Least Squares Support Vector Machine Classifiers |
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| Authors: | Suykens JAK Vandewalle J |
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| Affiliation: | (1) Department of Electrical Engineering, Katholieke Universiteit Leuven, ESAT-SISTA Kardinaal Mercierlaan 94, B–3001 Leuven (Heverlee), Belgium, e-mail |
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| Abstract: | In this letter we discuss a least squares version for support vector machine (SVM) classifiers. Due to equality type constraints in the formulation, the solution follows from solving a set of linear equations, instead of quadratic programming for classical SVM's. The approach is illustrated on a two-spiral benchmark classification problem. |
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| Keywords: | classification support vector machines linear least squares radial basis function kernel |
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