jsat.clustering.evaluation.intra

Class MeanCentroidDistance

java.lang.Object

jsat.clustering.evaluation.intra.MeanCentroidDistance

All Implemented Interfaces:

IntraClusterEvaluation

public class MeanCentroidDistance
extends java.lang.Object
implements IntraClusterEvaluation

Evaluates a cluster's validity by computing the mean distance of each point in the cluster from the cluster's centroid.

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
MeanCentroidDistance	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

MeanCentroidDistance

public MeanCentroidDistance()

Creates a new MeanCentroidDistance using the EuclideanDistance

MeanCentroidDistance

public MeanCentroidDistance(DistanceMetric dm)

Creates a new MeanCentroidDistance.

Parameters:

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

MeanCentroidDistance

public MeanCentroidDistance(MeanCentroidDistance 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 MeanCentroidDistance clone()

Specified by:

clone in interface IntraClusterEvaluation

Overrides:

clone in class java.lang.Object