Uses of Class
de.lmu.ifi.dbs.elki.algorithm.AbstractPrimitiveDistanceBasedAlgorithm

Packages that use AbstractPrimitiveDistanceBasedAlgorithm

Package	Description
de.lmu.ifi.dbs.elki.algorithm	Algorithms suitable as a task for the KDDTask main routine.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans	K-means clustering and variations.
tutorial.clustering	Classes from the tutorial on implementing a custom k-means variation.

Uses of AbstractPrimitiveDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm

Subclasses of AbstractPrimitiveDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm

Modifier and Type	Class and Description
class	DependencyDerivator<V extends NumberVector<?>,D extends Distance<D>> Dependency derivator computes quantitatively linear dependencies among attributes of a given dataset based on a linear correlation PCA.

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

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

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

Uses of AbstractPrimitiveDistanceBasedAlgorithm in tutorial.clustering

Subclasses of AbstractPrimitiveDistanceBasedAlgorithm in tutorial.clustering

Modifier and Type	Class and Description
class	SameSizeKMeansAlgorithm<V extends NumberVector<?>> K-means variation that produces equally sized clusters.