def __init__(self, n_iter=100): MultinomialHMM.__init__(self, n_components=len(self.states), n_iter=n_iter) self.voca = dict() self.word_freq = defaultdict(int) self.max_num_segs = 0 self.n_training = 0
def __init__(self,
t,
theta,
rho,
algorithm='viterbi',
random_state=None,
n_iter=20, tol=0,
verbose=False):
MultinomialHMM.__init__(self, n_components=len(t)+1,
algorithm=algorithm,
random_state=random_state,
n_iter=n_iter, tol=tol,
verbose=verbose)
self.t = np.append(np.append([0], t), [np.inf])
self.tau = np.diff(self.t)
self.theta = theta
self.rho = rho
def __init__(self,
n_components=1,
startprob_prior=1.0,
transmat_prior=1.0,
algorithm="viterbi",
random_state=None,
n_iter=10,
tol=1e-2,
verbose=False,
params="ste",
init_params="ste"):
MultinomialHMM.__init__(self,
n_components=n_components,
startprob_prior=startprob_prior,
transmat_prior=transmat_prior,
algorithm=algorithm,
random_state=random_state,
n_iter=n_iter,
tol=tol,
verbose=verbose,
params=params,
init_params=init_params)
return
