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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.

Versions across snapshots

VersionRepositoryFileSize
0.4.2 rolling linux/jammy R-4.5 kmed_0.4.2.tar.gz 275.3 KiB
0.4.2 rolling linux/noble R-4.5 kmed_0.4.2.tar.gz 275.4 KiB
0.4.2 rolling source/ R- kmed_0.4.2.tar.gz 181.3 KiB
0.4.2 latest linux/jammy R-4.5 kmed_0.4.2.tar.gz 275.3 KiB
0.4.2 latest linux/noble R-4.5 kmed_0.4.2.tar.gz 275.4 KiB
0.4.2 latest source/ R- kmed_0.4.2.tar.gz 181.3 KiB
0.4.2 2026-04-26 source/ R- kmed_0.4.2.tar.gz 181.3 KiB
0.4.2 2026-04-23 source/ R- kmed_0.4.2.tar.gz 181.3 KiB
0.4.2 2026-04-09 windows/windows R-4.5 kmed_0.4.2.zip 275.7 KiB
0.4.2 2025-04-20 source/ R- kmed_0.4.2.tar.gz 181.3 KiB

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