Package elki.clustering.kmeans.initialization

Class SphericalKMeansPlusPlus<O>

java.lang.Object

elki.clustering.kmeans.initialization.AbstractKMeansInitialization

elki.clustering.kmeans.initialization.SphericalKMeansPlusPlus<O>

Type Parameters:

O - Vector type

All Implemented Interfaces:

KMeansInitialization

@Title("Spherical K-means++")
@Reference(authors="Y. Endo and S. Miyamoto",
           title="Spherical k-Means++ Clustering",
           booktitle="Modeling Decisions for Artificial Intelligence",
           url="https://doi.org/10.1007/978-3-319-23240-9_9",
           bibkey="DBLP:conf/mdai/EndoM15")
public class SphericalKMeansPlusPlus<O>
extends AbstractKMeansInitialization

Spherical K-Means++ initialization for k-means.

FIXME: currently assumes the vectors to be L2 normalized beforehand, but does not ensure that this is true.

Reference:

Y. Endo and S. Miyamoto
Spherical k-Means++ Clustering
Modeling Decisions for Artificial Intelligence

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected static class	SphericalKMeansPlusPlus.Instance	Abstract instance implementing the weight handling.
static class	SphericalKMeansPlusPlus.Par<V>	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
protected double	alpha	Parameter to balance distance vs. uniform sampling.
private static Logging	LOG	Class logger.

Fields inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

rnd

Constructor Summary

Constructors

Constructor	Description
SphericalKMeansPlusPlus(double alpha, RandomFactory rnd)	Constructor.

Method Summary

Modifier and Type	Method	Description
double[][]	chooseInitialMeans(Relation<? extends NumberVector> relation, int k, NumberVectorDistance<?> distance)	Choose initial means

Methods inherited from class elki.clustering.kmeans.initialization.AbstractKMeansInitialization

unboxVectors

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

alpha

protected double alpha

Parameter to balance distance vs. uniform sampling.

Constructor Detail

SphericalKMeansPlusPlus

public SphericalKMeansPlusPlus(double alpha,
                               RandomFactory rnd)

Constructor.

Parameters:

alpha - alpha-SKM parameter, usually 1.5

rnd - Random generator.

Method Detail

chooseInitialMeans

public double[][] chooseInitialMeans(Relation<? extends NumberVector> relation,
                                     int k,
                                     NumberVectorDistance<?> distance)

Description copied from interface: KMeansInitialization

Choose initial means

Parameters:

relation - Relation

k - Parameter k

distance - Distance function

Returns:

List of chosen means for k-means