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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 433-440An New Fuzzy Support Vector Machine for Binary...

An New Fuzzy Support Vector Machine for Binary Classification

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Abstract:

In this paper, we proposed a new fuzzy support vector machine(called L2–FSVM here), which error part of object is L2–norm.Meanwhile we introduce a new method of generating fuzzy memberships so as to reduce to effects of outliers. The experimental results demonstrate that the L2-FSVM method provides improved ability to reduce to effects of outliers in comparison with traditional SVMs and FSVMs, and claim that L2–FSVM is the best way to solve the binary classiﬁcation in the three methods stated above.

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Materials Science and Information Technology

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Periodical:

Advanced Materials Research (Volumes 433-440)

Pages:

2856-2861

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.433-440.2856

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Online since:

January 2012

Authors:

Rui Zhang, Tong Bo Liu, Ming Wen Zheng

Keywords:

FSVM, Kernel Function, Support Vector Machine (SVM)

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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