intern.intraclass: Clustering evaluation through intraclass inertia
In fdm2id: Data Mining and R Programming for Beginners
intern.intraclass R Documentation
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$clus, iris [, -5])
fdm2id documentation built on July 9, 2023, 6:05 p.m.
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| intern.intraclass | R Documentation |
Clustering evaluation through intraclass inertia
Description
Evaluation a clustering algorithm according to intraclass inertia.
Usage
intern.intraclass(clus, d, type = c("global", "cluster"))
Arguments
clus |
The extracted clusters. |
d |
The dataset. |
type |
Indicates whether a "global" or a "cluster"-wise evaluation should be used. |
Value
The evaluation of the clustering.
See Also
intern, intern.dunn, intern.interclass
Examples
require (datasets)
data (iris)
km = KMEANS (iris [, -5], k = 3)
intern.intraclass (km$clus, iris [, -5])
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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