Uses of Class
elki.clustering.kmeans.AbstractKMeans

Packages that use AbstractKMeans Package Description elki.clustering.kmeans Kmeans clustering and variations.elki.clustering.kmeans.parallel Parallelized implementations of kmeans.elki.clustering.kmeans.spherical Spherical kmeans clustering and variations.tutorial.clustering Classes from the tutorial on implementing a custom kmeans variation. 

Uses of AbstractKMeans in elki.clustering.kmeans
Subclasses of AbstractKMeans in elki.clustering.kmeans Modifier and Type Class Description class
AnnulusKMeans<V extends NumberVector>
Annulus kmeans algorithm.class
BetulaLloydKMeans
BIRCH/BETULAbased clustering algorithm that simply treats the leafs of the CFTree as clusters.class
CompareMeans<V extends NumberVector>
CompareMeans: Accelerated kmeans by exploiting the triangle inequality and pairwise distances of means to prune candidate means.class
ElkanKMeans<V extends NumberVector>
Elkan's fast kmeans by exploiting the triangle inequality.class
ExponionKMeans<V extends NumberVector>
Newlings's Exponion kmeans algorithm, exploiting the triangle inequality.class
GMeans<V extends NumberVector,M extends MeanModel>
GMeans extends KMeans and estimates the number of centers with Anderson Darling Test.
Implemented as specialization of XMeans.class
HamerlyKMeans<V extends NumberVector>
Hamerly's fast kmeans by exploiting the triangle inequality.class
HartiganWongKMeans<V extends NumberVector>
Hartigan and Wong kmeans clustering.class
KDTreeFilteringKMeans<V extends NumberVector>
Filtering or "blacklisting" Kmeans with kdtree acceleration.class
KDTreePruningKMeans<V extends NumberVector>
Pruning Kmeans with kdtree acceleration.class
KMeansMinusMinus<V extends NumberVector>
kmeans: A Unified Approach to Clustering and Outlier Detection.class
KMediansLloyd<V extends NumberVector>
kmedians clustering algorithm, but using Lloydstyle bulk iterations instead of the more complicated approach suggested by Kaufman and Rousseeuw (seePAM
instead).class
LloydKMeans<V extends NumberVector>
The standard kmeans algorithm, using bulk iterations and commonly attributed to Lloyd and Forgy (independently).class
MacQueenKMeans<V extends NumberVector>
The original kmeans algorithm, using MacQueen style incremental updates; making this effectively an "online" (streaming) algorithm.class
ShallotKMeans<V extends NumberVector>
Borgelt's Shallot kmeans algorithm, exploiting the triangle inequality.class
SimplifiedElkanKMeans<V extends NumberVector>
Simplified version of Elkan's kmeans by exploiting the triangle inequality.class
SingleAssignmentKMeans<V extends NumberVector>
Pseudokmeans variations, that assigns each object to the nearest center.class
SortMeans<V extends NumberVector>
SortMeans: Accelerated kmeans by exploiting the triangle inequality and pairwise distances of means to prune candidate means (with sorting).class
XMeans<V extends NumberVector,M extends MeanModel>
Xmeans: Extending Kmeans with Efficient Estimation on the Number of Clusters.class
YinYangKMeans<V extends NumberVector>
YinYang kMeans Clustering.Methods in elki.clustering.kmeans that return AbstractKMeans Modifier and Type Method Description abstract AbstractKMeans<V,?>
AbstractKMeans.Par. make()

Uses of AbstractKMeans in elki.clustering.kmeans.parallel
Subclasses of AbstractKMeans in elki.clustering.kmeans.parallel Modifier and Type Class Description class
ParallelLloydKMeans<V extends NumberVector>
Parallel implementation of kMeans clustering. 
Uses of AbstractKMeans in elki.clustering.kmeans.spherical
Subclasses of AbstractKMeans in elki.clustering.kmeans.spherical Modifier and Type Class Description class
EuclideanSphericalElkanKMeans<V extends NumberVector>
Elkan's fast kmeans by exploiting the triangle inequality in the corresponding Euclidean space.class
EuclideanSphericalHamerlyKMeans<V extends NumberVector>
A spherical kMeans algorithm based on Hamerly's fast kmeans by exploiting the triangle inequality in the corresponding Euclidean space.class
EuclideanSphericalSimplifiedElkanKMeans<V extends NumberVector>
A spherical kMeans algorithm based on Hamerly's fast kmeans by exploiting the triangle inequality in the corresponding Euclidean space.class
SphericalElkanKMeans<V extends NumberVector>
Elkan's fast kmeans by exploiting the triangle inequality.class
SphericalHamerlyKMeans<V extends NumberVector>
A spherical kMeans algorithm based on Hamerly's fast kmeans by exploiting the triangle inequality.class
SphericalKMeans<V extends NumberVector>
The standard spherical kmeans algorithm.class
SphericalSimplifiedElkanKMeans<V extends NumberVector>
A spherical kMeans algorithm based on Hamerly's fast kmeans by exploiting the triangle inequality.class
SphericalSimplifiedHamerlyKMeans<V extends NumberVector>
A spherical kMeans algorithm based on Hamerly's fast kmeans by exploiting the triangle inequality.class
SphericalSingleAssignmentKMeans<V extends NumberVector>
PseudokMeans variations, that assigns each object to the nearest center. 
Uses of AbstractKMeans in tutorial.clustering
Subclasses of AbstractKMeans in tutorial.clustering Modifier and Type Class Description class
SameSizeKMeans<V extends NumberVector>
Kmeans variation that produces equally sized clusters.
