Machine Learning, Clustering, Python, Gaussian Mixture Model, Unsupervised Learning.
np.random.normal([0, 3], [0.3, 1], (n_samples, 2)), np.random.normal([2, 4], [0.3, 1], (n_samples, 2)), np.random.normal([4, 6], [0.4, 1], (n_samples, 2)) )) return X X = generate_elliptic() # k-means clustering kmeans = KMeans(n_clusters=3, random_state=0).fit(X) kmeans_labels = kmeans.labels_ #