jsat.clustering.evaluation.intra

Class MeanDistance

java.lang.Object

jsat.clustering.evaluation.intra.MeanDistance

All Implemented Interfaces:

IntraClusterEvaluation

public class MeanDistance
extends java.lang.Object
implements IntraClusterEvaluation

Evaluates a cluster's validity by computing the mean distance between all combinations of points.

Constructor Summary

Constructors

Constructor and Description
MeanDistance() Creates a new MeanDistance using the EuclideanDistance
MeanDistance(DistanceMetric dm) Creates a new MeanDistance
MeanDistance(MeanDistance toCopy) Copy constructor

Method Summary

Modifier and Type	Method and Description
MeanDistance	clone()
double	evaluate(int[] designations, DataSet dataSet, int clusterID) Evaluates the cluster represented by the given list of data points.
double	evaluate(java.util.List<DataPoint> dataPoints) Evaluates the cluster represented by the given list of data points.

Methods inherited from class java.lang.Object

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

Constructor Detail

MeanDistance

public MeanDistance()

Creates a new MeanDistance using the EuclideanDistance

MeanDistance

public MeanDistance(DistanceMetric dm)

Creates a new MeanDistance

Parameters:

dm - the metric to measure the distance between two points by

MeanDistance

public MeanDistance(MeanDistance toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

Method Detail

evaluate

public double evaluate(int[] designations,
                       DataSet dataSet,
                       int clusterID)

Description copied from interface: IntraClusterEvaluation

Evaluates the cluster represented by the given list of data points.

Specified by:

evaluate in interface IntraClusterEvaluation

Parameters:

designations - the array of cluster designations for the data set

dataSet - the full data set of all clusters

clusterID - the cluster id in the designations array to return the evaluation of

Returns:

the value in the range [0, Inf) that indicates how well formed the cluster is.

evaluate

public double evaluate(java.util.List<DataPoint> dataPoints)

Description copied from interface: IntraClusterEvaluation

Evaluates the cluster represented by the given list of data points.

Specified by:

evaluate in interface IntraClusterEvaluation

Parameters:

dataPoints - the data points that make up this cluster

Returns:

the value in the range [0, Inf) that indicates how well formed the cluster is.

clone

public MeanDistance clone()

Specified by:

clone in interface IntraClusterEvaluation

Overrides:

clone in class java.lang.Object