title: Determination of global minima of some common validation functions in support vector machine.
abstract: Tuning of the regularization parameter C is a well-known process in the implementation of a support vector machine (SVM) classifier. Such a tuning process uses an appropriate validation function whose value, evaluated over a validation set, has to be optimized for the determination of the optimal C. Unfortunately, most common validation functions are not smooth functions of C. This brief presents a method for obtaining the global optimal solution of these non-smooth validation functions. The method is guaranteed to find the global optimum and relies on the regularization solution path of SVM over a range of C values. When the solution path is available, the computation needed is minimal.
authors.affiliation: Department of Mechanical Engineering, National University of Singapore, 117576, Singapore. yangjianbo@nus.edu.sg
authors.forename: Jian-Bo
authors.initials: JB
authors.lastname: Yang
authors.forename: Chong-Jin
authors.initials: CJ
authors.lastname: Ong
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D010363:Pattern Recognition, Automated; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity