Uses of Interface
gov.sandia.cognition.learning.algorithm.clustering.cluster.ClusterCreator

Packages that use ClusterCreator

Package	Description
gov.sandia.cognition.learning.algorithm.clustering	Provides clustering algorithms.
gov.sandia.cognition.learning.algorithm.clustering.cluster	Provides implementations of different types of clusters.
gov.sandia.cognition.learning.algorithm.clustering.initializer	Provides implementations of methods for selecting initial clusters.

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

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

Modifier and Type	Field and Description
protected ClusterCreator<ClusterType,DataType>	AgglomerativeClusterer.creator The merger used to merge two clusters into one element.

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

Modifier and Type	Method and Description
ClusterCreator<ClusterType,DataType>	AgglomerativeClusterer.getCreator() Gets the cluster creator.
ClusterCreator<ClusterType,DataType>	DBSCANClusterer.getCreator() Gets the cluster creator.
ClusterCreator<ClusterType,DataType>	KMeansClusterer.getCreator() Gets the cluster creator.

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

Modifier and Type	Method and Description
void	AgglomerativeClusterer.setCreator(ClusterCreator<ClusterType,DataType> creator) Sets the cluster creator.
void	DBSCANClusterer.setCreator(ClusterCreator<ClusterType,DataType> creator) Sets the cluster creator.
void	KMeansClusterer.setCreator(ClusterCreator<ClusterType,DataType> creator) Sets the cluster creator.
MiniBatchKMeansClusterer.Builder<DataType>	MiniBatchKMeansClusterer.Builder.withCreator(ClusterCreator<MiniBatchCentroidCluster,Vector> creator)

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

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.
DBSCANClusterer(double eps, int minSamples, Semimetric<? super DataType> metric, ClusterCreator<ClusterType,DataType> creator) Creates a new instance of AffinityPropagation.
DBSCANClusterer(Semimetric<? super DataType> metric, ClusterCreator<ClusterType,DataType> creator) Creates a new instance of DBSCANClusterer.
KMeansClusterer(int numRequestedClusters, int maxIterations, FixedClusterInitializer<ClusterType,DataType> initializer, ClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator) Creates a new instance of KMeansClusterer using the given parameters.
KMeansClustererWithRemoval(int numRequestedClusters, int maxIterations, FixedClusterInitializer<ClusterType,DataType> initializer, ClusterDivergenceFunction<ClusterType,DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, double removalThreshold) Creates a new instance of KMeansClusterer using the given parameters.
MiniBatchKMeansClusterer(int numClusters, int maxIterations, FixedClusterInitializer<MiniBatchCentroidCluster,Vector> initializer, Semimetric<? super Vector> metric, ClusterCreator<MiniBatchCentroidCluster,Vector> creator, java.util.Random random) Creates a new MiniBatchKMeansClusterer.
OptimizedKMeansClusterer(int numClusters, int maxIterations, FixedClusterInitializer<CentroidCluster<DataType>,DataType> initializer, Metric<? super DataType> metric, ClusterCreator<CentroidCluster<DataType>,DataType> creator) Creates a new instance of OptimizedKMeansClusterer.
ParallelizedKMeansClusterer(int numRequestedClusters, int maxIterations, java.util.concurrent.ThreadPoolExecutor threadPool, FixedClusterInitializer<ClusterType,DataType> initializer, ClusterDivergenceFunction<? super ClusterType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator) Creates a new instance of ParallelizedKMeansClusterer2

Uses of ClusterCreator in gov.sandia.cognition.learning.algorithm.clustering.cluster

Subinterfaces of ClusterCreator in gov.sandia.cognition.learning.algorithm.clustering.cluster

Modifier and Type	Interface and Description
interface	IncrementalClusterCreator<ClusterType extends Cluster<DataType>,DataType> An interface for a ClusterCreator that can incrementally add and remove members from a cluster.

Classes in gov.sandia.cognition.learning.algorithm.clustering.cluster that implement ClusterCreator

Modifier and Type	Class and Description
class	DefaultClusterCreator<DataType> The DefaultClusterCreator class implements a default ClusterCreator that just creates a DefaultCluster from the given list of members.
class	DefaultIncrementalClusterCreator<DataType> A default implementation of the IncrementalClusterCreator interface that just creates a cluster as having a collection of members.
class	GaussianClusterCreator The GaussianClusterCreator class implements a ClusterCreator for creating GaussianClusters by fitting a MultivariateGaussian to the given set of example vectors.
class	MedoidClusterCreator<DataType> The MedoidClusterCreator class creates a CentroidCluster at the sample that minimizes the sum of the divergence to the objects assigned to the cluster.
class	NormalizedCentroidClusterCreator A cluster creator for NormalizedCentroidClusters which are clusters that have a normalized centroid in addition to the usual centroid.
class	VectorMeanCentroidClusterCreator The VectorMeanCentroidClusterCreator class implements a cluster creator for centroid clusters where the centroid is the mean of the vectors that are members of the cluster.
class	VectorMeanMiniBatchCentroidClusterCreator Implementation of VectorMeanCentroidClusterCreator for mini-batch clustering.

Uses of ClusterCreator in gov.sandia.cognition.learning.algorithm.clustering.initializer

Fields in gov.sandia.cognition.learning.algorithm.clustering.initializer declared as ClusterCreator

Modifier and Type	Field and Description
protected ClusterCreator<ClusterType,DataType>	AbstractMinDistanceFixedClusterInitializer.creator The ClusterCreator to create the initial clusters from.
protected ClusterCreator<ClusterType,DataType>	RandomClusterInitializer.creator The creator for new clusters.

Methods in gov.sandia.cognition.learning.algorithm.clustering.initializer that return ClusterCreator

Modifier and Type	Method and Description
ClusterCreator<ClusterType,DataType>	AbstractMinDistanceFixedClusterInitializer.getCreator() Gets the cluster creator used to create the initial clusters.

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

Modifier and Type	Method and Description
void	AbstractMinDistanceFixedClusterInitializer.setCreator(ClusterCreator<ClusterType,DataType> creator) Sets the cluster creator used to create the initial clusters.

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

Constructor and Description
AbstractMinDistanceFixedClusterInitializer(DivergenceFunction<? super DataType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, java.util.Random random) Creates a new instance of AbstractMinDistanceFixedClusterInitializer.
DistanceSamplingClusterInitializer(DivergenceFunction<? super DataType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, java.util.Random random) Creates a new instance of MinDistanceSamplingClusterInitializer.
GreedyClusterInitializer(DivergenceFunction<? super DataType,? super DataType> divergenceFunction, ClusterCreator<ClusterType,DataType> creator, java.util.Random random) Creates a new instance of GreedyClusterInitializer.
RandomClusterInitializer(ClusterCreator<ClusterType,DataType> creator, java.util.Random random) Creates a new random cluster creator.