Skip to main content
SpringerLink
Log in

Attribute Ranking Driven Filtering of Decision Rules

  • Conference paper
Rough Sets and Intelligent Systems Paradigms

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8537))

Abstract

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.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  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. 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. Fiesler, E., Beale, R.: Handbook of neural computation. Oxford University Press (1997)

    Google Scholar 

  4. Greco, S., Matarazzo, B., Słowiński, R.: Rough set theory for multicriteria decision analysis. European Journal of Operational Research 129(1), 1–47 (2001)

    Article  MathSciNet  Google Scholar 

  5. Jensen, R., Shen, Q.: Computational Intelligence and Feature Selection. John Wiley & Sons, Inc., Hoboken (2008)

    Book  Google Scholar 

  6. Pawlak, Z.: Rough sets and intelligent data analysis. Information Sciences 147, 1–12 (2002)

    Article  MathSciNet  Google Scholar 

  7. Peng, R., Hengartner, H.: Quantitative analysis of literary styles. The American Statistician 56(3), 15–38 (2002)

    Article  MathSciNet  Google Scholar 

  8. Sikora, M.: Redefinition of classification rules by evaluation of elementary conditions occurring in the rule premises. Fundamenta Informaticae 123(2), 171–197 (2013)

    MathSciNet  MATH  Google Scholar 

  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)

    Chapter  Google Scholar 

  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)

    Chapter  Google Scholar 

  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)

    Chapter  Google Scholar 

  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)

    Chapter  Google Scholar 

  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. 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)

    Chapter  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Akademicka 16, 44-100, Gliwice, Poland

    Urszula Stańczyk

Authors
  1. Urszula Stańczyk
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665, Warsaw, Poland

    Marzena Kryszkiewicz  & Zbigniew W. Raś  & 

  2. Department of Computer Science and Artificial Intelligence, University of Granada, Calle del Periodista Daniel Saucedo Aranda s/n, 18071, Granada, Spain

    Chris Cornelis

  3. DISCo, Università di Milano – Bicocca, Viale Sarca 336 – U14, 20126, Milano, Italy

    Davide Ciucci

  4. Dpt. de Matemáticas, University of Càdiz, Spain

    Jesús Medina-Moreno

  5. School of Computing and Information Systems, University of Tasmania, Japan

    Hiroshi Motoda

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Stańczyk, U. (2014). Attribute Ranking Driven Filtering of Decision Rules. In: Kryszkiewicz, M., Cornelis, C., Ciucci, D., Medina-Moreno, J., Motoda, H., Raś, Z.W. (eds) Rough Sets and Intelligent Systems Paradigms. Lecture Notes in Computer Science(), vol 8537. Springer, Cham. https://doi.org/10.1007/978-3-319-08729-0_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-08729-0_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-08728-3

  • Online ISBN: 978-3-319-08729-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation