The BIC was developed by Gideon E. Schwarz, who gave a Bayesian argument for adopting it.
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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.