hmm_model

pip install hidden_markov

import numpy as np
from hidden_markov import hmm

ob_types = ('W', 'N')  # Working and Not Working
states = ('L', 'M')    # Legitimate and Malicious

observations = ('W', 'W', 'W', 'N')

start = np.matrix('0.1 0.9')  # Initial state probabilities
transition = np.matrix('0.7 0.3; 0.1 0.9')  # Transition probabilities
emission = np.matrix('0.2 0.8; 0.4 0.6')    # Emission probabilities

_hmm = hmm(states, ob_types, start, transition, emission)

print("Forward algorithm:")
print(_hmm.forward_algo(observations))

print("Viterbi algorithm:")
print(_hmm.viterbi(observations))