jsat.clustering.evaluation

Class DaviesBouldinIndex

java.lang.Object

jsat.clustering.evaluation.DaviesBouldinIndex

All Implemented Interfaces:

ClusterEvaluation

public class DaviesBouldinIndex
extends java.lang.Object
implements ClusterEvaluation

A measure for evaluating the quality of a clustering by measuring the distances of points to their centroids.

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
DaviesBouldinIndex	clone()
double	evaluate(int[] designations, DataSet dataSet) Evaluates the clustering of the given clustering.
double	evaluate(java.util.List<java.util.List<DataPoint>> dataSets) Evaluates the clustering of the given set of clusters.

Methods inherited from class java.lang.Object

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

Constructor Detail

DaviesBouldinIndex

public DaviesBouldinIndex()

Creates a new DaviesBouldinIndex using the EuclideanDistance.

DaviesBouldinIndex

public DaviesBouldinIndex(DaviesBouldinIndex toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

DaviesBouldinIndex

public DaviesBouldinIndex(DistanceMetric dm)

Creates a new DaviesBouldinIndex

Parameters:

dm - the distance measure to use when computing

Method Detail

evaluate

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

Description copied from interface: ClusterEvaluation

Evaluates the clustering of the given clustering.

Specified by:

evaluate in interface ClusterEvaluation

Parameters:

designations - the array that stores the cluster assignments for each data point in the data set

dataSet - the data set that contains all data points

Returns:

a value in [0, Inf) that indicates the quality of the clustering.

evaluate

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

Description copied from interface: ClusterEvaluation

Evaluates the clustering of the given set of clusters.

Specified by:

evaluate in interface ClusterEvaluation

Parameters:

dataSets - a list of lists, where the size of the first index indicates the the number of clusters, and the list at each index is the data points that make up each cluster.

Returns:

a value in [0, Inf) that indicates the quality of the clustering.

clone

public DaviesBouldinIndex clone()

Specified by:

clone in interface ClusterEvaluation

Overrides:

clone in class java.lang.Object