Least Squares Support Vector Machine Classifiers
- Cite this article as:
- Suykens, J. & Vandewalle, J. Neural Processing Letters (1999) 9: 293. doi:10.1023/A:1018628609742
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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.