ProbabilisticModel.py 文件源码

def fit(self, data):
        gmm = GMM(n_components=1, covariance_type=self.cv_type)
        gmm.fit(data)
        self.mean = gmm.means_[0]
        if self.cv_type == 'full':
            self.cov = gmm.covars_[0]
        elif self.cv_type == 'tied':
            self.cov = gmm.covars_
        else:
            self.cov = np.diag(gmm.covars_[0])