Uses of Interface
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMedoidsInitialization

Packages that use KMedoidsInitialization

Package	Description
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.

Uses of KMedoidsInitialization in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Classes in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans that implement KMedoidsInitialization

Modifier and Type	Class and Description
class	FirstKInitialMeans<V> Initialize K-means by using the first k objects as initial means.
class	KMeansPlusPlusInitialMeans<V,D extends NumberDistance<D,?>> K-Means++ initialization for k-means.
class	PAMInitialMeans<V,D extends NumberDistance<D,?>> PAM initialization for k-means (and of course, PAM).
class	RandomlyChosenInitialMeans<V> Initialize K-means by randomly choosing k exsiting elements as cluster centers.

Fields in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans declared as KMedoidsInitialization

Modifier and Type	Field and Description
protected KMedoidsInitialization<V>	KMedoidsEM.initializer Method to choose initial means.
protected KMedoidsInitialization<V>	KMedoidsEM.Parameterizer.initializer
protected KMedoidsInitialization<V>	KMedoidsPAM.initializer Method to choose initial means.
protected KMedoidsInitialization<V>	KMedoidsPAM.Parameterizer.initializer

Constructors in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans with parameters of type KMedoidsInitialization

Constructor and Description
KMedoidsEM(PrimitiveDistanceFunction<? super V,D> distanceFunction, int k, int maxiter, KMedoidsInitialization<V> initializer) Constructor.
KMedoidsPAM(PrimitiveDistanceFunction<? super V,D> distanceFunction, int k, int maxiter, KMedoidsInitialization<V> initializer) Constructor.