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Answer» What is Hidden Markov Model mean? Hidden Markov Model (HMM) is a statistical Markov model in which the system being modeled is assumed to be a Markov process — call it X {\displaystyle X} — with unobservable ("hidden") states. As part of the definition, HMM requires that there be an observable process Y {\displaystyle Y} whose outcomes are "influenced" by the outcomes of X {\displaystyle X} in a known way. Since X {\displaystyle X} cannot be observed directly, the goal is to learn about X {\displaystyle X} by observing Y . {\displaystyle Y.} HMM has an additional requirement that the outcome of Y {\displaystyle Y} at time t = t 0 {\displaystyle t=t_{0}} may be "influenced" exclusively by the outcome of X {\displaystyle X} at t = t 0 {\displaystyle t=t_{0}} and that the outcomes of X {\displaystyle X} and Y reference
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