Application of smoothing technique on twin support vector machines

Authors:
M. Arun Kumar;M. Gopal
Affiliations:
Control group, Department of Electrical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, India;Control group, Department of Electrical Engineering, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110 016, India
Venue:
Pattern Recognition Letters
Year:
2008

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Abstract

This paper enhances the recently proposed twin SVM Jayadeva et al. [Jayadeva, Khemchandani, R., Chandra, S., 2007. Twin support vector machines for pattern classification. IEEE Trans. Pattern Anal. Machine Intell. 29 (5), 905-910] using smoothing techniques to smooth twin SVM for binary classification. We attempt to solve the primal quadratic programming problems of twin SVM by converting them into smooth unconstrained minimization problems. The smooth reformulations are solved using the well-known Newton-Armijo algorithm. The effectiveness of the enhanced method is demonstrated by experimental results on available benchmark datasets.