Skip to main content

The OR Data Complement Method for Incomplete Decision Tables

  • Conference paper
  • 1526 Accesses

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 105))

Abstract

Uncertain information can not be processed by Pawlak rough set theory, and the missing data must be completed for applying in knowledge acquisition. In this paper, OR transposed table was proposed based on attribute reduction mentality to target incomplete decision tables. OR value can be selected from values of attribute by transforming information table into OR transposed table and using attribute reduction mentality, therefore the incomplete decision tables were transformed into complete decision table. And finally the example is analyzed.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
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

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Wang, X.: A Data Complement Method for Incomplete Decision Tables. Journal of Tianjin University of Science & Technology 22(3), 62–64 (2007)

    Google Scholar 

  2. Li, Y.: A Data Complement Method of Incomplete Decision Table. Science & Technology Information 20, 508–509 (2008)

    Google Scholar 

  3. Li, P., Wu, Q.: Completing data algorithms based on probability similarity. Application on Research of Computers 26(3), 881–883 (2009)

    Google Scholar 

  4. Chen, H., Zhang, M., Yang, J.-a.: Method of Data Discretization Based on Rough Set Theory. Computer Engineering 44(3), 30–32 (2008)

    MathSciNet  Google Scholar 

  5. Ning, W., Zhao, M.: More Improved Greedy Algorithm for Discretization of Decision Table. Computer Engineering and Applications 43(3), 173–174 (2007)

    MathSciNet  Google Scholar 

  6. Qu, B., Lu, Y.: Fast Attribute Reduction Algorithm Based on Rough Sets. Computer Engineering 33(11), 7–9 (2007)

    Google Scholar 

  7. Lu, S., Liu, F., Hu, B.: A attribute reduction algorithm based on attribute dependence. Journal of Huazhong University of Science & Technology 36(2), 39–41 (2008)

    MATH  Google Scholar 

  8. Zhang, W., Liang, Y., Wo, Z.: Information System and Knowledge Discovery. Science Publishers, Beijing (2003)

    Google Scholar 

  9. Zhang, W., Liang, Y., Wo, Z.: Rough Set Theory and Knowledge Acquisition. Xi’an Jiaotong University Press, Xi’an (2001)

    Google Scholar 

  10. Kantardzic, M.: Data Mining Concepts, Models, Methods and Algorithms. Wiley-Interscience, Piscataway (2003)

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Xu, J., Yang, Y., Liu, B. (2010). The OR Data Complement Method for Incomplete Decision Tables. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds) Information Computing and Applications. ICICA 2010. Communications in Computer and Information Science, vol 105. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16336-4_48

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-16336-4_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16335-7

  • Online ISBN: 978-3-642-16336-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics