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.
| Version: |
0.2.0 |
| Imports: |
stats, graphics, grDevices, utils, parallel |
| Suggests: |
CompQuadForm, MixSim, mclust, broom, tibble, testthat (≥
3.0.0), knitr, rmarkdown |
| Published: |
2026-07-19 |
| DOI: |
10.32614/CRAN.package.MergeKmeans (may not be active yet) |
| Author: |
Aqi Dong  [aut,
cre],
Volodymyr Melnykov [aut],
Yang-Li Liao [aut],
Peng Li [aut],
Xuejian Li [aut] |
| Maintainer: |
Aqi Dong <donga2 at erau.edu> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
MergeKmeans results |
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