Example Hidden Markov Model

hmm.ipynb

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      "[1 0 0 0 0 1]\n"
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   "source": [
    "import numpy as np\n",
    "from hmmlearn import hmm\n",
    "\n",
    "model = hmm.MultinomialHMM(n_components=2)  # create model with two states\n",
    "model.startprob_ = np.array([0.6, 0.4])  # start_probability\n",
    "model.n_features = 3  # observations\n",
    "model.transmat_ = np.array([[0.7, 0.3], [0.4, 0.6]])  # transition_probability\n",
    "model.emissionprob_ = np.array([[0.1, 0.4, 0.5], [0.6, 0.3, 0.1]])  # emission_probability\n",
    "\n",
    "print(model.predict(np.column_stack([[0, 2, 1, 1, 2, 0]])))"
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