Uses of Package
gov.sandia.cognition.learning.algorithm.clustering

Packages that use gov.sandia.cognition.learning.algorithm.clustering
gov.sandia.cognition.learning.algorithm.clustering Provides clustering algorithms. 
gov.sandia.cognition.learning.function.vector Provides functions that output vectors. 
gov.sandia.cognition.statistics.distribution Provides statistical distributions. 
 

Classes in gov.sandia.cognition.learning.algorithm.clustering used by gov.sandia.cognition.learning.algorithm.clustering
AffinityPropagation
          The AffinityPropagation algorithm requires three parameters: a divergence function, a value to use for self-divergence, and a damping factor (called lambda in the paper; 0.5 is the default).
AgglomerativeClusterer
          The AgglomerativeClusterer implements an agglomerative clustering algorithm, which is a type of hierarchical clustering algorithm.
AgglomerativeClusterer.HierarchyNode
          Holds the hierarchy information for the agglomerative clusterer.
BatchClusterer
          The BatchClusterer interface defines the functionality of a batch clustering algorithm.
DirichletProcessClustering
          Clustering algorithm that wraps Dirichlet Process Mixture Model.
KMeansClusterer
          The KMeansClusterer class implements the standard k-means (k-centroids) clustering algorithm.
OptimizedKMeansClusterer
          This class implements an optimized version of the k-means algorithm that makes use of the triangle inequality to compute the same answer as k-means while using less distance calculations.
ParallelizedKMeansClusterer
          This is a parallel implementation of the k-means clustering algorithm.
PartitionalClusterer
          The PartitionClusterer implements a partitional clustering algorithm, which is a type of hierarchical clustering algorithm.
 

Classes in gov.sandia.cognition.learning.algorithm.clustering used by gov.sandia.cognition.learning.function.vector
KMeansClusterer
          The KMeansClusterer class implements the standard k-means (k-centroids) clustering algorithm.
 

Classes in gov.sandia.cognition.learning.algorithm.clustering used by gov.sandia.cognition.statistics.distribution
KMeansClusterer
          The KMeansClusterer class implements the standard k-means (k-centroids) clustering algorithm.