DocumentCode
3182749
Title
Least squares support vector machines based on fuzzy rough set
Author
Zhang, Zhi-wei ; Chen, De-gang ; He, Qiang ; Wang, Hui
Author_Institution
Dept. of Math. & Phys., North China Electr. Power Univ., Beijing, China
fYear
2010
fDate
10-13 Oct. 2010
Firstpage
3834
Lastpage
3838
Abstract
In this paper, a new approach to improve least squares support vector machines is presented. We consider the membership of every sample in constraints, that is to say, every sample are not fully assigned to one class. The membership is computed by employing the technique of fuzzy rough sets, and then a new least squares support vector machine algorithm based on fuzzy rough sets is proposed, experiments are carried out to show that our idea in this paper is feasible and valid.
Keywords
fuzzy set theory; least squares approximations; rough set theory; support vector machines; fuzzy rough set; least squares support vector machines; Ionosphere; Kernel; Sonar; Testing; Fuzzy Membership; Fuzzy Rough Sets; Fuzzy Transitive Kernels; Least Squares Support Vector Machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on
Conference_Location
Istanbul
ISSN
1062-922X
Print_ISBN
978-1-4244-6586-6
Type
conf
DOI
10.1109/ICSMC.2010.5642029
Filename
5642029
Link To Document