edu.ucla.sspace.clustering

Class Streemer

java.lang.Object

edu.ucla.sspace.clustering.Streemer

All Implemented Interfaces:

Clustering

public class Streemer
extends Object
implements Clustering

An implementation of the Streemer (Streaming EM) algorithm for foreground/background clustering. The full algorithm is described in

• V. Kandylas, S. P. Upham, and L. Ungar. Finding cohesive clusters for analyzing knowledge communities. In Proceedings of the Seventh IEEE Conference on Data Mining (ICDM). IEEE Computer Society. Omaha, NE. Available online here

Author:

David Jurgens

Constructor Summary

Constructors

Constructor and Description
Streemer()

Method Summary

Methods

Modifier and Type	Method and Description
Assignments	cluster(Matrix matrix, int numClusters, double backgroundClusterPerc, double similarityThreshold, int minClusterSize, SimilarityFunction simFunc)
Assignments	cluster(Matrix matrix, int numClusters, Properties props) Clusters the set of rows in the given Matrix into the specified number of clusters.
Assignments	cluster(Matrix matrix, Properties props) Clusters the set of rows in the given Matrix without a specified number of clusters

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

Streemer

public Streemer()

Method Detail

cluster

public Assignments cluster(Matrix matrix,
                  Properties props)

Clusters the set of rows in the given Matrix without a specified number of clusters

Specified by:

cluster in interface Clustering

Parameters:

matrix - the Matrix whose row data points are to be clustered

props - the properties to use for any parameters each clustering algorithm may need

Returns:

an array of Assignment instances that indicate zero or more clusters to which each row belongs.

cluster

public Assignments cluster(Matrix matrix,
                  int numClusters,
                  Properties props)

Clusters the set of rows in the given Matrix into the specified number of clusters. The set of cluster assignments are returned for each row in the matrix.

Specified by:

cluster in interface Clustering

Parameters:

matrix - the Matrix whose row data points are to be clustered

numClusters - the number of clusters to generate

props - the properties to use for any parameters each clustering algorithm may need

Returns:

an array of Assignment instances that indicate zero or more clusters to which each row belongs.

cluster

public Assignments cluster(Matrix matrix,
                  int numClusters,
                  double backgroundClusterPerc,
                  double similarityThreshold,
                  int minClusterSize,
                  SimilarityFunction simFunc)