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Using Wolfe’s Method in Support Vector Machines Learning Stage

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5845))

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Abstract

In this paper, the application of Wolfe’s method in Support Vector Machines learning stage is presented. This stage is usually performed by solving a quadratic programming problem and a common approach for solving it, is breaking down that problem in smaller subproblems easier to solve and manage. In this manner, instead of dividing the problem, the application of Wolfe’s method is proposed. The method transforms a quadratic programming problem into an Equivalent Linear Model and uses a variation of simplex method employed in linear programming. The proposed approach is compared against QuadProg Matlab function used to solve quadratic programming problems. Experimental results show that the proposed approach has better quality of classification compared with that function.

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© 2009 Springer-Verlag Berlin Heidelberg

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Frausto-Solís, J., González-Mendoza, M., López-Díaz, R. (2009). Using Wolfe’s Method in Support Vector Machines Learning Stage. In: Aguirre, A.H., Borja, R.M., Garciá, C.A.R. (eds) MICAI 2009: Advances in Artificial Intelligence. MICAI 2009. Lecture Notes in Computer Science(), vol 5845. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05258-3_43

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  • DOI: https://doi.org/10.1007/978-3-642-05258-3_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05257-6

  • Online ISBN: 978-3-642-05258-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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