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Decision Rule Classifiers for Multi-label Decision Tables

  • Fawaz Alsolami
  • Mohammad Azad
  • Igor Chikalov
  • Mikhail Moshkov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8537)

Abstract

Recently, multi-label classification problem has received significant attention in the research community. This paper is devoted to study the effect of the considered rule heuristic parameters on the generalization error. The results of experiments for decision tables from UCI Machine Learning Repository and KEEL Repository show that rule heuristics taking into account both coverage and uncertainty perform better than the strategies taking into account a single criterion.

Keywords

decision rules rule heuristics classification 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fawaz Alsolami
    • 1
    • 2
  • Mohammad Azad
    • 1
  • Igor Chikalov
    • 1
  • Mikhail Moshkov
    • 1
  1. 1.Computer, Electrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwalSaudi Arabia
  2. 2.Computer Science DepartmentKing Abdulaziz UniversitySaudi Arabia

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