Package elki.clustering.kmeans.initialization

Class SphericalAFKMC2

java.lang.Object

elki.clustering.kmeans.initialization.AbstractKMeansInitialization

elki.clustering.kmeans.initialization.KMC2

elki.clustering.kmeans.initialization.AFKMC2

elki.clustering.kmeans.initialization.SphericalAFKMC2

All Implemented Interfaces:

KMeansInitialization

@Title("Spherical AFK-MC\u00b2")
@Reference(authors="R. Pratap, A. A. Deshmukh, P. Nair, T. Dutt",
           title="A Faster Sampling Algorithm for Spherical k-means",
           booktitle="Proc. 10th Asian Conference on Machine Learning, ACML",
           url="http://proceedings.mlr.press/v95/pratap18a.html",
           bibkey="DBLP:conf/acml/PratapDND18")
public class SphericalAFKMC2
extends AFKMC2

Spherical K-Means++ initialization with markov chains.

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

Reference:

R. Pratap, A. A. Deshmukh, P. Nair, T. Dutt
A Faster Sampling Algorithm for Spherical k-means
Proc. 10th Asian Conference on Machine Learning, ACML

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
protected static class	SphericalAFKMC2.Instance	Abstract instance implementing the weight handling.
static class	SphericalAFKMC2.Par	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.KMC2

m

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

rnd

Constructor Summary

Constructors

Constructor	Description
SphericalAFKMC2(int m, 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

SphericalAFKMC2

public SphericalAFKMC2(int m,
                       double alpha,
                       RandomFactory rnd)

Constructor.

Parameters:

m - M parameter

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

Specified by:

chooseInitialMeans in interface KMeansInitialization

Overrides:

chooseInitialMeans in class AFKMC2

Parameters:

relation - Relation

k - Parameter k

distance - Distance function

Returns:

List of chosen means for k-means