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: |
0.44-5 |
Depends: |
cluster, MASS |
Imports: |
ade4, e1071, rgl, R2HTML, modeest, grDevices, graphics, stats, utils |
Suggests: |
mlbench |
Published: |
2016-08-04 |
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:
Reverse dependencies:
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