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Radial basis function kernel optimization for Support Vector Machine classifiers

Published in arXiv (Cornell University) • Jul 16, 2020
Authors:
Karl Thurnhofer‐Hemsi
,
Ezequiel López‐Rubio
,
Miguel A. Molina‐Cabello

Abstract

Support Vector Machines (SVMs) are still one of the most popular and precise classifiers. The Radial Basis Function (RBF) kernel has been used in SVMs to separate among classes with considerable success. However, there is an intrinsic dependence on the initial value of the kernel hyperparameter. In ...

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