title: Gaussian hidden markov model
body: <p>I am following a tutorial from this link <a href="http://www.blackarbs.com/blog/introduction-hidden-markov-models-python-networkx-sklearn/2/9/2017" rel="nofollow noreferrer">http://www.blackarbs.com/blog/introduction-hidden-markov-models-python-networkx-sklearn/2/9/2017</a> in order to implement hidden markov model in my example. I have 2 hidden states and 2 observed states .</p>
  
  <p>As I understand  from the code in the tutorial first step in HMM is to estimate parameters of the model using maximum likelihood estimation model and then from the results of the parameters we can predict hidden states.<br>
  So  Vitebri algorithm is used in order to train the model to find the optimal parameters and then predict the observed states.<br>
  Is it the case? I can share my code if it is more explicable.</p>