How to use the hmmlearn.hmm.GaussianHMM.__init__ function in hmmlearn

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github CostaLab / reg-gen / rgt / HINT / hmm.py View on Github external
def __init__(self, n_components=1, covariance_type='diag', min_covar=1e-3, startprob_prior=1.0,
                 transmat_prior=1.0, means_prior=0, means_weight=0, covars_prior=1e-2, covars_weight=1,
                 algorithm="viterbi", random_state=None, n_iter=5, tol=1e-2, verbose=False,
                 params="stmc", init_params="stmc", states_prior=None, fp_state=None):
        GaussianHMM.__init__(self, n_components=n_components, covariance_type=covariance_type,
                             min_covar=min_covar, startprob_prior=startprob_prior, transmat_prior=transmat_prior,
                             means_prior=means_prior, means_weight=means_weight,
                             covars_prior=covars_prior, covars_weight=covars_weight,
                             algorithm=algorithm, random_state=random_state,
                             n_iter=n_iter, tol=tol, verbose=verbose,
                             params=params, init_params=init_params)

        self.covariance_type = covariance_type
        self.min_covar = min_covar
        self.means_prior = means_prior
        self.means_weight = means_weight
        self.covars_prior = covars_prior
        self.covars_weight = covars_weight
        self.states_prior = states_prior
        self.fp_state = fp_state