edu.ucla.sspace.clustering.seeding

Class RandomSeed

java.lang.Object

edu.ucla.sspace.clustering.seeding.RandomSeed

All Implemented Interfaces:

KMeansSeed

public class RandomSeed
extends Object
implements KMeansSeed

This KMeansSeed implementation selects data points at random from any given data set to serve as the initial centroid seeds.

Author:

Keith Stevens

Constructor Summary

Constructors

Constructor and Description
RandomSeed()

Method Summary

Methods

Modifier and Type	Method and Description
DoubleVector[]	chooseSeeds(int numCentroids, Matrix dataPoints) Returns an array of length numCentroids that contains centroids composed of either vectors from dataPoints or a linear combination of vectors from dataPoints.

Methods inherited from class java.lang.Object

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

Constructor Detail

RandomSeed

public RandomSeed()

Method Detail

chooseSeeds

public DoubleVector[] chooseSeeds(int numCentroids,
                         Matrix dataPoints)

Returns an array of length numCentroids that contains centroids composed of either vectors from dataPoints or a linear combination of vectors from dataPoints.

Specified by:

chooseSeeds in interface KMeansSeed