On Tolerant Fuzzy c -Means Clustering
Yukihiro Hamasuna*, Yasunori Endo**, and Sadaaki Miyamoto**
*Doctoral Program in Risk Engineering, University of Tsukuba
** Department of Risk Engineering, Faculty of Systems and Information Engineering, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan
-  J. C. Bezdek, “Pattern Recognition with Fuzzy Objective Function Algorithms,” Plenum Press, New York, 1981.
-  S. Miyamoto and M. Mukaidono, “Fuzzy c -means as a regularization and maximum entropy approach,” Proc. of the 7th Int. Fuzzy Systems Association World Congress (IFSA'97), June 25-30, 1997, Prague, Czech, Vol.2, pp. 86-92, 1997.
-  W. K. Ngai, B. Kao, C. K. Chui, R. Cheng, M. Chau, and K. Y. Yip, “Efficient Clustering of Uncertain Data,” Proc. of the Sixth Int. Conf. on Data Mining (ICDM'06), December 18-22, 2006, Hong Kong, China, pp. 436-445, 2006.
-  O. Takata and S. Miyamoto, “Fuzzy Clustering of Data with Interval Uncertainties,” Journal of Japan Society for Fuzzy Theory and Systems, Vol.12, No.5, pp. 686-695, 2000 (in Japanese).
-  Y. Endo, R. Murata, H. Haruyama, and S. Miyamoto, “Fuzzy c -Means for Data with Tolerance,” Proc. of Int. Symposium on Nonlinear Theory and Its Applications, pp. 345-348, 2005.
-  R. Murata, Y. Endo, H. Haruyama, and S. Miyamoto, “On Fuzzy c -Means for data with Tolerance,” Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.10, No.5, pp. 673-681, 2006.
-  Y. Hasegawa, Y. Endo, Y. Hamasuna, and S. Miyamoto, “Fuzzy c -Means for Data with Tolerance Defined as Hyper-rectangles,” Modeling Decisions for Artificial Intelligence (MDAI2007), pp. 237-248. Springer, Heidelberg 2007.
-  Y. Hamasuna, Y. Endo, S. Miyamoto, and Y. Hasegawa, “On Hard Clustering for Data with Tolerance,” Journal of Japan Society for Fuzzy Theory and Intelligent Informatics, Vol.20, No.3, pp. 388-398, 2008 (in Japanese).
-  Y. Endo, Y. Hasegawa, Y. Hamasuna, and S. Miyamoto, “Fuzzy c -Means for Data with Rectangular Maximum Tolerance Range,” Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII), Vol.12, No.5, pp. 461-466, 2007.
-  Y. Hamasuna, Y. Endo, and M. Yamashiro, “On Tolerant Entropy Regularized Fuzzy c -Means,” IEEE Int. Conf. on Granular Computing (GrC2008), Aug 26-28, 2008, Hangzhou, China, pp. 244-247, 2008.
-  Y. Hamasuna, Y. Endo, and S. Miyamoto, “On Tolerant Fuzzy c -Means,” Joint 4th Int. Conf. on Soft Computing and Intelligent Systems and 9th Int. Symposium on advanced Intelligent Systems (SCIS&ISIS2008), Sep 17-21, 2008, Nagoya, Japan, pp. 574-577, 2008.
-  UCI Machine Learning Repository Content Summary
-  S. Miyamoto, H. Ichihashi, and K. Honda, “Algorithms for Fuzzy Clustering,” Springer, Heidelberg, 2008.
-  K. Jajuga, “L1-norm based fuzzy clustering,” Fuzzy Sets and Systems, Vol.39, pp. 43-50, 1991.
-  S. Miyamoto and Y. Agusta, “An Efficient Algorithm for l1 Fuzzy c -Means and Its Termination,” Control and Cybernetics, Vol.24, No.4, pp. 421-436, 1995.
This article is published under a Creative Commons Attribution-NoDerivatives 4.0 Internationa License.