nomclust (version 1.1.1106)

evalclust: Evaluation of the Clustering

Description

The function evaluates clustering results no matter which clustering method they were obtained by. The clusters are evaluated from a point of view of the within-cluster variability by the following indices: Within-cluster mutability coefficient (WCM), Within-cluster entropy coefficient (WCE), Pseudo tau coefficient (PSTau), Pseudo uncertainty coefficient (PSU) and Pseudo F, Indices based on the mutability (PSFM) and the entropy (PSFE).

Usage

evalclust(data, num_var, clu_low = 2, clu_high = 6)

Arguments

data

data frame or matrix with cases in rows and variables in colums. First m1 variables are the original data used for clustering, the next m2 variables express the cluster memberships in an increasing way (e.g. from clu_2 to clu_6).

num_var

numeric value which determines how many variables in a dataset were used for the clustering.

clu_low

numeric value expressing the lower bound for number of cluster solutions.

clu_high

numeric value expressing the higher bound for number of cluster solutions.

Value

Function returns a data frame, where the rows express a serie of cluster solutions and columns clustering evaluation statistics in a following order: WCM, WCE, PSTau, PSU, PSFM, PSFE.

See Also

nomclust.

Examples

# NOT RUN {
#sample data
data(data20)
#creation of a dataset with cluster memberships
data_clu <- nomclust(data20, iof, clu_high = 7)
#binding an original dataset to cluster memberships variables
data_clu2 <- cbind(data20, data_clu$mem)
#evaluation of created clusters
evaluation <- evalclust(data_clu2, 5, clu_high = 7)

# }