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:
Cloneable, CloneableSerializable, DivergenceFunction<ClusterType,ClusterType>, Serializable
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
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone