Mathematical Probability Theory
Hidden Markov Models (HMMs) are statistical models that represent systems which follow a Markov process with hidden states. They are characterized by the assumption that the system being modeled is a Markov process, but the states themselves are not directly observable, making them 'hidden.' HMMs are widely used in various fields such as speech recognition, bioinformatics, and finance to analyze time series data where the underlying state transitions cannot be directly measured.
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