net.sourceforge.cilib.clustering.kmeans
Class DataSetBasedCentroidsInitialisationStrategy

java.lang.Object
  net.sourceforge.cilib.clustering.kmeans.DataSetBasedCentroidsInitialisationStrategy

All Implemented Interfaces:

Serializable, CentroidsInitialisationStrategy, Cloneable

public class DataSetBasedCentroidsInitialisationStrategy
extends Object
implements CentroidsInitialisationStrategy

This strategy initializes the parts of the returned centroids Vector from randomly chosen patterns in the dataset.

Author:

Theuns Cloete

See Also:

Serialized Form

Constructor Summary

DataSetBasedCentroidsInitialisationStrategy()
Create a new instance of DataSetBasedCentroidsInitialisationStrategy.

Method Summary

DataSetBasedCentroidsInitialisationStrategy	getClone() Create a cloned copy of the current object and return it.
Vector	initialise(ClusteringProblem problem, ClusterableDataSet dataset) Initialize the centroid vectors for a clustering from randomly chosen patterns in the given dataset.

Methods inherited from class java.lang.Object

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

Constructor Detail

DataSetBasedCentroidsInitialisationStrategy

public DataSetBasedCentroidsInitialisationStrategy()

Create a new instance of DataSetBasedCentroidsInitialisationStrategy.

Method Detail

getClone

public DataSetBasedCentroidsInitialisationStrategy 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

Returns:

An exact clone of the current object instance.

See Also:

Object.clone()

initialise

public Vector initialise(ClusteringProblem problem,
                         ClusterableDataSet dataset)

Initialize the centroid vectors for a clustering from randomly chosen patterns in the given dataset.

Specified by:

initialise in interface CentroidsInitialisationStrategy

Parameters:

problem - the ClusteringProblem currently being optimized

dataset - the ClusterableDataSet currently being clustered

Returns:

a Vector that represents all the centroids