de.lmu.ifi.dbs.elki.evaluation.clustering.internal

Class EvaluateCIndex<O>

java.lang.Object

de.lmu.ifi.dbs.elki.evaluation.clustering.internal.EvaluateCIndex<O>

All Implemented Interfaces:

Evaluator, ResultProcessor

@Reference(authors="L. J. Hubert and J. R. Levin",
           title="A general statistical framework for assessing categorical clustering in free recall.",
           booktitle="Psychological Bulletin, Vol. 83(6)",
           url="http://dx.doi.org/10.1037/0033-2909.83.6.1072")
public class EvaluateCIndex<O>
extends Object
implements Evaluator

Compute the C-index of a data set. Reference:

L. J. Hubert and J.R. Levin
A general statistical framework for assessing categorical clustering in free recall
Psychological Bulletin, Vol. 83(6)

Author:

Stephan Baier, Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	EvaluateCIndex.Parameterizer<O> Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private DistanceFunction<? super O>	distance Distance function to use.
private String	key Key for logging statistics.
private static Logging	LOG Logger for debug output.
private NoiseHandling	noiseOption Option for noise handling.

Constructor Summary

Constructors

Constructor and Description
EvaluateCIndex(DistanceFunction<? super O> distance, NoiseHandling noiseOpt) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
double	evaluateClustering(Database db, Relation<? extends O> rel, DistanceQuery<O> dq, Clustering<?> c) Evaluate a single clustering.
void	processNewResult(ResultHierarchy hier, Result result) Process a result.

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Logger for debug output.

noiseOption

private NoiseHandling noiseOption

Option for noise handling.

distance

private DistanceFunction<? super O> distance

Distance function to use.

key

private String key

Key for logging statistics.

Constructor Detail

EvaluateCIndex

public EvaluateCIndex(DistanceFunction<? super O> distance,
              NoiseHandling noiseOpt)

Constructor.

Parameters:

distance - Distance function

noiseOpt - Flag to control noise handling

Method Detail

evaluateClustering

public double evaluateClustering(Database db,
                        Relation<? extends O> rel,
                        DistanceQuery<O> dq,
                        Clustering<?> c)

Evaluate a single clustering.

Parameters:

db - Database

rel - Data relation

c - Clustering

Returns:

C-Index

processNewResult

public void processNewResult(ResultHierarchy hier,
                    Result result)

Description copied from interface: ResultProcessor

Process a result.

Specified by:

processNewResult in interface ResultProcessor

Parameters:

hier - The base of the result tree.

result - Newly added result subtree.