Package: MajKMeans 0.1.0
MajKMeans: k-Means Algorithm with a Majorization-Minimization Method
A hybrid of the K-means algorithm and a Majorization-Minimization method to introduce a robust clustering. The reference paper is: Julien Mairal, (2015) <doi:10.1137/140957639>. The two most important functions in package 'MajKMeans' are cluster_km() and cluster_MajKm(). cluster_km() clusters data without Majorization-Minimization and cluster_MajKm() clusters data with Majorization-Minimization method. Both of these functions calculate the sum of squares (SS) of clustering.
Authors:
MajKMeans_0.1.0.tar.gz
MajKMeans_0.1.0.zip(r-4.7)MajKMeans_0.1.0.zip(r-4.6)MajKMeans_0.1.0.zip(r-4.5)
MajKMeans_0.1.0.tgz(r-4.6-any)MajKMeans_0.1.0.tgz(r-4.5-any)
MajKMeans_0.1.0.tar.gz(r-4.7-any)MajKMeans_0.1.0.tar.gz(r-4.6-any)
MajKMeans_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
MajKMeans/json (API)
| # Install 'MajKMeans' in R: |
| install.packages('MajKMeans', repos = c('https://sheikhi-a.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/sheikhi-a/majkmeans/issues
Last updated from:2e2cb82dea. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 96 | ||
| source / vignettes | OK | 147 | ||
| linux-release-x86_64 | NOTE | 106 | ||
| macos-release-arm64 | NOTE | 148 | ||
| macos-oldrel-arm64 | NOTE | 213 | ||
| windows-devel | NOTE | 72 | ||
| windows-release | NOTE | 64 | ||
| windows-oldrel | NOTE | 74 | ||
| wasm-release | OK | 138 |
Exports:clusters_kmclusters_MajKmEuclidkmeans
Dependencies:MASS
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| clustering results of the k-mean algorithm | clusters_km |
| clustering results of the majorized k-mean algorithm | clusters_MajKm |
| Euclidian distance | Euclid |
| k-means function | kmeans |
