High Quality Content by WIKIPEDIA articles! The forward algorithm, in the context of a hidden Markov model, is used to calculate a 'belief state': the probability of a state at a certain time, given the history of evidence. The process is also known as filtering. The forward algorithm is closely related to, but distinct from, the Viterbi algorithm.In order to take into account future history (i.e., if one w ...Täielik kirjeldus
High Quality Content by WIKIPEDIA articles! The forward algorithm, in the context of a hidden Markov model, is used to calculate a 'belief state': the probability of a state at a certain time, given the history of evidence. The process is also known as filtering. The forward algorithm is closely related to, but distinct from, the Viterbi algorithm.In order to take into account future history (i.e., if one wanted to improve the estimate for past times), you can run the Backward algorithm, a complement of the Forward. This is called smoothing. Mathematically, it would be said that the forward/backward algorithm computes P(xk | y1:t) for 0 < k < t. So the use of the full F/B algorithm takes into account all evidence.