Hidden Markov Model (HMM) Viterbi State Prediction

>>> from mlpack import hmm_viterbi

This utility takes an already-trained HMM, specified as 'input_model', and evaluates the most probable hidden state sequence of a given sequence of observations (specified as ''input', using the Viterbi algorithm. The computed state sequence may be saved using the 'output' output parameter.

For example, to predict the state sequence of the observations 'obs' using the HMM 'hmm', storing the predicted state sequence to 'states', the following command could be used:

>>> hmm_viterbi(input=obs, input_model=hmm)
>>> states = output['output']

input options

output options

The return value from the binding is a dict containing the following elements: