本文整理汇总了Python中hmmlearn.hmm.GaussianHMM.__init__方法的典型用法代码示例。如果您正苦于以下问题：Python GaussianHMM.__init__方法的具体用法？Python GaussianHMM.__init__怎么用？Python GaussianHMM.__init__使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类hmmlearn.hmm.GaussianHMM的用法示例。
在下文中一共展示了GaussianHMM.__init__方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: __init__
# 需要导入模块: from hmmlearn.hmm import GaussianHMM [as 别名]
# 或者: from hmmlearn.hmm.GaussianHMM import __init__ [as 别名]
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