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Least Squares Support Vector Machine Classifiers
Authors:JAK Suykens  J Vandewalle
Institution:(1) Department of Electrical Engineering, Katholieke Universiteit Leuven, ESAT-SISTA Kardinaal Mercierlaan 94, B–3001 Leuven (Heverlee), Belgium, e-mail
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.
Keywords:classification  support vector machines  linear least squares  radial basis function kernel
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