Hidden Markov Models

**Definition:** Finite learnable stochastic models often used in MACHINE LEARNING consisting of two processes: a MARKOV CHAIN and an event observed and analyzed in a state unknown or hidden to the observer. Hidden Markov Models are often used in BIOINFORMATICS, time series analysis and speech and handwriting recognition.

**Tree numbers:** - E05.318.740.600.500.300 - E05.318.740.996.500.250 - G17.830.500.250 - N05.715.360.750.625.500.300 - N05.715.360.750.770.500.250 - N06.850.520.830.600.500.300 - N06.850.520.830.996.500.250