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MergeKmeans

Clustering Large Datasets by Merging K-Means Solutions

Fast clustering of large datasets by hierarchically merging components of a K-means solution based on the pairwise overlap between the Gaussian mixture components implied by the K-means partition, as proposed by Melnykov and Michael (2020) <doi:10.1007/s00357-019-09314-8>. Implements the DEMP-K merging algorithm with single, Ward's, average, and complete linkages, the overlap map display for selecting the number of clusters, four K-means variants corresponding to Gaussian mixtures with spherical or elliptical, homoscedastic or heteroscedastic components, and a tool for selecting the number of K-means components.

Versions across snapshots

VersionRepositoryFileSize
0.2.0 rolling linux/jammy R-4.5 MergeKmeans_0.2.0.tar.gz 457.5 KiB
0.2.0 rolling linux/noble R-4.5 MergeKmeans_0.2.0.tar.gz 457.5 KiB
0.2.0 rolling source/ R- MergeKmeans_0.2.0.tar.gz 376.5 KiB
0.2.0 latest linux/jammy R-4.5 MergeKmeans_0.2.0.tar.gz 457.5 KiB
0.2.0 latest linux/noble R-4.5 MergeKmeans_0.2.0.tar.gz 457.5 KiB
0.2.0 latest source/ R- MergeKmeans_0.2.0.tar.gz 376.5 KiB
0.2.0 2026-04-23 source/ R- MergeKmeans_0.2.0.tar.gz 0 B

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