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

Packages that use AbstractNumberVectorDistanceBasedAlgorithm

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.
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel	Parallelized implementations of k-means.
de.lmu.ifi.dbs.elki.algorithm.outlier.distance	Distance-based outlier detection algorithms, such as DBOutlier and kNN.
de.lmu.ifi.dbs.elki.algorithm.statistics	Statistical analysis algorithms.

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

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

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

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

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

Modifier and Type	Class and Description
class	AbstractKMeans<V extends NumberVector,M extends Model> Abstract base class for k-means implementations.
class	KMeansBatchedLloyd<V extends NumberVector> An algorithm for k-means, using Lloyd-style bulk iterations.
class	KMeansElkan<V extends NumberVector> Elkan's fast k-means by exploiting the triangle inequality.
class	KMeansHamerly<V extends NumberVector> Hamerly's fast k-means by exploiting the triangle inequality.
class	KMeansHybridLloydMacQueen<V extends NumberVector> A hybrid k-means algorithm, alternating between MacQueen-style incremental processing and Lloyd-Style batch steps.
class	KMeansLloyd<V extends NumberVector> The standard k-means algorithm, using Lloyd-style bulk iterations.
class	KMeansMacQueen<V extends NumberVector> The original k-means algorithm, using MacQueen style incremental updates; making this effectively an "online" (streaming) algorithm.
class	KMediansLloyd<V extends NumberVector> k-medians clustering algorithm, but using Lloyd-style bulk iterations instead of the more complicated approach suggested by Kaufman and Rousseeuw (see KMedoidsPAM instead).
class	SingleAssignmentKMeans<V extends NumberVector> Pseudo-k-Means variations, that assigns each object to the nearest center.
class	XMeans<V extends NumberVector,M extends MeanModel> X-means: Extending K-means with Efficient Estimation on the Number of Clusters.

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

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

Modifier and Type	Class and Description
class	ParallelLloydKMeans<V extends NumberVector> Parallel implementation of k-Means clustering.

Uses of AbstractNumberVectorDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm.outlier.distance

Subclasses of AbstractNumberVectorDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm.outlier.distance

Modifier and Type	Class and Description
class	ReferenceBasedOutlierDetection Reference-Based Outlier Detection algorithm, an algorithm that computes kNN distances approximately, using reference points.

Uses of AbstractNumberVectorDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm.statistics

Subclasses of AbstractNumberVectorDistanceBasedAlgorithm in de.lmu.ifi.dbs.elki.algorithm.statistics

Modifier and Type	Class and Description
class	HopkinsStatisticClusteringTendency The Hopkins Statistic of Clustering Tendency measures the probability that a data set is generated by a uniform data distribution.