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

Packages that use ClusterToClusterDivergenceFunction
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
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
 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
 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
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 maxMinDistance)
          Initializes the clustering to use the given metric between clusters, the given cluster merger, and the maximum minimum distance between clusters to allow.
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 maxMinDistance)
          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
 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.