Machine Learning, Clustering, Expectation Maximization, Gaussian Mixture Model, Image Clustering.
get_log_likelihood(data, weights, means, covariances) l1_list = [l1] for it in range(maxiter): # E-step: calculate responsibilities resp = get_responsibilities(data, weights, means, covariances) # M-step calculate cluster parameter counts = get_soft_counts(resp) weights = _get_weights(counts) means