clvalidity: compute and plot cluster validity

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/clvalidity.R

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

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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 ∑_j W_j divided by ∑_{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

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

Example output

Loading required package: rpart
Loading required package: robustbase

chemometrics documentation built on May 1, 2019, 7:58 p.m.