeRestriction()

Description copied from interface: Similarity

Get the input data type of the function.

Specified by:

getInputTypeRestriction in interface Distance<Clustering<?>>

Specified by:

getInputTypeRestriction in interface PrimitiveDistance<Clustering<?>>

Specified by:

getInputTypeRestriction in interface Similarity<Clustering<?>>

Returns:

Type restriction