Package edu.stanford.nlp.cluster

Data Structures and Algorithms for Clustering Data.

See:
Description

Interface Summary

Cluster	Data Structure for Cluster.
ClusteringMethod	Interface for Clustering Methods.
Clusters	Interface for a collection of Clusters that span the entire data collection.
SimpleClusters	Simple Interface for a collection of Clusters.

Class Summary

AbstractClusteringMethod	Abstract implementation of ClusteringMethod.
AbstractSimpleClusters	Simple Interface for a collection of Clusters.
ClusterTransform	Transforms an XML Clusters file into an HTML Clusters file.
HACM	Hierarchical Agglomerative Clustering Method
HardCluster	Hard Cluster.
HHCluster	Hierarchical Hard Cluster.
HiddenState	Data Structure for clusters in LSSA.
Kmeans	K-means Clustering Algorithm.
LSSA	Latent State Sequence Analysis.
MatrixDecompositionClusters	SimpleClusters implementation that represents P(z), P(w|z), P(d|z) as matrices.
PDDP	Principal Direction Divisive Partitioning.
PLSI	Probabilistic Latent Semantic Indexing.
SimilarityMatrix	Variables and methods for constructing a matrix of similarities of a data collection.
SimpleCluster	A simple implementation of Cluster.
SoftCluster	Soft Cluster.
SVD	Takes the SVD of the feature matrix, and returns U=P(w|z), S=P(z), V=P(d|z).
VectorClusters	Simple implementation of Clusters.

Package edu.stanford.nlp.cluster Description

Data Structures and Algorithms for Clustering Data. This package needs an overhaul in terms of the basic data structures. Currently implements k-means, plsi, lssa, and the hierarchical agglomerative clustering methods.

Sepandar David Kamvar

Last modified: Thu Oct 31 10:35:28 PST 2002