Scikit-learn’s AffinityPropagation class clusters data using similarity measures like negative squared Euclidean distances or a custom precomputed matrix. Key parameters include preference to control cluster count, damping for convergence stability, and max_iter for iteration limits, enabling tailored clustering workflows.