gov.sandia.cognition.learning.algorithm.clustering.divergence

Interface WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType>

Type Parameters:

ClusterType - type of Cluster<DataType> used in the evalute() method.

DataType - type of data in the cluster.

All Superinterfaces:

java.lang.Cloneable, CloneableSerializable, java.io.Serializable

All Known Implementing Classes:

WithinClusterDivergenceWrapper, WithinNormalizedCentroidClusterCosineDivergence

public interface WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType>
extends java.lang.Cloneable, CloneableSerializable, java.io.Serializable

Defines a function that computes the divergence of the elements in a cluster.

Author:

Andrew N. Fisher <anfishe@sandia.gov>

Method Summary

Modifier and Type	Method and Description
double	evaluate(ClusterType cluster) Evaluates the divergence within a cluster.

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Method Detail

evaluate

double evaluate(ClusterType cluster)

Evaluates the divergence within a cluster.

Parameters:

cluster - Cluster to evaluate the divergence for.

Returns:

The divergence for the cluster.