A New Filled Function method for Smooth Clustering
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| Title | A New Filled Function method for Smooth Clustering |
| Authors | |
| Abstract | The mathematical modeling of the clustering centers problem leads to a min-sum-min formulation which, has the significant characteristic of being strongly nondifferentiable. To overcome this difficulty, a new filled function method is proposed to find centers of clusters based on entropy technique. A completely differentiable non-convex optimization model for the clustering center problem is constructed. A parameter free filled function method is adopted to search for a global optimal solution of the optimization model. For the purpose of illustrating both the reliability and the efficiency of the method, a set of computational experiments was performed. Numerical results illustrate that the proposed algorithm can effectively hunt centers of clusters and especially improve the accuracy of the clustering even with a relatively small entropy factor. |
| Publisher | ACADEMY PUBLISHER |
| Date | 2012-02-01 |
| Source | Journal of Computers Vol 7, No 2 (2012) |
| Rights | Copyright © ACADEMY PUBLISHER - All Rights Reserved.To request permission, please check out URL: http://www.academypublisher.com/copyrightpermission.html. |