All Tools Bookmark

Share

http://online-toolz.com/tools/r-package-details.php?p=clusterSim

Facebook Share Twitter Share

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).

clusterSim.pdf