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Hello, I have three questions on the use of the mchmm.
I have previously used the hmmlearn library, and I was wondering if it is possible to
a) set a starting set of initial probabilities for the transition matrix states. For example
start_probs = np.array([0.5, 0.5])
b) Use a different type of hmm (Poisson vs MixtureModel for example)
In hmmlearn you can set a model type (e.g. hmm.MultinomialHMM hmm.Poisson) is it possible to define different model types?
c) Output the probabilities for each predicted state.
In hmm learn you can output the probabilities of the predictions from the Viterbi function. Is there a method to perform this task in mchmm?
Thanks Jonathan
The text was updated successfully, but these errors were encountered:
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Hello, I have three questions on the use of the mchmm.
I have previously used the hmmlearn library, and I was wondering if it is possible to
a) set a starting set of initial probabilities for the transition matrix states. For example
b) Use a different type of hmm (Poisson vs MixtureModel for example)
In hmmlearn you can set a model type (e.g. hmm.MultinomialHMM hmm.Poisson) is it possible to define different model types?
c) Output the probabilities for each predicted state.
In hmm learn you can output the probabilities of the predictions from the Viterbi function. Is there a method to perform this task in mchmm?
Thanks
Jonathan
The text was updated successfully, but these errors were encountered: