Clustering evaluation through internal criteria
Evaluation a clustering algorithm according to internal criteria.
intern(clus, d, eval = "intraclass", type = c("global", "cluster"))clus |
The extracted clusters. |
d |
The dataset. |
eval |
The evaluation criteria. |
type |
Indicates whether a "global" or a "cluster"-wise evaluation should be used. |
The evaluation of the clustering.
require (datasets)
data (iris)
km = KMEANS (iris [, -5], k = 3)
intern (km$clus, iris [, -5])
intern (km$clus, iris [, -5], type = "cluster")
intern (km$clus, iris [, -5], eval = c ("intraclass", "interclass"))
intern (km$clus, iris [, -5], eval = c ("intraclass", "interclass"), type = "cluster")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.