The Baum–Welch algorithm is used for computing maximum likelihood estimates and posterior mode estimates for the parameters (transition and emission probabilities) of a HMM, when given only output sequences (emissions) as training data.
The Baum–Welch algorithm is a particular instantiation of the expectation-maximization algorithm, suited for HMMs.
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(2017). Baum-Welch Algorithm. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning and Data Mining. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7687-1_59
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DOI: https://doi.org/10.1007/978-1-4899-7687-1_59
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