• DocumentCode
    3597344
  • Title

    A Review on Evolutionary Feature Selection

  • Author

    Abd-Alsabour, Nadia

  • Author_Institution
    Cairo Univ., Cairo, Egypt
  • fYear
    2014
  • Firstpage
    20
  • Lastpage
    26
  • Abstract
    This paper presents a review of some of the most recent evolutionary algorithms used for solving feature selection based upon previously published research on feature selection. In addition, we discuss various research issues relating to each of the presented evolutionary algorithm. Evolutionary algorithms present several advantages over traditional search such as they require less domain-specific information. Such advantages have made them very popular within feature selection as explained in this paper. This paper covers the first part only of the evolutionary algorithms for the feature selection problem due to the limitation of the number of pages. The references cited in this paper cover the major theoretical issues, and provide access to the main branches of the literature dealing with such methods.
  • Keywords
    ant colony optimisation; computational complexity; feature selection; genetic algorithms; particle swarm optimisation; search problems; NP hard optimization problem; ant colony optimization; evolutionary algorithms; evolutionary feature selection; genetic algorithms; page number limitation; particle swarm optimization; Classification algorithms; Evolutionary computation; Feature extraction; Genetic algorithms; Optimization; Sociology; Statistics; Ant Colony Optimization (ACO); Feature Selection (FS); Genetic Algorithms (GAs); Particle Swarm Optimization (PSO);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Modelling Symposium (EMS), 2014 European
  • Print_ISBN
    978-1-4799-7411-5
  • Type

    conf

  • DOI
    10.1109/EMS.2014.28
  • Filename
    7153969