clusterSim: 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 categorial and symbolic interval-valued data).

Version: 0.44-2
Depends: cluster, MASS
Imports: ade4, e1071, rgl, R2HTML
Suggests: mlbench
Published: 2015-03-14
Author: Marek Walesiak Andrzej Dudek
Maintainer: Andrzej Dudek <andrzej.dudek at ue.wroc.pl>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: http://keii.ue.wroc.pl/clusterSim
NeedsCompilation: yes
In views: Cluster, Multivariate
CRAN checks: clusterSim results

Downloads:

Reference manual: clusterSim.pdf
Package source: clusterSim_0.44-2.tar.gz
Windows binaries: r-devel: clusterSim_0.44-2.zip, r-release: clusterSim_0.44-2.zip, r-oldrel: clusterSim_0.44-2.zip
OS X Snow Leopard binaries: r-oldrel: clusterSim_0.43-5.tgz
OS X Mavericks binaries: r-release: clusterSim_0.44-2.tgz
Old sources: clusterSim archive

Reverse dependencies:

Reverse depends: emma, symbolicDA
Reverse imports: comato, conjoint
Reverse suggests: mlr