org.ddogleg.clustering.kmeans

Class InitializeStandard_F64

java.lang.Object

org.ddogleg.clustering.kmeans.InitializeStandard_F64

All Implemented Interfaces:

InitializeKMeans_F64

public class InitializeStandard_F64
extends java.lang.Object
implements InitializeKMeans_F64

Seeds are selects by randomly picking points. This is the standard way to initialize k-means

Constructor Summary

Constructors

Constructor and Description
InitializeStandard_F64()

Method Summary

Modifier and Type	Method and Description
void	init(int pointDimension, long randomSeed) Initializes internal data structures.
void	selectSeeds(java.util.List<double[]> points, java.util.List<double[]> seeds)

Methods inherited from class java.lang.Object

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

Constructor Detail

InitializeStandard_F64

public InitializeStandard_F64()

Method Detail

init

public void init(int pointDimension,
                 long randomSeed)

Description copied from interface: InitializeKMeans_F64

Initializes internal data structures. Must be called first.

Specified by:

init in interface InitializeKMeans_F64

Parameters:

pointDimension - NUmber of degrees of freedom in each point.

randomSeed - Seed for any random number generators used internally.

selectSeeds

public void selectSeeds(java.util.List<double[]> points,
                        java.util.List<double[]> seeds)

Specified by:

selectSeeds in interface InitializeKMeans_F64

Parameters:

points - Set of points which is to be clustered.

seeds - List full of points which will act as the initial seed for k-means.