Heru Gunawan, Saib Suwilo, Zakarias Situmorang
Affinity Propagation (AP) is exemplar-based clustering algorithm, this algorithmdoes not require prior knowledge of the number of clusters. The quality of clustering results is highly dependent on the "preference" value. Standard AP algorithm take "preference" value based on median or minimum value of similarity matrix, then the value is shared to all "preference" value on similarity matrix. This method does not give the best solution, because the value not represent the overall data structure. The Modified AP (M-AP) is proposed to resolve this problem. M-AP algorithmtake "preference" value based on data distribution on each row from similarity matrix. Experimental result show that M-AP cat outperform AP in quality clustering result based on Silhouette Index score. © Published under licence by IOP Publishing Ltd.
Departement of Computer Science, Universitas Sumatera Utara, Medan, Indonesia; Department of Mathematics, Universitas Sumatera Utara, Medan, Indonesia; Universitas Katolik Santo Thomas, Medan, Indonesia
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