Mastering Machine Learning Algorithms

Finding the most likely hidden state sequence with hmmlearn

At this point, we can continue with the previous example, using our model to find the most likely hidden state sequence given a set of possible observations. We can use either the decode() method or the predict() method. The first one returns the log probability of the whole sequence and the sequence itself; however, they all use the Viterbi algorithm as a default decoder:

sequence = np.array([[1], [1], [1], [0], [1], [1], [1], [0], [1],                      [0], [1], [0], [1], [0], [1], [1], [0], [1],                      [1], [0], [1], [0], [1], [0], [1], [0], [1],                      [1], [1], [0], [0], [1], [1], [0], [1], [1]], dtype=np.int32)lp, hs = hmm_model.decode(sequence)print(hs)[0 1 1 0 1 1 1 0 1 0 1 0 1 0 1 1 0 1 1 0 1 0 1 0 ...