Package cc.mallet.cluster

Class HillClimbingClusterer

java.lang.Object

cc.mallet.cluster.Clusterer

cc.mallet.cluster.KBestClusterer

cc.mallet.cluster.HillClimbingClusterer

All Implemented Interfaces:

java.io.Serializable

Direct Known Subclasses:

GreedyAgglomerative

public abstract class HillClimbingClusterer
extends KBestClusterer

A Clusterer that iteratively improves a predicted Clustering using a NeighborEvaluator.

Since:

1.0

Version:

1.0

Author:

"Aron Culotta"

See Also:

Clusterer, Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
protected NeighborEvaluator	evaluator

Constructor Summary

Constructors

Constructor	Description
HillClimbingClusterer(Pipe instancePipe, NeighborEvaluator evaluator)

Method Summary

Modifier and Type	Method	Description
Clustering	cluster(InstanceList instances)	While not converged, calls improveClustering to modify the current predicted Clustering.
Clustering	cluster(InstanceList instances, int iterations, Clustering initialClustering)	While not converged, call improveClustering to modify the current predicted Clustering.
Clustering[]	clusterKBest(InstanceList instances, int k)
Clustering[]	clusterKBest(InstanceList instances, int iterations, Clustering initialClustering, int k)	Return the K most recent solutions.
abstract boolean	converged(Clustering clustering)
NeighborEvaluator	getEvaluator()
abstract Clustering	improveClustering(Clustering clustering)
abstract Clustering	initializeClustering(InstanceList instances)
abstract void	reset()	Perform any cleanup of the clustering algorithm prior to clustering.

Methods inherited from class cc.mallet.cluster.Clusterer

getPipe

Methods inherited from class java.lang.Object

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

Field Detail

evaluator

protected NeighborEvaluator evaluator

Constructor Detail

HillClimbingClusterer

public HillClimbingClusterer(Pipe instancePipe,
                             NeighborEvaluator evaluator)

Method Detail

getEvaluator

public NeighborEvaluator getEvaluator()

cluster

public Clustering cluster(InstanceList instances)

While not converged, calls improveClustering to modify the current predicted Clustering.

Specified by:

cluster in class Clusterer

Parameters:

instances -

Returns:

The predicted Clustering.

clusterKBest

public Clustering[] clusterKBest(InstanceList instances,
                                 int k)

Specified by:

clusterKBest in class KBestClusterer

cluster

public Clustering cluster(InstanceList instances,
                          int iterations,
                          Clustering initialClustering)

While not converged, call improveClustering to modify the current predicted Clustering.

Parameters:

instances - Instances to cluster.

iterations - Maximum number of iterations.

initialClustering - Initial clustering of the Instances.

Returns:

The predicted Clustering

clusterKBest

public Clustering[] clusterKBest(InstanceList instances,
                                 int iterations,
                                 Clustering initialClustering,
                                 int k)

Return the K most recent solutions.

Parameters:

instances -

iterations -

initialClustering -

Returns:

converged

public abstract boolean converged(Clustering clustering)

Parameters:

clustering -

Returns:

True if clustering is complete.

improveClustering

public abstract Clustering improveClustering(Clustering clustering)

Parameters:

clustering -

Returns:

A modified Clustering.

initializeClustering

public abstract Clustering initializeClustering(InstanceList instances)

Parameters:

instances -

Returns:

An initialized Clustering of these Instances.

reset

public abstract void reset()

Perform any cleanup of the clustering algorithm prior to clustering.