[1]LIU San-yang,DU Zhe.An improved fuzzy support vector machine method[J].CAAI Transactions on Intelligent Systems,2007,2(3):30-33.
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An improved fuzzy support vector machine method

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 2 Number of periods: 2007 3 Page number: 30-33 Column: 学术论文—机器学习 Public date: 2007-06-25
Title:
An improved fuzzy support vector machine method
Author(s):
LIU San-yang; DU Zhe
School of Science, Xidian University, Xi’an 710071, China
Keywords:
fuzzy support vector machine;  membership function;  classification
CLC:
TP181
DOI:
-
Abstract:
A design that improves the classifying ability of an SVM by improving the assignment of fuzzy membership is an important step in solving the fuzzy SVM problem. In this paper, a radius controlling factor is introduced to assign sample membership more accurately. This technique can distinguish noise and outliers and increase accuracy of membership in support vectors, compensating for the disadvantages of assigning fuzzy membership based on the distance between a sample and its cluster center proposed by Lin and Wang. Experimental results verify the effectiveness of this method .
References:
［1］ VAPNIK V. The nature of statistical learning theory［M］. New York： Spring er, 1995.
［2］CRISTIANINI N, TAYLOR S J. An introduction to support vector machines ［M ］. Cambridge： Cambridge University Press, 2000.
［3］LIN C F, WANG S D. Fuzzy support vector machines［J］. IEEE Trans Neural Networks, 2002,13(2):464-471.
［4］INOUE T, ABE S.Fuzzy support vector machines for pattern classification［A ］. Proceedings of International Joint Conference on Neural Networks［C］.Washington , D.C.，2001.
［5］HUANG H P,LIU Y H..Fuzzy support vector machines for pattern recognition a nd data mining［J］. International Journal of Fuzzy Systems, 2002,4(3):826-835. 
［6］ZHANG X G. Using class-center vectors to build support vector machines ［A］. Proc IEEE NNSP’99［C］.USA,1999.
［7］安金龙，王正欧，马振平.基于密度法的模糊支持向量机［J］.天津大学学报，2004，37（6）: 544-548．
?AN Jinlong, WANG Zheng’ou， MA Zhenping. Fuzzy support vector machine based o n densi ty［J］. Journal of Tianjin University, 2004, 37(6):544-548.
［8］边肇祺，张学工.模式识别(第2版)［M］.北京:清华大学出版社，2000.
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