intern.intraclass {fdm2id}

Clustering evaluation through intraclass inertia

Description

Evaluation a clustering algorithm according to intraclass inertia.

Usage

intern.intraclass(clus, d, type = c("global", "cluster"))

Arguments

clus

The extracted clusters.

d

The dataset.

type

Indicates whether a "global" or a "cluster"-wise evaluation should be used.

Value

The evaluation of the clustering.

See Also

intern, intern.dunn, intern.interclass

Examples

require (datasets)
data (iris)
km = KMEANS (iris [, -5], k = 3)
intern.intraclass (km$clus, iris [, -5])