Entropic priors for hidden-Markov model classification

Abstract

In pattern classification problems lack of knowledge about the prior distribution is typically filled up with uniform priors. However this choice may lead to unsatisfactory inference results when the amount of observed data is scarce. The application of Maximum Entropy (ME) principle to prior determination results in the so-called en-tropic priors, which… (More)

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