Hidden Markov Model in Machine learning

Hidden Markov Model in Machine learning

A Hidden Markov Model (HMM) is a statistical probabilistic framework used to model a system assumed to be a Markov process with unobservable (hidden) states. In machine learning, it is utilized to predict a sequence of hidden variables based on a sequence of observable events.