jMEF.BregmanSoftClustering Class Reference

List of all members.

Static Public Member Functions

static MixtureModel initialize (Vector< PVector >[] clusters, ExponentialFamily EF)
 Initializes a mixture model from clusters of points, each cluster containing a set of points.
static MixtureModel run (PVector[] pointSet, MixtureModel fL, int iterations)
 Processes the Bregman soft clustering (EM) algorithm.
static MixtureModel run (PVector[] pointSet, MixtureModel fL)
 Processes the Bregman soft clustering (EM) algorithm.


Detailed Description

Author:
Vincent Garcia

Frank Nielsen

Version:
1.0

License

See file LICENSE.txt

Description

The Bregman soft clustering is the generalization of the soft clustering (also know as expectation-maximization algorithm) towards the exponential family. Given a set of points, the Bregman soft clustering algorithm estimates the parameters of the mixture model for a chosen exponential family.

Member Function Documentation

static MixtureModel jMEF.BregmanSoftClustering.initialize ( Vector< PVector >[]  clusters,
ExponentialFamily  EF 
) [static]

Initializes a mixture model from clusters of points, each cluster containing a set of points.

Parameters:
clusters clusters of points
EF exponential family member
Returns:
initialized mixture model

static MixtureModel jMEF.BregmanSoftClustering.run ( PVector[]  pointSet,
MixtureModel  fL 
) [static]

Processes the Bregman soft clustering (EM) algorithm.

Parameters:
pointSet set of points
fL initial mixture model given in source parameters
Returns:
estimated mixture model

static MixtureModel jMEF.BregmanSoftClustering.run ( PVector[]  pointSet,
MixtureModel  fL,
int  iterations 
) [static]

Processes the Bregman soft clustering (EM) algorithm.

Parameters:
pointSet set of points
fL initial mixture model given in source parameters
iterations maximum number of iterations allowed
Returns:
estimated mixture model


The documentation for this class was generated from the following file:

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