A wrapper method for feature selection using Support Vector Machines

Authors:
Sebastián Maldonado;Richard Weber
Affiliations:
Department of Industrial Engineering, University of Chile, P.O. Box 2777, República 701, Santiago de Chile, Chile;Department of Industrial Engineering, University of Chile, P.O. Box 2777, República 701, Santiago de Chile, Chile
Venue:
Information Sciences: an International Journal
Year:
2009

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Abstract

We introduce a novel wrapper Algorithm for Feature Selection, using Support Vector Machines with kernel functions. Our method is based on a sequential backward selection, using the number of errors in a validation subset as the measure to decide which feature to remove in each iteration. We compare our approach with other algorithms like a filter method or Recursive Feature Elimination SVM to demonstrate its effectiveness and efficiency.