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Determining the Number and the Locations of RBF Centers Using Enhanced K-Medoids Clustering and Bi-Section Search Method  

Lee, Daewon (Department of Industrial Engineering, Pohang University of Science and Technology)
Lee, Jaewook (Department of Industrial Engineering, Pohang University of Science and Technology)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.29, no.2, 2003 , pp. 172-178 More about this Journal
Abstract
In the recent researches, a variety of ways for determining the locations of RBF centers have been proposed assuming that the number of RBF centers is known. But they have also many numerical drawbacks. We propose a new method to overcome such drawbacks. The strength of our method is to determine the locations and the number of RBF centers at the same time without any assumption about the number of RBF centers. The proposed method consists of two phases. The first phase is to determine the number and the locations of RBF centers using bi-section search method and enhanced k-medoids clustering which overcomes drawbacks of clustering algorithm. In the second phase, network weights are computed and the design of RBF network is completed. This new method is applied to several benchmark data sets. Benchmark results show that the proposed method is competitive with the previously reported approaches for center selection.
Keywords
generalized RBF network; center selection; data partition; bi-section; k-medoids clustering;
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