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Feature Selection Using Tabu Search with Learning Memory: Learning Tabu Search

  • Lucien MousinEmail author
  • Laetitia Jourdan
  • Marie-Eléonore Kessaci Marmion
  • Clarisse Dhaenens
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10079)

Abstract

Feature selection in classification can be modeled as a combinatorial optimization problem. One of the main particularities of this problem is the large amount of time that may be needed to evaluate the quality of a subset of features. In this paper, we propose to solve this problem with a tabu search algorithm integrating a learning mechanism. To do so, we adapt to the feature selection problem, a learning tabu search algorithm originally designed for a railway network problem in which the evaluation of a solution is time-consuming. Experiments are conducted and show the benefit of using a learning mechanism to solve hard instances of the literature.

Keywords

Feature Selection Local Search Tabu Search Combinatorial Optimization Problem Learning Mechanism 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Lucien Mousin
    • 1
    Email author
  • Laetitia Jourdan
    • 1
  • Marie-Eléonore Kessaci Marmion
    • 1
  • Clarisse Dhaenens
    • 1
  1. 1.Univ. Lille, CNRS, Centrale Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de LilleLilleFrance

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