Package: kmed 0.4.2
kmed: Distance-Based k-Medoids
Algorithms of distance-based k-medoids clustering: simple and fast k-medoids, ranked k-medoids, and increasing number of clusters in k-medoids. Calculate distances for mixed variable data such as Gower, Podani, Wishart, Huang, Harikumar-PV, and Ahmad-Dey. Cluster validation applies internal and relative criteria. The internal criteria includes silhouette index and shadow values. The relative criterium applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm such as complete, ward, or average linkages. The cluster result can be plotted in a marked barplot or pca biplot.
Authors:
kmed_0.4.2.tar.gz
kmed_0.4.2.zip(r-4.5)kmed_0.4.2.zip(r-4.4)kmed_0.4.2.zip(r-4.3)
kmed_0.4.2.tgz(r-4.4-any)kmed_0.4.2.tgz(r-4.3-any)
kmed_0.4.2.tar.gz(r-4.5-noble)kmed_0.4.2.tar.gz(r-4.4-noble)
kmed_0.4.2.tgz(r-4.4-emscripten)kmed_0.4.2.tgz(r-4.3-emscripten)
kmed.pdf |kmed.html✨
kmed/json (API)
NEWS
| # Install 'kmed' in R: |
| install.packages('kmed', repos = c('https://weksi-budiaji.r-universe.dev', 'https://cloud.r-project.org')) |
- clust4 - 4-clustered data set
- clust5 - 5-clustered data set
- globalfood - Global food security index
- heart - Heart Disease data set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:524e990059. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 29 2024 |
| R-4.5-win | OK | Oct 29 2024 |
| R-4.5-linux | OK | Oct 29 2024 |
| R-4.4-win | OK | Oct 29 2024 |
| R-4.4-mac | OK | Oct 29 2024 |
| R-4.3-win | OK | Oct 29 2024 |
| R-4.3-mac | OK | Oct 29 2024 |
Exports:barplotnumclustbootclustheatmapconsensusmatrixcooccurcsvdistmixdistNumericfastkmedinckmedmatchingmsvpcabiplotrankkmedsilskm
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
