Package com.aliasi.cluster

Classes for clustering data and evaluation.

See: Description

Interface Summary

Interface	Description
Clusterer<E>	The Clusterer interface defines a means of clustering a set of input elements Typically, the clusters returned by a clusterer will form a partition of the input elements.
HierarchicalClusterer<E>	The HierarchicalClusterer interface defines a means of clustering a set of objects into a hierarchy of clusters.

Class Summary

Class	Description
AbstractHierarchicalClusterer<E>	An AbstractHierachicalClusterer provides an adapter for clustering for hierarchical clusterers.
ClusterScore<E>	A ClusterScore provides a range of cluster scoring metrics for reference partitions versus response partitions.
CompleteLinkClusterer<E>	A CompleteLinkClusterer implements complete link agglomerative clustering.
Dendrogram<E>	A Dendrogram represents the result of a weighted hierarchical clustering of a set of objects.
KMeansClusterer<E>	A KMeansClusterer provides an implementation of k-means(++) clustering based on vectors constructed by feature extractors.
LatentDirichletAllocation	A LatentDirichletAllocation object represents a latent Dirichlet allocation (LDA) model.
LatentDirichletAllocation.GibbsSample	The LatentDirichletAllocation.GibbsSample class encapsulates all of the information related to a single Gibbs sample for latent Dirichlet allocation (LDA).
LeafDendrogram<E>	A LeafDendrogram represents a dendrogram consisting of a single object with link cost of 0.0.
LinkDendrogram<E>	A LinkDendrogram consists of a pair of sub-dendrograms which are joined at a specified cost.
SingleLinkClusterer<E>	A SingleLinkClusterer implements standard single-link agglomerative clustering.

Package com.aliasi.cluster Description

Classes for clustering data and evaluation.