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The hmmlearn tutorial demonstrates how a Hidden Markov Model can be fitted to a dataset:

model = hmm.GaussianHMM(n_components=3, covariance_type="full", n_iter=100)
model.fit(X)

Is there a built-in way to do cross validation, Or do I have to do it by hand?

smci
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Oblomov
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  • interesting, I assumed I could plug that model into sklearn's cross_val_score but apparently not – Max Power Jun 21 '17 at 06:12
  • I was hoping too, that the hmmlearn model would integrate into the sklearn environment like that... – Oblomov Jun 21 '17 at 09:17
  • You mean 'built-in' in `hmmlearn` package, not `sklearn`? Or are you asking why `sklearn`'s cross-validation methods don't work with hmmlearn? (what happens if you try them? show your code and/or errors please. cc: @MaxPower) OP please clarify your question, it's too broad/unclear. – smci Aug 13 '19 at 05:54

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