A Fuzzy-GA Wrapper-Based Constructive Induction Model

  • Zohreh HajAbedi
  • Mohammad Reza Kangavari
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5755)

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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