Semi-supervised Affinity Propagation Based on Density Peaks
نویسندگان
چکیده
Original scientific paper In view of the unsatisfying clustering effect of affinity propagation (AP) clustering algorithm when dealing with data sets of complex structures, a semi-supervised affinity propagation clustering algorithm based on density peaks (SAP-DP) was proposed in this paper. The algorithm uses a new algorithm of density peaks (DP) which has the advantage of the manifold clustering with the idea of semi-supervised, builds pairwise constraints to adjust the similarity matrix, and then executes the AP clustering. The results of the simulation experiments validated that the proposed algorithm has better clustering performance compared with conventional AP.
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