RSVM: Reduced Support Vector Machines

Abstract

Abstract An algorithm is proposed which generates a nonlinear kernel-based separating surface that requires as little as 1 % of a large dataset for its explicit evaluation. To generate this nonlinear surface, the entire dataset is used as a constraint in an optimization problem with very few variables corresponding to the 1

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