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Comment on Show HN: Markov chains explained visually

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The one thing to add to this is that usually each state doesn't emit a single token ("I am in state 1" then "I am in state 2") but instead you assume that each state has a range of possible actions and the likelihood of a choice of action varies with state.

So if might not be that your model is sunny versus rainy but instead cold front v warm front. Since rain is more likely during a cold front your observation of rain increases your belief that the system is in the "cold front" state.

That's a Hidden Markov Model.

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