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Global learning of decision trees by an evolutionary algorithm

  • Marek Krętowski
  • Marek Grześ

Abstract

In the paper, an evolutionary algorithm for global induction of decision trees is presented. In contrast to greedy, top-down approaches it searches for the whole tree at the moment. Specialised genetic operators are proposed which allow modifying both tests used in the non-terminal nodes and structure of the tree. The proposed approach was validated on both artificial and real-life datasets. Experimental results show that the proposed algorithm is able to find competitive classifiers in terms of accuracy and especially complexity.

Keywords

Data mining decision trees evolutionary algorithms global induction 

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Copyright information

© Springer Science+Business Media, Inc. 2005

Authors and Affiliations

  • Marek Krętowski
    • 1
  • Marek Grześ
    • 1
  1. 1.Faculty of Computer ScienceBiałystok Technical UniversityBiałystokPoland

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