Package com.aliasi.cluster

Classes for clustering data and evaluation.


Interface Summary
Clusterer<E> The Clusterer interface defines a means of clustering a set of input elements
HierarchicalClusterer<E> The HierarchicalClusterer interface defines a means of clustering a set of objects into a hierarchy of clusters.

Class Summary
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.