Machine Learning, Clustering, Affinity Propagation, Python, Unsupervised Learning.
213, 271, 288])) """ With the default configuration, we obtained 14 different clusters. plt.figure(figsize=(10, 6)) colors = ['r', 'g', 'b', 'c', 'm', 'y', 'k','r', 'g', 'b', 'c', 'm', 'y', 'k'] for k, col in zip(range(len(cluster_centers_indices)), colors): class_members = labels == k