Another set of methods for determining the number of clusters are information criteria, such as the Akaike information criterion (AIC), Bayesian information criterion (BIC), or the Deviance information criterion (DIC) — if it is possible to make a likelihood function for the clustering model.
In the early 1970s he formulated an information criterion for model identification which has become known as the Akaike information criterion.
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