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Action Rule Extraction from a Decision Table: ARED

  • Seunghyun Im
  • Zbigniew W. Raś
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4994)

Abstract

In this paper, we present an algorithm that discovers action rules from a decision table. Action rules describe possible transitions of objects from one state to another with respect to a distinguished attribute. The previous research on action rule discovery required the extraction of classification rules before constructing any action rule. The new proposed algorithm does not require pre-existing classification rules, and it uses a bottom up approach to generate action rules having minimal attribute involvement.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Seunghyun Im
    • 1
  • Zbigniew W. Raś
    • 2
    • 3
  1. 1.Department of Computer ScienceUniversity of Pittsburgh at JohnstownJohnstownUSA
  2. 2.Department of Computer ScienceUniversity of North CarolinaCharlotteUSA
  3. 3.Institute of Computer SciencePolish Academy of SciencesWarsawPoland

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