jsat.clustering.evaluation

Class DunnIndex

java.lang.Object

jsat.clustering.evaluation.DunnIndex

All Implemented Interfaces:

ClusterEvaluation

public class DunnIndex
extends Object
implements ClusterEvaluation

Computes the Dunn Index (DI) using a customizable manner. Normally, a higher DI value indicates a better value. In order to conform to the interface contract of a lower value indicating a better result, the value of 1/(1+DI) is returned.

Author:

Edward Raff

Constructor Summary

Constructors

Constructor and Description
DunnIndex(DunnIndex toCopy) Copy constructor
DunnIndex(IntraClusterEvaluation ice, ClusterDissimilarity cd) Creates a new DunnIndex

Method Summary

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

Methods inherited from class java.lang.Object

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

Constructor Detail

DunnIndex

public DunnIndex(IntraClusterEvaluation ice,
                 ClusterDissimilarity cd)

Creates a new DunnIndex

Parameters:

ice - the metric to measure the quality of a single cluster

cd - the metric to measure the distance between two clusters

DunnIndex

public DunnIndex(DunnIndex toCopy)

Copy constructor

Parameters:

toCopy - the object to copy

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(List<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 DunnIndex clone()

Specified by:

clone in interface ClusterEvaluation

Overrides:

clone in class Object