On choosing a mixture model for clustering

  title={On choosing a mixture model for clustering},
  author={Joseph Ngatchou-Wandji and Jan Bulla},
Two methods for clustering data and choosing a mixture model are proposed. First, we derive a new classification algorithm based on the classification likelihood. Then, the likelihood conditional on these clusters is written as the product of likelihoods of each cluster, and AICrespectively BIC-type approximations are applied. The resulting criteria turn out to be the sum of the AIC or BIC relative to each cluster plus an entropy term. The performances of our methods are evaluated by Monte… CONTINUE READING
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