Uses of Interface
gov.sandia.cognition.learning.algorithm.clustering.divergence.ClusterToClusterDivergenceFunction

Packages that use ClusterToClusterDivergenceFunction

Package	Description
gov.sandia.cognition.learning.algorithm.clustering	Provides clustering algorithms.
gov.sandia.cognition.learning.algorithm.clustering.divergence	Provides divergence functions for use in clustering.

Uses of ClusterToClusterDivergenceFunction in gov.sandia.cognition.learning.algorithm.clustering

Fields in gov.sandia.cognition.learning.algorithm.clustering declared as ClusterToClusterDivergenceFunction

Modifier and Type	Field and Description
protected ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType>	AgglomerativeClusterer.divergenceFunction The divergence function used to find the distance between two clusters.

Methods in gov.sandia.cognition.learning.algorithm.clustering that return ClusterToClusterDivergenceFunction

Modifier and Type	Method and Description
ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType>	AgglomerativeClusterer.getDivergenceFunction() Gets the divergence function used in clustering.

Methods in gov.sandia.cognition.learning.algorithm.clustering with parameters of type ClusterToClusterDivergenceFunction

Modifier and Type	Method and Description
void	AgglomerativeClusterer.setDivergenceFunction(ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction) Sets the divergence function.

Constructors in gov.sandia.cognition.learning.algorithm.clustering with parameters of type ClusterToClusterDivergenceFunction

Constructor and Description
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator) Initializes the clustering to use the given metric between clusters, and the given cluster creator.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, double maxDistance) Initializes the clustering to use the given metric between clusters, the given cluster merger, and the maximum distance between clusters to allow when merging.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, int minNumClusters) Initializes the clustering to use the given metric between clusters, the given cluster creator, and the minimum number of clusters to allow.
AgglomerativeClusterer(ClusterToClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, int minNumClusters, double maxDistance) Initializes the clustering to use the given metric between clusters, the given cluster merger, the minimum number of clusters to allow, and the maximum minimum distance between clusters to allow.

Uses of ClusterToClusterDivergenceFunction in gov.sandia.cognition.learning.algorithm.clustering.divergence

Classes in gov.sandia.cognition.learning.algorithm.clustering.divergence that implement ClusterToClusterDivergenceFunction

Modifier and Type	Class and Description
class	AbstractClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The AbstractClusterToClusterDivergenceFunction class is an abstract class that helps out implementations of ClusterToClusterDivergenceFunction implementations by holding a DivergenceFunction between elements of a cluster.
class	ClusterCentroidDivergenceFunction<DataType> The ClusterCentroidDivergenceFunction class implements the distance between two clusters by computing the distance between the cluster's centroid.
class	ClusterCompleteLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterCompleteLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
class	ClusterMeanLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterMeanLinkDivergenceFunction class implements the mean linkage distance metric between two clusters.
class	ClusterSingleLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterSingleLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.