Uses of Class
gov.sandia.cognition.learning.algorithm.clustering.KMeansClusterer

Packages that use KMeansClusterer
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. 
 

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

Subclasses of KMeansClusterer in gov.sandia.cognition.learning.algorithm.clustering
 class KMeansClustererWithRemoval<DataType,ClusterType extends Cluster<DataType>>
          Creates a k-means clustering algorithm that removes clusters that do not have sufficient membership to pass a simple statistical significance test.
 class OptimizedKMeansClusterer<DataType>
          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.
 class ParallelizedKMeansClusterer<DataType,ClusterType extends Cluster<DataType>>
          This is a parallel implementation of the k-means clustering algorithm.
 

Methods in gov.sandia.cognition.learning.algorithm.clustering that return KMeansClusterer
 KMeansClusterer<DataType,ClusterType> KMeansClusterer.clone()
           
 

Uses of KMeansClusterer in gov.sandia.cognition.learning.function.vector
 

Constructors in gov.sandia.cognition.learning.function.vector with parameters of type KMeansClusterer
GaussianContextRecognizer.Learner(KMeansClusterer<Vector,GaussianCluster> algorithm)
          Creates a new instance of Learner
 

Uses of KMeansClusterer in gov.sandia.cognition.statistics.distribution
 

Constructors in gov.sandia.cognition.statistics.distribution with parameters of type KMeansClusterer
MixtureOfGaussians.Learner(KMeansClusterer<Vector,GaussianCluster> algorithm)
          Creates a new Learner