A Fuzzy-GA Wrapper-Based Constructive Induction Model

  • Zohreh HajAbedi
  • Mohammad Reza Kangavari
Conference paper

DOI: 10.1007/978-3-642-04020-7_47

Part of the Lecture Notes in Computer Science book series (LNCS, volume 5755)
Cite this paper as:
HajAbedi Z., Kangavari M.R. (2009) A Fuzzy-GA Wrapper-Based Constructive Induction Model. In: Huang DS., Jo KH., Lee HH., Kang HJ., Bevilacqua V. (eds) Emerging Intelligent Computing Technology and Applications. With Aspects of Artificial Intelligence. ICIC 2009. Lecture Notes in Computer Science, vol 5755. Springer, Berlin, Heidelberg

Abstract

Constructive Induction is a preprocessing step applied to representation space prior to machine learning algorithms and transforms the original representation with complex interaction into a representation that highlights regularities and is easy to be learned. In this paper a Fuzzy-GA wrapper-based constructive induction system is represented. In this model an understandable real-coded GA is employed to construct new features and a fuzzy system is designed to evaluate new constructed features and select more relevant features. This model is applied on a PNN classifier as a learning algorithm and results show that integrating PNN classifier with Fuzzy-GA wrapper-based constructive induction module will improve the effectiveness of the classifier.

Keywords

Constructive induction Feature construction Feature selection Fuzzy GA 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Zohreh HajAbedi
    • 1
  • Mohammad Reza Kangavari
    • 2
  1. 1.Science and Research branchIslamic Azad UniversityTehranIran
  2. 2.Department of ComputerIran University of Scince and TechnologyTehranIran

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