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Evaluation a clustering algorithm according to interclass inertia.
intern.interclass(clus, d, type = c("global", "cluster"))
The extracted clusters.
The dataset.
Indicates whether a "global" or a "cluster"-wise evaluation should be used.
The evaluation of the clustering.
intern, intern.dunn, intern.intraclass
intern
intern.dunn
intern.intraclass
# NOT RUN { require (datasets) data (iris) km = KMEANS (iris [, -5], k = 3) intern.interclass (km$clus, iris [, -5]) # }
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