Skip to main content

Discernibility-Matrix Method Based on the Hybrid of Equivalence and Dominance Relations

  • Conference paper
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing (RSFDGrC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6743))

Abstract

The attribute set of some information systems is composed of both regular attributes and criteria. In order to obtain information reduction of this type of information systems, equivalence relation should be defined on the regular attributes and dominance relation on the criteria. Firstly, suppose condition attributes are criteria and decision attributes are regular attributes, dominance-equivalence relation is introduced,and the Discernibility-Matrix (DM) method of reduct generation is developed and compared with the attribute significance method. Secondly, when condition attributes are the hybrid of regular attributes and criteria, equivalence-dominance relation is then defined and Discernibility-Matrix approach of reduction generation is also provided.The effectiveness of this method is shown by both theoretical proof and illustrative example.

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

Access this chapter

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. Pawlak, Z.: Rough set: Theoretical aspects of reasoning about data. Kluwer Academic Publishers, Boston (1991)

    Book  MATH  Google Scholar 

  2. Kryszkiewicz, M.: Rough Set Approach to Incomplete Information System. Information Sciences 112, 39–49 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  3. Kryszkiewicz, M.: Comparative studies of alternative of knowledge reduction in inconsistent systems. Intelligent Systems 16(1), 105–120 (2001)

    MATH  Google Scholar 

  4. Zhang, W.X., Mi, J.S., Wu, W.Z.: Approaches to Knowledge Reductions in Inconsistent Systems. Chinese Journal of Computers 26, 12–18 (2003)

    MATH  Google Scholar 

  5. Greco, S., Matarazzo, B., Slowingski, R.: Intelligent Decision Support: Rough approximation of a preference relation by dominance relation. European Journal of Operation Research 117, 63–83 (1999)

    Article  MATH  Google Scholar 

  6. Xu, W.H., Zhang, W.X.: Distribution reduction in inconsistent information systems based on dominance relations. Fuzzy Systems and Mathematics 21(4), 124–131 (2007) (in Chinese)

    MathSciNet  MATH  Google Scholar 

  7. Xu, W.H., Zhang, X.Y., Zhang, W.X.: Lower approximation reduction in inconsistent information systems based on dominance relations. Computer Engineering and Applications 45(16), 66–68 (2009) (in Chinese)

    Google Scholar 

  8. Chen, J., Wang, G.Y., Hu, J.: Positive Domain Reduction Based on Dominance Relation in Inconsistent System. Computer Science 35(3), 216–218, 227 (2008) (in Chinese)

    Google Scholar 

  9. Zhang, W.X., Qiu, G.F.: Uncertain decision making based on rough set. Tsinghua University Press, Beijing (2005)

    Google Scholar 

  10. Shao, M.W., Zhang, X.Y.: Dominance relation and rules in an incomplete ordered information system. International Journal of Intelligent Systems 20, 13–27 (2005)

    Article  MATH  Google Scholar 

  11. Greco, S., Matarazzo, B., Slowinski, R.: Rough sets methodology for sorting problems in presence of multiple attributes and criteria. European Journal of Operational Research 138, 247–259 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  12. Blaszczynski, J., Greco, S., Slowinski, R.: Multi-criteria classification-A new scheme for application of dominance-based decision rules. European Journal of Operational Research 181, 1030–1044 (2007)

    Article  MATH  Google Scholar 

  13. Greco, S., Matarazzo, B., Slowinski, R.: Dominance-Based Rough Set Approach as a Proper Way of Handling Graduality in Rough Set Theory. Transactions on Rough Sets 7, 36–52 (2007)

    MathSciNet  MATH  Google Scholar 

  14. Blaszczynski, J., Greco, S., Slowinski, R., Szelag, M.: Monotonic variable consistency rough set approaches. International Journal of Approximate Reasoning 50, 979–999 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  15. Blaszczynski, J., Greco, S., Slowinski, R.: Ordinal and non-ordinal classification using monotonic rules. In: 8th International Conference of Modeling and Simulation-MOSIM 2010 (2010)

    Google Scholar 

  16. Blaszczynski, J., Slowinski, R., Szelag, M.: Sequential covering rule induction algorithm for variable consistency rough set approaches. Information Sciences (in press)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Li, Y., Zhao, J., Sun, NX., Wang, XZ., Zhai, JH. (2011). Discernibility-Matrix Method Based on the Hybrid of Equivalence and Dominance Relations. In: Kuznetsov, S.O., Ślęzak, D., Hepting, D.H., Mirkin, B.G. (eds) Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. RSFDGrC 2011. Lecture Notes in Computer Science(), vol 6743. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21881-1_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-21881-1_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21880-4

  • Online ISBN: 978-3-642-21881-1

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics