Attribute Ranking Driven Filtering of Decision Rules

  • Urszula Stańczyk
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8537)


In decision rule induction approaches either minimal, complete, or satisfying sets of constituent rules are inferred, with an aim of providing predictive properties while offering descriptive capabilities for the learned concepts. Instead of limiting rules at their induction phase we can also execute post-processing of the set of generated decision rules (whether it is complete or not) by filtering out those that meet some constraints. The paper presents the research on rule filtering while following a ranking of conditional attributes, obtained in the process of sequential forward selection of input features for ANN classifiers.


Decision Algorithm Decision Rule DRSA Feature Selection Ranking Rule Filtering ANN Stylometry Authorship Attribution 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Bayardo Jr., R., Agrawal, R.: Mining the most interesting rules. In: Proceedings of the 5th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 145–154 (1999)Google Scholar
  2. 2.
    Craig, H.: Stylistic analysis and authorship studies. In: Schreibman, S., Siemens, R., Unsworth, J. (eds.) A Companion to Digital Humanities. Blackwell, Oxford (2004)Google Scholar
  3. 3.
    Fiesler, E., Beale, R.: Handbook of neural computation. Oxford University Press (1997)Google Scholar
  4. 4.
    Greco, S., Matarazzo, B., Słowiński, R.: Rough set theory for multicriteria decision analysis. European Journal of Operational Research 129(1), 1–47 (2001)MathSciNetCrossRefGoogle Scholar
  5. 5.
    Jensen, R., Shen, Q.: Computational Intelligence and Feature Selection. John Wiley & Sons, Inc., Hoboken (2008)CrossRefGoogle Scholar
  6. 6.
    Pawlak, Z.: Rough sets and intelligent data analysis. Information Sciences 147, 1–12 (2002)MathSciNetCrossRefGoogle Scholar
  7. 7.
    Peng, R., Hengartner, H.: Quantitative analysis of literary styles. The American Statistician 56(3), 15–38 (2002)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Sikora, M.: Redefinition of classification rules by evaluation of elementary conditions occurring in the rule premises. Fundamenta Informaticae 123(2), 171–197 (2013)MathSciNetzbMATHGoogle Scholar
  9. 9.
    Sikora, M., Wróbel, Ł.: Data-driven adaptive selection of rules quality measures for improving the rules induction algorithm. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds.) RSFDGrC 2011. LNCS (LNAI), vol. 6743, pp. 278–285. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  10. 10.
    Słowiński, R., Greco, S., Matarazzo, B.: Dominance-based rough set approach to reasoning about ordinal data. In: Kryszkiewicz, M., Peters, J.F., Rybiński, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 5–11. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  11. 11.
    Stańczyk, U.: DRSA decision algorithm analysis in stylometric processing of literary texts. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds.) RSCTC 2010. LNCS (LNAI), vol. 6086, pp. 600–609. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  12. 12.
    Stańczyk, U.: Rule-based approach to computational stylistics. In: Bouvry, P., Kłopotek, M.A., Leprévost, F., Marciniak, M., Mykowiecka, A., Rybiński, H. (eds.) SIIS 2011. LNCS (LNAI), vol. 7053, pp. 168–179. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  13. 13.
    Stańczyk, U.: Decision rule length as a basis for evaluation of attribute relevance. Journal of Intelligent and Fuzzy Systems 24(3), 429–445 (2013)Google Scholar
  14. 14.
    Stańczyk, U.: Establishing relevance of characteristic features for authorship attribution with ANN. In: Decker, H., Lhotská, L., Link, S., Basl, J., Tjoa, A.M. (eds.) DEXA 2013, Part II. LNCS, vol. 8056, pp. 1–8. Springer, Heidelberg (2013)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Urszula Stańczyk
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

Personalised recommendations