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

Packages that use Cluster

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.divergence	Provides divergence functions for use in clustering.
gov.sandia.cognition.learning.algorithm.clustering.hierarchy	Provides a hierarchy for clusters.
gov.sandia.cognition.learning.algorithm.clustering.initializer	Provides implementations of methods for selecting initial clusters.
gov.sandia.cognition.learning.function.cost	Provides cost functions.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.

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

Classes in gov.sandia.cognition.learning.algorithm.clustering with type parameters of type Cluster

Modifier and Type	Class and Description
class	AgglomerativeClusterer<DataType,ClusterType extends Cluster<DataType>> The AgglomerativeClusterer implements an agglomerative clustering algorithm, which is a type of hierarchical clustering algorithm.
static class	AgglomerativeClusterer.HierarchyNode<DataType,ClusterType extends Cluster<DataType>> Holds the hierarchy information for the agglomerative clusterer.
interface	BatchClusterer<DataType,ClusterType extends Cluster<DataType>> The BatchClusterer interface defines the functionality of a batch clustering algorithm.
class	DBSCANClusterer<DataType extends Vectorizable,ClusterType extends Cluster<DataType>> The DBSCAN algorithm requires three parameters: a distance metric, a value for neighborhood radius, and a value for the minimum number of surrounding neighbors for a point to be considered non-noise.
class	KMeansClusterer<DataType,ClusterType extends Cluster<DataType>> The KMeansClusterer class implements the standard k-means (k-centroids) clustering algorithm.
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	ParallelizedKMeansClusterer<DataType,ClusterType extends Cluster<DataType>> This is a parallel implementation of the k-means clustering algorithm.
class	PartitionalClusterer<DataType,ClusterType extends Cluster<DataType>> The PartitionalClusterer implements a partitional clustering algorithm, which is a type of hierarchical clustering algorithm.

Classes in gov.sandia.cognition.learning.algorithm.clustering that implement Cluster

Modifier and Type	Class and Description
static class	AgglomerativeClusterer.HierarchyNode<DataType,ClusterType extends Cluster<DataType>> Holds the hierarchy information for the agglomerative clusterer.

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

Classes in gov.sandia.cognition.learning.algorithm.clustering.cluster with type parameters of type Cluster

Modifier and Type	Interface and Description
interface	ClusterCreator<ClusterType extends Cluster<DataType>,DataType> The ClusterCreator defines the functionality of a class that can create a new cluster from a given collection of members of that cluster.
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 Cluster

Modifier and Type	Class and Description
class	CentroidCluster<ClusterType> The CentroidCluster class extends the default cluster to contain a central element.
class	DefaultCluster<ClusterType> The DefaultCluster class implements a default cluster which contains a list of members in an ArrayList along with an index that identifies the cluster.
class	GaussianCluster The GaussianCluster class implements a cluster of Vector objects that has a MultivariateGaussian object representing the cluster.
class	MiniBatchCentroidCluster
class	NormalizedCentroidCluster<ClusterType> Add the ability to store the centroid of the normalized vectors belonging to a centroid cluster.

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

Classes in gov.sandia.cognition.learning.algorithm.clustering.divergence with type parameters of type Cluster

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	ClusterCompleteLinkDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterCompleteLinkDivergenceFunction class implements the complete linkage distance metric between two clusters.
interface	ClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterDivergenceFunction interface defines a function that computes the divergence between a cluster and some other object.
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.
interface	ClusterToClusterDivergenceFunction<ClusterType extends Cluster<DataType>,DataType> The ClusterToClusterDivergenceFunction defines a DivergenceFunction between two clusters of the same data type.
interface	WithinClusterDivergence<ClusterType extends Cluster<DataType>,DataType> Defines a function that computes the divergence of the elements in a cluster.
class	WithinClusterDivergenceWrapper<ClusterType extends Cluster<DataType>,DataType> Accumulates the results of a ClusterDivergenceFunction by summing the divergence of each point to its cluster.

Uses of Cluster in gov.sandia.cognition.learning.algorithm.clustering.hierarchy

Classes in gov.sandia.cognition.learning.algorithm.clustering.hierarchy with type parameters of type Cluster

Modifier and Type	Class and Description
class	AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> An abstract implementation of the ClusterHierarchyNode class.
interface	BatchHierarchicalClusterer<DataType,ClusterType extends Cluster<DataType>> The BatchHierarchicalClusterer interface defines the functionality of a batch hierarchical clustering algorithm.
class	BinaryClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> Implements a binary cluster hierarchy node.
interface	ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> Defines a node in a hierarchy of clusters.
class	DefaultClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> A default implementation of the cluster hierarchy node.

Subinterfaces of Cluster in gov.sandia.cognition.learning.algorithm.clustering.hierarchy

Modifier and Type	Interface and Description
interface	ClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> Defines a node in a hierarchy of clusters.

Classes in gov.sandia.cognition.learning.algorithm.clustering.hierarchy that implement Cluster

Modifier and Type	Class and Description
class	AbstractClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> An abstract implementation of the ClusterHierarchyNode class.
class	BinaryClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> Implements a binary cluster hierarchy node.
class	DefaultClusterHierarchyNode<DataType,ClusterType extends Cluster<DataType>> A default implementation of the cluster hierarchy node.

Fields in gov.sandia.cognition.learning.algorithm.clustering.hierarchy declared as Cluster

Modifier and Type	Field and Description
protected ClusterType	AbstractClusterHierarchyNode.cluster The cluster associated with the node.

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

Classes in gov.sandia.cognition.learning.algorithm.clustering.initializer with type parameters of type Cluster

Modifier and Type	Class and Description
class	AbstractMinDistanceFixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> Implements an abstract FixedClusterInitializer that works by using the minimum distance from a point to the cluster.
class	DistanceSamplingClusterInitializer<ClusterType extends Cluster<DataType>,DataType> Implements FixedClusterInitializer that initializes clusters by first selecting a random point for the first cluster and then randomly sampling each successive cluster based on the squared minimum distance from the point to the existing selected clusters.
interface	FixedClusterInitializer<ClusterType extends Cluster<DataType>,DataType> The FixedClusterInitializer interface defines the functionality of a class that can initialize a given number of clusters from a set of elements.
class	GreedyClusterInitializer<ClusterType extends Cluster<DataType>,DataType> Implements a FixedClusterInitializer that greedily attempts to create the initial clusters.
class	RandomClusterInitializer<ClusterType extends Cluster<DataType>,DataType> Creates initial clusters by selecting random data points as singleton clusters.

Uses of Cluster in gov.sandia.cognition.learning.function.cost

Classes in gov.sandia.cognition.learning.function.cost with type parameters of type Cluster

Modifier and Type	Class and Description
class	ClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> Computes the objective measure for a clustering algorithm, based on the internal "distortion" of each cluster.
class	ParallelClusterDistortionMeasure<DataType,ClusterType extends Cluster<DataType>> A parallel implementation of ClusterDistortionMeasure.

Uses of Cluster in gov.sandia.cognition.statistics.bayesian

Classes in gov.sandia.cognition.statistics.bayesian that implement Cluster

Modifier and Type	Class and Description
static class	DirichletProcessMixtureModel.DPMMCluster<ObservationType> Cluster for a step in the DPMM