AUTOMATIC DETERMINATION OF THE NUMBER OF CLUSTERS BY MIXTURES OF BAYESIAN NETWORKS

The invention automatically determines the number of clusters in a Bayesian network or in a mixture of Bayesian networks (MBN). A common external hidden variable is associated with the network. Expected sufficient statistics (ESS) are computed in the case of a Bayesian network or expected complete model sufficient statistics (ECMSS) are computed in the case of an MBN, from the observed data. An expected sample size for each state of a hidden variable is computed from the ESS or ECMSS. The optimum number of states is reached by deleting those states having a sample size less than a predetermined threshold.