A hidden Markov model (HMM) is a statistical model that can be used to describe the evolution of observable events that depend on internal factors, which are not directly observable. When an HMM is used to evaluate the relevance of a hypothesis for a particular output sequence, the statistical significance indicates the false positive rate. In Computational Biology, a hidden Markov model (HMM) is a statistical approach that is frequently used for modelling biological sequences. Hidden Markov Models (HMMs) – A. So in this chapter, we introduce the full set of algorithms for. A similar approach to the one above can be used for parameter learning of the HMM model.

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