Semi-supervised Affinity Propagation Clustering

Affinity propagation clustering is an efficient and fast clustering algorithm,especially for large data sets,but its clustering quality is low when it is applied to a data set with loose cluster structures.This paper proposes semi-supervised affinity propagation,where cluster validity indices are embedded into iteration process of the algorithm to supervise and guide its running to an optimal clustering solution.The experimental results show that the algorithm gives accurate clustering results for data sets with compact and loose cluster structures.