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i'm new to the HMM universe. I've followed the tutorials using a GaussianHMM machine learner, and they work but i was just wondering how i can use the code to display the probability of an observation given the most likely sequence, assuming i have multiple sequences of observations? Thanks

so for example, if the observations are: seq1:[1,2,-1,4,2], seq2:[a,v,s,a,f], and the model has 2 states, once the model predicts the states, how does one calculate the probability of an observed output [1],[a] ?

kw t
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  • Are you interested in the formula or in the code using `hmmlearn`? – Sergei Lebedev Feb 12 '17 at 18:19
  • "the probability of an observation given the most likely sequence" - This doesn't make sense to me within the HMM framework. Either you want the most likely sequence of states using the Viterbi algorithm, or you want the likelihood of an observation sequence given the MODEL. The likelihood can be computed using a forward algorithm. – Eskapp Feb 21 '17 at 21:03

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