Clustering evaluation through interclass inertia
Evaluation a clustering algorithm according to interclass inertia.
intern.interclass(clus, d, type = c("global", "cluster"))clus |
The extracted clusters. |
d |
The dataset. |
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.interclass (km$clus, iris [, -5])
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