Package org.hipparchus.clustering.evaluation

Class ClusterEvaluator<T extends Clusterable>

java.lang.Object

org.hipparchus.clustering.evaluation.ClusterEvaluator<T>

Type Parameters:

T - type of the clustered points

Direct Known Subclasses:

SumOfClusterVariances

public abstract class ClusterEvaluator<T extends Clusterable>
extends Object

Base class for cluster evaluation methods.

Constructor Summary

Constructors

Constructor	Description
ClusterEvaluator()	Creates a new cluster evaluator with an EuclideanDistance as distance measure.
ClusterEvaluator(DistanceMeasure measure)	Creates a new cluster evaluator with the given distance measure.

Method Summary

Modifier and Type	Method	Description
protected Clusterable	centroidOf(Cluster<T> cluster)	Computes the centroid for a cluster.
protected double	distance(Clusterable p1, Clusterable p2)	Calculates the distance between two Clusterable instances with the configured DistanceMeasure.
boolean	isBetterScore(double score1, double score2)	Returns whether the first evaluation score is considered to be better than the second one by this evaluator.
abstract double	score(List<? extends Cluster<T>> clusters)	Computes the evaluation score for the given list of clusters.

Methods inherited from class java.lang.Object

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

Constructor Details

ClusterEvaluator

public ClusterEvaluator()

Creates a new cluster evaluator with an EuclideanDistance as distance measure.

ClusterEvaluator

public ClusterEvaluator(DistanceMeasure measure)

Creates a new cluster evaluator with the given distance measure.

Parameters:

measure - the distance measure to use

Method Details

score

public abstract double score(List<? extends Cluster<T>> clusters)

Computes the evaluation score for the given list of clusters.

Parameters:

clusters - the clusters to evaluate

Returns:

the computed score

isBetterScore

public boolean isBetterScore(double score1,
 double score2)

Returns whether the first evaluation score is considered to be better than the second one by this evaluator.

Specific implementations shall override this method if the returned scores do not follow the same ordering, i.e. smaller score is better.

Parameters:

score1 - the first score

score2 - the second score

Returns:

true if the first score is considered to be better, false otherwise

distance

protected double distance(Clusterable p1,
 Clusterable p2)

Calculates the distance between two Clusterable instances with the configured DistanceMeasure.

Parameters:

p1 - the first clusterable

p2 - the second clusterable

Returns:

the distance between the two clusterables

centroidOf

protected Clusterable centroidOf(Cluster<T> cluster)

Computes the centroid for a cluster.

Parameters:

cluster - the cluster

Returns:

the computed centroid for the cluster, or null if the cluster does not contain any points