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

Class EvaluateDaviesBouldin

java.lang.Object

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

All Implemented Interfaces:

Evaluator, ResultProcessor

@Reference(authors="D. L. Davies and D. W. Bouldin",
           title="A Cluster Separation Measure",
           booktitle="IEEE Transactions Pattern Analysis and Machine Intelligence PAMI-1(2)",
           url="http://dx.doi.org/10.1109/TPAMI.1979.4766909")
public class EvaluateDaviesBouldin
extends Object
implements Evaluator

Compute the Davies-Bouldin index of a data set. Reference:

D. L. Davies and D. W. Bouldin
A Cluster Separation Measure
In: IEEE Transactions Pattern Analysis and Machine Intelligence PAMI-1(2)

Author:

Stephan Baier

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	EvaluateDaviesBouldin.Parameterizer Parameterization class.

Field Summary

Fields

Modifier and Type	Field and Description
private NumberVectorDistanceFunction<?>	distanceFunction 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
EvaluateDaviesBouldin(NumberVectorDistanceFunction<?> distance, NoiseHandling noiseOpt) Constructor.

Method Summary

Methods

Modifier and Type	Method and Description
double	evaluateClustering(Database db, Relation<? extends NumberVector> rel, Clustering<?> c) Evaluate a single clustering.
void	processNewResult(ResultHierarchy hier, Result result) Process a result.
double[]	withinGroupDistances(Relation<? extends NumberVector> rel, List<? extends Cluster<?>> clusters, NumberVector[] centroids)

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.

distanceFunction

private NumberVectorDistanceFunction<?> distanceFunction

Distance function to use.

key

private String key

Key for logging statistics.

Constructor Detail

EvaluateDaviesBouldin

public EvaluateDaviesBouldin(NumberVectorDistanceFunction<?> distance,
                     NoiseHandling noiseOpt)

Constructor.

Parameters:

distance - Distance function

noiseOpt - Flag to control noise handling

Method Detail

evaluateClustering

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

Evaluate a single clustering.

Parameters:

db - Database

rel - Data relation

c - Clustering

Returns:

DB-index

withinGroupDistances

public double[] withinGroupDistances(Relation<? extends NumberVector> rel,
                            List<? extends Cluster<?>> clusters,
                            NumberVector[] centroids)

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.