Searching for optimal clustering procedure for a data set

Documentation for package `clusterSim' version 0.30-7

cluster.Description	Descriptive statistics calculated separately for each cluster and variable
cluster.Sim	Determination of optimal clustering procedure for a data set
data.Normalization	Types of variable normalization formulas
data_binary	Binary data
data_interval	Interval data
data_mixed	Mixed data
data_nominal	Nominal data
data_ordinal	Ordinal data
data_ratio	Ratio data
data_symbolic	Symbolic interval data
dist.BC	Calculates Bray-Curtis distance measure for ratio data
dist.GDM	Calculates Generalized Distance Measure
dist.SM	Calculates Sokal-Michener distance measure for nominal variables
GDM	Calculates Generalized Distance Measure
GDM1	Calculates Generalized Distance Measure
GDM2	Calculates Generalized Distance Measure
HINoV.Mod	Modification of Carmone, Kara & Maxwell Heuristic Identification of Noisy Variables (HINoV) method
HINoV.Symbolic	Modification of Carmone, Kara & Maxwell Heuristic Identification of Noisy Variables (HINoV) method for symbolic interval data
index.G1	Calculates Calinski-Harabasz pseudo F-statistic
index.G2	Calculates G2 internal cluster quality index
index.G3	Calculates G3 internal cluster quality index
index.Gap	Calculates Tibshirani, Walther and Hastie gap index
index.H	Calculates Hartigan index
index.KL	Calculates Krzanowski-Lai index
index.S	Calculates Rousseeuw's Silhouette internal cluster quality index
initial.Centers	Calculation of initial clusters centers for k-means like alghoritms
replication.Mod	Modification of replication analysis for cluster validation