Kamel, M.S. and Selim, S.Z. NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM. PATTERN RECOGNITION, 27. pp. 421-428.
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Abstract
Two new algorithms for fuzzy clustering are presented. Convergence of the proposed algorithms is proved. An empirical study of their convergence behavior is discussed. The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. Experimental results show that the new algorithms are faster and lead to computational savings.
| Item Type: | Article |
|---|---|
| Subjects: | Computer |
| Divisions: | College Of Computer Sciences and Engineering > Systems Engineering Dept |
| Creators: | Kamel, M.S. and Selim, S.Z. |
| Email: | UNSPECIFIED, selim@kfupm.edu.sa |
| ID Code: | 2559 |
| Deposited By: | SHAIKH ARIFUSALAM |
| Deposited On: | 14 Jun 2008 13:35 |
| Last Modified: | 12 Apr 2011 13:13 |
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