Uses of Class
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans

Packages that use AbstractKMeans

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

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

Subclasses of AbstractKMeans in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Modifier and Type	Class and Description
class	KMeansLloyd<V extends NumberVector<V,?>,D extends Distance<D>> Provides the k-means algorithm, using Lloyd-style bulk iterations.
class	KMeansMacQueen<V extends NumberVector<V,?>,D extends Distance<D>> Provides the k-means algorithm, using MacQueen style incremental updates.
class	KMediansLloyd<V extends NumberVector<V,?>,D extends Distance<D>> Provides the k-medians clustering algorithm, using Lloyd-style bulk iterations.

Methods in de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans that return AbstractKMeans

Modifier and Type	Method and Description
protected AbstractKMeans<V,D>	KMeansLloyd.Parameterizer.makeInstance()
protected AbstractKMeans<V,D>	KMeansMacQueen.Parameterizer.makeInstance()
protected AbstractKMeans<V,D>	KMediansLloyd.Parameterizer.makeInstance()