Le Thi Hoai An, T. Belghiti, Pham Dinh Tao: "A new efficient algorithm based on DC programming and DCA for Clustering".

Abstract: In this paper, a version of K-median problem, one of the most popular and best studied clustering measures, is discussed. The model using squared Euclidean distances terms to which the K-means algorithm has been successfully applied is considered. A fast and robust algorithm based on DC (Difference of Convex functions) programming and DC Algorithms (DCA) is investigated. Preliminary numerical solutions on real-world databases show the efficiency and the superiority of the appropriate DCA with respect to the standard K-means algorithm.

 

Keywords: Clustering, K-median problem, K-means algorithm, DC programming, DCA, Nonsmooth nonconvex programming.

 

Citation: Le Thi Hoai An, T. Belghiti and Pham Dinh Tao, A new efficient algorithm based on DC programming and DCA for Clustering, Journal of Global Optimization 37: 593-608, 2007.

 

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