Algorithms of distancebased kmedoids clustering: simple and fast kmedoids, ranked kmedoids, and increasing number of clusters in kmedoids. Calculate distances for mixed variable data such as Gower, Podani, Wishart, Huang, HarikumarPV, and AhmadDey. Cluster validations apply internal and relative criteria. The internal criteria include silhouette index and shadow values. The relative criterium applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm such as ward, complete, or centroid linkages. The cluster result can be plotted in a marked barplot or pca biplot.
Package details 


Author  Weksi Budiaji 
Maintainer  Weksi Budiaji <budiaji@untirta.ac.id> 
License  GPL3 
Version  0.3.0 
Package repository  View on CRAN 
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