'Compute the posterior probability for each state in the model.
X : array-like, shape (n_samples, n_features)
Feature matrix of individual samples.
lengths : array-like of integers, shape (n_sequences, ), optional
Lengths of the individual sequences in ``X``. The sum of
these should be ``n_samples``.
Returns
posteriors : array, shape (n_samples, n_components)
State-membership probabilities for each sample from ``X``.'

def predict_proba(self, X, lengths=None):

    (_, posteriors) = self.score_samples(X, lengths)
    return posteriors
