Closed-Form Gaussian Spread Estimation for Small and Large Support Vector Classification
Diego Isla-Cernadas,
Manuel Fernández-Delgado,
Eva Cernadas
et al.
Abstract:The support vector machine (SVM) with Gaussian kernel often achieves state-of-the-art performance in classification problems, but requires the tuning of the kernel spread. Most optimization methods for spread tuning require training, being slow and not suited for large-scale datasets. We formulate an analytic expression to calculate, directly from data without iterative search, the spread minimizing the difference between Gaussian and ideal kernel matrices. The proposed direct gamma tuning (DGT) equals the per… Show more
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