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When fitting finite mixtures to multivariate data, it is crucial to select the appropriate number of components. Under regularization theory, we aim to resolve this ldquounsupervisedrdquo learning problem via regularizing the likelihood by the full entropy of posterior probabilities for finite mixture fitting. Two deterministic annealing implementations are further proposed for this entropy regularized...
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