A Hidden Markov Random Field (HMF) is a mathematical model used in statistics to study patterns of events over time.
HMFs use a particular type of probability distribution, called a hiddenMarkov chain, to model the occurrence of individual events.
This type of probability distribution is often used in situations where you want to know how likely it is that an event will happen given that it has already happened, and you don’t care about which event occurs first.
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