Package | Description |
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de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
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de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.parallel |
Parallelized implementations of k-means.
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Modifier and Type | Class and Description |
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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.
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Modifier and Type | Method and Description |
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protected abstract AbstractKMeans<V,?> |
AbstractKMeans.Parameterizer.makeInstance() |
Modifier and Type | Class and Description |
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class |
ParallelLloydKMeans<V extends NumberVector>
Parallel implementation of k-Means clustering.
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Copyright © 2015 ELKI Development Team, Lehr- und Forschungseinheit für Datenbanksysteme, Ludwig-Maximilians-Universität München. License information.