A Rough Margin Based Fuzzy Support Vector Machine

Abstract:

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By combining fuzzy support vector machine with rough set, we propose a rough margin based fuzzy support vector machine (RFSVM). It inherits the characteristic of the FSVM method and considers position of training samples of the rough margin in order to reduce overfitting due to noises or outliers. The new proposed algorithm finds the optimal separating hyperplane that maximizes the rough margin containing lower margin and upper margin. Meanwhile, the points lied on the lower margin have larger penalty than these in the boundary of the rough margin. Experiments on several benchmark datasets show that the RFSVM algorithm is effective and feasible compared with the existing support vector machines.

Info:

Periodical:

Advanced Materials Research (Volumes 204-210)

Edited by:

Helen Zhang, Gang Shen and David Jin

Pages:

879-882

DOI:

10.4028/www.scientific.net/AMR.204-210.879

Citation:

K. Li and X. X. Lu, "A Rough Margin Based Fuzzy Support Vector Machine", Advanced Materials Research, Vols. 204-210, pp. 879-882, 2011

Online since:

February 2011

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Price:

$35.00

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