Heuristic Approaches for Support Vector Machines with the Ramp Loss

Carrizosa, Emilio, Nogales-Gómez, Amaya and Romero-Morales, Dolores (2014) Heuristic Approaches for Support Vector Machines with the Ramp Loss. Optimization Letters, 8 (3). pp. 1125-1135.

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Recently, Support Vector Machines with the ramp loss (RLM) have attracted attention from the computational point of view. In this technical note, we propose two heuristics, the first one based on solving the continuous relaxation of a Mixed Integer Nonlinear formulation of the RLM and the second one based on the training of an SVM classifier on a reduced dataset identified by an integer linear problem. Our computational results illustrate the ability of our heuristics to handle datasets of much larger size than those previously addressed in the literature.

Item Type: Article
Keywords: Support vector machines; ramp loss; mixed integer nonlinear programming; heuristics; management science
Subject(s): Management science
Date Deposited: 26 Feb 2013 16:34
Last Modified: 09 Mar 2017 16:24
URI: http://eureka.sbs.ox.ac.uk/id/eprint/4511

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