Ensemble Learning with Evolutionary Computation: Application to Feature Ranking

  • Kees Jong
  • Elena Marchiori
  • Michèle Sebag
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3242)

Abstract

Exploiting the diversity of hypotheses produced by evolutionary learning, a new ensemble approach for Feature Selection is presented, aggregating the feature rankings extracted from the hypotheses. A statistical model is devised to enable the direct evaluation of the approach; comparative experimental results show its good behavior on non-linear concepts when the features outnumber the examples.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Kees Jong
    • 1
  • Elena Marchiori
    • 1
  • Michèle Sebag
    • 2
  1. 1.Department of Mathematics and Computer ScienceVrije UniversiteitAmsterdamThe Netherlands
  2. 2.Laboratoire de Recherche en Informatique, CNRS-INRIAUniversité Paris-Sud OrsayFrance

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