Machine Learning, Clustering, Expectation Maximization, Gaussian Mixture Model, Image Clustering.
get_responsibilities(self, data, weights, means, covariances): n_data = len(data) n_clusters = len(means) resp = np.zeros((n_data, n_clusters)) for i in range(n_data): for k in range(n_clusters): resp[i, k] = weights[k]* multivariate_normal.pdf(data[i],means[k],covariances[k]) # Add up