JACIII Vol.10 No.5 pp. 673-681
doi: 10.20965/jaciii.2006.p0673


On Fuzzy c-Means for Data with Tolerance

Ryuichi Murata, Yasunori Endo, Hideyuki Haruyama, and Sadaaki Miyamoto

University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8573, Japan

January 1, 2006
April 15, 2006
September 20, 2006
fuzzy c-means, tolerance, optimization problem
This paper presents two new clustering algorithms which are based on the entropy regularized fuzzy c-means and can treat data with some errors. First, the tolerance is formulated and introduce into optimization problems of clustering. Next, the problems are solved using Kuhn-Tucker conditions. Last, the algorithms are constructed based on the results of solving the problems.
Cite this article as:
R. Murata, Y. Endo, H. Haruyama, and S. Miyamoto, “On Fuzzy c-Means for Data with Tolerance,” J. Adv. Comput. Intell. Intell. Inform., Vol.10 No.5, pp. 673-681, 2006.
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