net.sourceforge.cilib.clustering.kmeans
Class KMeans

java.lang.Object
  net.sourceforge.cilib.algorithm.Algorithm
      net.sourceforge.cilib.algorithm.SingularAlgorithm
          net.sourceforge.cilib.clustering.kmeans.KMeans

All Implemented Interfaces:

Serializable, Runnable, Cloneable

public class KMeans
extends SingularAlgorithm

This algorithm is an implementation of the KMeans Clustering algorithm.

This is the implementation as described in Section 2 of:

Author:

Theuns Cloete

See Also:

Serialized Form

Field Summary

Fields inherited from class net.sourceforge.cilib.algorithm.Algorithm

optimisationProblem

Constructor Summary

KMeans()
Create an instance of KMeans.

KMeans(KMeans copy)
Create a copy of the provided instance.

Method Summary

void	algorithmIteration() Performs a single iteration of the KMeans algorithm.
OptimisationSolution	getBestSolution() Get the best current solution.
CentroidsInitialisationStrategy	getCentroidsInitialisationStrategy() Get the centroid initialisation strategy.
Algorithm	getClone() Create a cloned copy of the current object and return it.
List<OptimisationSolution>	getSolutions() Get the collection of best solutions.
void	performInitialisation() This initialisation of the centroids is handled by the chosen CentroidsInitialisationStrategy.
void	setCentroidsInitialisationStrategy(CentroidsInitialisationStrategy centroidsInitialisationStrategy) Set the current CentroidsInitialisationStrategy.

Methods inherited from class net.sourceforge.cilib.algorithm.Algorithm

addAlgorithmListener, addStoppingCondition, get, getAlgorithmList, getIterations, getOptimisationProblem, getPercentageComplete, getStoppingConditions, initialise, isFinished, performIteration, performUninitialisation, removeAlgorithmListener, removeStoppingCondition, reset, run, setOptimisationProblem, terminate

Methods inherited from class java.lang.Object

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

Constructor Detail

KMeans

public KMeans()

Create an instance of KMeans.

KMeans

public KMeans(KMeans copy)

Create a copy of the provided instance.

Parameters:

rhs - The instance to copy.

Method Detail

getClone

public Algorithm getClone()

Create a cloned copy of the current object and return it. In general the created copy will be a deep copy of the provided instance. As a result this operation an be quite expensive if used incorrectly.

Specified by:

getClone in interface Cloneable

Specified by:

getClone in class Algorithm

Returns:

An exact clone of the current object instance.

See Also:

Object.clone()

performInitialisation

public void performInitialisation()

This initialisation of the centroids is handled by the chosen CentroidsInitialisationStrategy.

Overrides:

performInitialisation in class Algorithm

algorithmIteration

public void algorithmIteration()

Performs a single iteration of the KMeans algorithm.

Specified by:

algorithmIteration in class SingularAlgorithm

getBestSolution

public OptimisationSolution getBestSolution()

Get the best current solution. This best solution is determined from the personal bests of the particles.

Specified by:

getBestSolution in class Algorithm

Returns:

The OptimisationSolution representing the best solution.

getSolutions

public List<OptimisationSolution> getSolutions()

Get the collection of best solutions. This result does not actually make sense in the normal PSO algorithm, but rather in a MultiObjective optimization.

Specified by:

getSolutions in class Algorithm

Returns:

The Collection<OptimisationSolution> containing the solutions.

getCentroidsInitialisationStrategy

public CentroidsInitialisationStrategy getCentroidsInitialisationStrategy()

Get the centroid initialisation strategy.

Returns:

The current CentroidsInitialisationStrategy.

setCentroidsInitialisationStrategy

public void setCentroidsInitialisationStrategy(CentroidsInitialisationStrategy centroidsInitialisationStrategy)

Set the current CentroidsInitialisationStrategy.

Parameters:

centroidsInitialisationStrategy - The value to set.