clvalidity: compute and plot cluster validity

View source: R/clvalidity.R

clvalidityR Documentation

compute and plot cluster validity

Description

A cluster validity measure based on within- and between-sum-of-squares is computed and plotted for the methods k-means, fuzzy c-means, and model-based clustering.

Usage

clvalidity(x, clnumb = c(2:10))

Arguments

x

input data matrix

clnumb

range for the desired number of clusters

Details

The validity measure for a number k of clusters is \sum_j W_j divided by \sum_{j<l} B_{jl} with W_j is the sum of squared distances of the objects in each cluster cluster to its center, and B_{jl} is the squared distance between the cluster centers of cluster j and l.

Value

validity

vector with validity measure for the desired numbers of clusters

Author(s)

Peter Filzmoser <P.Filzmoser@tuwien.ac.at>

References

K. Varmuza and P. Filzmoser: Introduction to Multivariate Statistical Analysis in Chemometrics. CRC Press, Boca Raton, FL, 2009.

See Also

princomp

Examples

data(glass)
require(robustbase)
res <- pcaCV(glass,segments=4,repl=100,cex.lab=1.2,ylim=c(0,1),las=1)

chemometrics documentation built on Aug. 25, 2023, 5:18 p.m.