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Information and Entropy in Cluster Analysis,etized distributions ....), ..(..) (. = 1,…, .) will be maximized (e.g., Kullback-Leibler’s discrimination information or the .. noncentrality parameter). We conclude with some comments on methods for selecting a suitable number of classes, e.g., by using A. information criterion AIC and its modifications.

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