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Least squares support vector machines based on fuzzy rough set

Biomedical Sciences Research Institute Computer Science Research Institute Environmental Sciences Research Institute Nanotechnology & Advanced Materials Research Institute

Zhang, Zhiwei, Chen, Degang, He, Qiang and Wang, Hui (2010) Least squares support vector machines based on fuzzy rough set. In: IEEE International Conference on Systems, Man and Cybernetics, Istanbul. IEEE. 3834 pp. [Conference contribution]

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DOI: 10.1109/ICSMC.2010.5642029

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.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:17370
Deposited By:Professor Hui Wang
Deposited On:30 Mar 2011 16:27
Last Modified:30 Mar 2011 16:27

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