Journal
INFORMATION SCIENCES
Volume 179, Issue 13, Pages 2208-2217Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ins.2009.02.014
Keywords
Feature selection; Wrapper methods; Classification; Support Vector Machines; Mathematical programming
Categories
Funding
- Millennium Science Institute on Complex Engineering Systems
- Fondecyt [1040926]
- CONICYT
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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. (C) 2009 Elsevier Inc. All rights reserved.
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