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

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

Type Parameters:

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

DataType - The algorithm operates on a Collection<DataType>, so DataType will be something like Vector or String

All Superinterfaces:

DivergenceFunction<ClusterType,ClusterType>

All Known Implementing Classes:

AbstractClusterToClusterDivergenceFunction, ClusterCentroidDivergenceFunction, ClusterCompleteLinkDivergenceFunction, ClusterMeanLinkDivergenceFunction, ClusterSingleLinkDivergenceFunction

@CodeReview(reviewer="Kevin R. Dixon",
            date="2008-07-23",
            changesNeeded=false,
            comments={"Cleaned up javadoc a little bit with code annotations.","Otherwise, looks fine."})
public interface ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType>
extends DivergenceFunction<ClusterType,ClusterType>

The ClusterToClusterDivergenceFunction defines a DivergenceFunction between two clusters of the same data type. This represents the divergence between the two clusters. It is useful in conjunction with AgglomerativeClustering.

Since:

1.0

Author:

Justin Basilico

Method Summary

Methods inherited from interface gov.sandia.cognition.math.DivergenceFunction

evaluate