hidden Markov model

A Markov model in which the system being modeled is assumed to be a Markov process with unobservable states. The model provides an observ­able process whose outcomes are influenced by the outcomes of a Markov model in a known way. An HMM can be used to describe the evolution of observable events that depend on internal factors that are not directly observable. In ma­chine learning, it is assumed that the internal state of a model is hidden but not its hyperparameters.