Em Algorithm, Statistics, Machine Learning, Clustering Algorithm, Python.
= seed self.log_likelihood_list = [] self.phi_list = [] self.mean_list = [] self.cov_list = [] np.random.seed(self.seed) def initialize(self, X): # The data dimension n_sample, n_dim = X.shape # w self.w = np.zeros((n_sample, self.n_clusters)) ## initialize parameters # phi # assign each cluster