Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization |
Initialization strategies for k-means.
|
de.lmu.ifi.dbs.elki.index.idistance |
iDistance is a distance based indexing technique, using a reference points embedding.
|
Modifier and Type | Field and Description |
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protected KMedoidsInitialization<V> |
KMedoidsPAM.initializer
Method to choose initial means.
|
protected KMedoidsInitialization<V> |
KMedoidsPAM.Parameterizer.initializer
Method to choose initial means.
|
protected KMedoidsInitialization<V> |
KMedoidsEM.initializer
Method to choose initial means.
|
protected KMedoidsInitialization<V> |
KMedoidsEM.Parameterizer.initializer |
Constructor and Description |
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CLARA(DistanceFunction<? super V> distanceFunction,
int k,
int maxiter,
KMedoidsInitialization<V> initializer,
int numsamples,
double sampling,
RandomFactory random)
Constructor.
|
KMedoidsEM(DistanceFunction<? super V> distanceFunction,
int k,
int maxiter,
KMedoidsInitialization<V> initializer)
Constructor.
|
KMedoidsPAM(DistanceFunction<? super V> distanceFunction,
int k,
int maxiter,
KMedoidsInitialization<V> initializer)
Constructor.
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Modifier and Type | Class and Description |
---|---|
class |
FarthestPointsInitialMeans<O>
K-Means initialization by repeatedly choosing the farthest point (by the
minimum distance to earlier points).
|
class |
FarthestSumPointsInitialMeans<O>
K-Means initialization by repeatedly choosing the farthest point (by the
sum of distances to previous objects).
|
class |
FirstKInitialMeans<O>
Initialize K-means by using the first k objects as initial means.
|
class |
KMeansPlusPlusInitialMeans<O>
K-Means++ initialization for k-means.
|
class |
PAMInitialMeans<O>
PAM initialization for k-means (and of course, PAM).
|
class |
RandomlyChosenInitialMeans<O>
Initialize K-means by randomly choosing k existing elements as cluster
centers.
|
Modifier and Type | Field and Description |
---|---|
private KMedoidsInitialization<O> |
InMemoryIDistanceIndex.initialization
Initialization method.
|
(package private) KMedoidsInitialization<V> |
InMemoryIDistanceIndex.Factory.initialization
Initialization method.
|
(package private) KMedoidsInitialization<V> |
InMemoryIDistanceIndex.Factory.Parameterizer.initialization
Initialization method.
|
Constructor and Description |
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InMemoryIDistanceIndex.Factory(DistanceFunction<? super V> distance,
KMedoidsInitialization<V> initialization,
int k)
Constructor.
|
InMemoryIDistanceIndex(Relation<O> relation,
DistanceQuery<O> distance,
KMedoidsInitialization<O> initialization,
int numref)
Constructor.
|
Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.