A Rough Margin Based Fuzzy Support Vector Machine
2011 ◽
Vol 204-210
◽
pp. 879-882
Keyword(s):
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.
2013 ◽
Vol 756-759
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pp. 3399-3403
2021 ◽
2013 ◽
Vol 475-476
◽
pp. 312-317
2008 ◽
pp. 1277-1282
2011 ◽
Vol 230-232
◽
pp. 625-628
2013 ◽
Vol 2013
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pp. 1-10
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2014 ◽
Vol 1061-1062
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pp. 935-938
2001 ◽
Vol 09
(06)
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pp. 803-813
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