DocumentCode :
1864275
Title :
Fuzzy c-means for data with tolerance by introducing penalty term
Author :
Kanzawa, Yuchi ; Endo, Yasunori ; Miyamoto, Sadaaki
Author_Institution :
Fac. of Eng., Shibaura Inst. of Technol., Tokyo
fYear :
2008
fDate :
25-27 June 2008
Firstpage :
371
Lastpage :
376
Abstract :
In this paper, two new clustering algorithms are proposed for data with some errors. In any of these algorithms, the error is interpreted as one of decision variables - called ldquotolerancerdquo - of a certain optimization problem like the previously proposed algorithm, but the tolerance in new methods is determined by the new introduced penalty term of it in the corresponding objective function. Through some numerical experiments, the difference between our methods and the previously proposed one is discussed.
Keywords :
fuzzy set theory; optimisation; pattern clustering; clustering algorithms; fuzzy c-means; optimization problem; penalty term; Clustering algorithms; Computer applications; Computer industry; Constraint optimization; Data engineering; Entropy; Humans; Optimization methods; Partitioning algorithms; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Soft Computing in Industrial Applications, 2008. SMCia '08. IEEE Conference on
Conference_Location :
Muroran
Print_ISBN :
978-1-4244-3782-5
Electronic_ISBN :
978-4-9904-2590-6
Type :
conf
DOI :
10.1109/SMCIA.2008.5045992
Filename :
5045992
Link To Document :
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