Machine Learning, Clustering, Python, Gaussian Mixture Model, Unsupervised Learning.
KMeans(n_clusters=3, random_state=42) kmeans_labels = kmeans.fit_predict(X) # boundaries of the cluster spheres radii = [np.max(np.linalg.norm(X[kmeans_labels == i, :] - kmeans.cluster_centers_[i, :], axis=1)) for i in range(3)] # plot fig, ax = plt.subplots(ncols=2, figsize=(10, 4))