clusterSim (0.45-2)

Searching for Optimal Clustering Procedure for a Data Set.

Distance measures (GDM1, GDM2, Sokal-Michener, Bray-Curtis, for symbolic interval-valued data), cluster quality indices (Calinski-Harabasz, Baker-Hubert, Hubert-Levine, Silhouette, Krzanowski-Lai, Hartigan, Gap, Davies-Bouldin), data normalization formulas, data generation (typical and non-typical data), HINoV method, replication analysis, linear ordering methods, spectral clustering, agreement indices between two partitions, plot functions (for categorical and symbolic interval-valued data).

Maintainer: Andrzej Dudek
Author(s): Marek Walesiak <> Andrzej Dudek <>

License: GPL (>= 2)

Uses: ade4, cluster, e1071, MASS, modeest, R2HTML, rgl, mlbench, testthat
Reverse depends: conjoint, emma, mdsOpt, Metabonomic, RandForestGUI, symbolicDA
Reverse suggests: mlr, spectralGraphTopology

Released about 3 years ago.