Uses of Class
elki.clustering.kmeans.AbstractKMeans
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Packages that use AbstractKMeans Package Description elki.clustering.kmeans K-means clustering and variations.elki.clustering.kmeans.parallel Parallelized implementations of k-means.elki.clustering.kmeans.spherical Spherical k-means clustering and variations.tutorial.clustering Classes from the tutorial on implementing a custom k-means variation. -
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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 k-means algorithm.class
BetulaLloydKMeans
BIRCH/BETULA-based clustering algorithm that simply treats the leafs of the CFTree as clusters.class
CompareMeans<V extends NumberVector>
Compare-Means: Accelerated k-means by exploiting the triangle inequality and pairwise distances of means to prune candidate means.class
ElkanKMeans<V extends NumberVector>
Elkan's fast k-means by exploiting the triangle inequality.class
ExponionKMeans<V extends NumberVector>
Newlings's Exponion k-means algorithm, exploiting the triangle inequality.class
GMeans<V extends NumberVector,M extends MeanModel>
G-Means extends K-Means and estimates the number of centers with Anderson Darling Test.
Implemented as specialization of XMeans.class
HamerlyKMeans<V extends NumberVector>
Hamerly's fast k-means by exploiting the triangle inequality.class
HartiganWongKMeans<V extends NumberVector>
Hartigan and Wong k-means clustering.class
KDTreeFilteringKMeans<V extends NumberVector>
Filtering or "blacklisting" K-means with k-d-tree acceleration.class
KDTreePruningKMeans<V extends NumberVector>
Pruning K-means with k-d-tree acceleration.class
KMeansMinusMinus<V extends NumberVector>
k-means--: A Unified Approach to Clustering and Outlier Detection.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 (seePAM
instead).class
LloydKMeans<V extends NumberVector>
The standard k-means algorithm, using bulk iterations and commonly attributed to Lloyd and Forgy (independently).class
MacQueenKMeans<V extends NumberVector>
The original k-means algorithm, using MacQueen style incremental updates; making this effectively an "online" (streaming) algorithm.class
ShallotKMeans<V extends NumberVector>
Borgelt's Shallot k-means algorithm, exploiting the triangle inequality.class
SimplifiedElkanKMeans<V extends NumberVector>
Simplified version of Elkan's k-means by exploiting the triangle inequality.class
SingleAssignmentKMeans<V extends NumberVector>
Pseudo-k-means variations, that assigns each object to the nearest center.class
SortMeans<V extends NumberVector>
Sort-Means: Accelerated k-means by exploiting the triangle inequality and pairwise distances of means to prune candidate means (with sorting).class
XMeans<V extends NumberVector,M extends MeanModel>
X-means: Extending K-means with Efficient Estimation on the Number of Clusters.class
YinYangKMeans<V extends NumberVector>
Yin-Yang k-Means Clustering.Methods in elki.clustering.kmeans that return AbstractKMeans Modifier and Type Method Description abstract AbstractKMeans<V,?>
AbstractKMeans.Par. make()
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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 k-Means 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 k-means by exploiting the triangle inequality in the corresponding Euclidean space.class
EuclideanSphericalHamerlyKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality in the corresponding Euclidean space.class
EuclideanSphericalSimplifiedElkanKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality in the corresponding Euclidean space.class
SphericalElkanKMeans<V extends NumberVector>
Elkan's fast k-means by exploiting the triangle inequality.class
SphericalHamerlyKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.class
SphericalKMeans<V extends NumberVector>
The standard spherical k-means algorithm.class
SphericalSimplifiedElkanKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.class
SphericalSimplifiedHamerlyKMeans<V extends NumberVector>
A spherical k-Means algorithm based on Hamerly's fast k-means by exploiting the triangle inequality.class
SphericalSingleAssignmentKMeans<V extends NumberVector>
Pseudo-k-Means 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>
K-means variation that produces equally sized clusters.
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