Improving the Quality of Association Rule Mining by Means of Rough Sets

  • Daniel Delic
  • Hans-J. Lenz
  • Mattis Neiling
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 16)


We evaluate the rough set and the association rule method with respect to their performance and the quality of the produced rules. It is shown that despite their different approaches, both methods are based on the same principle and, consequently, must generate identical rules. However, they differ strongly with respect to performance Subsequently an optimized association rule procedure is presented which unifies the advantages of both methods.


Association Rule Minimum Support Association Rule Mining Decision Attribute Rule Derivation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Daniel Delic
    • 1
  • Hans-J. Lenz
    • 1
  • Mattis Neiling
    • 1
  1. 1.Institute of Applied Computer ScienceFree University of BerlinBerlinGermany

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