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
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
