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Least Squares Support Vector Machine Classifiers

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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Suykens, J., Vandewalle, J. Least Squares Support Vector Machine Classifiers. Neural Processing Letters 9, 293–300 (1999). https://doi.org/10.1023/A:1018628609742

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  • classification
  • support vector machines
  • linear least squares
  • radial basis function kernel