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Rough Mereological Classifiers Obtained from Weak Variants of Rough Inclusions

  • Piotr Artiemjew
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5009)

Abstract

Granular reflections of data sets have turned out to be very effective in data classification. In this work we present results of classification of real data sets by means of an approach in which granules of objects or decision rules are built on the basis of weak variants of rough inclusions.

Keywords

rough sets granulation of knowledge rough inclusions classification of data 

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References

  1. [B]
    Bazan, J.G.: A comparison of dynamic and non–dynamic rough set methods for extracting laws from decision tables. In: Polkowski, L., Skowron, A. (eds.) Rough Sets in Knowledge Discovery 1, pp. 321–365. Physica, Heidelberg (1998)Google Scholar
  2. [Po1]
    Polkowski, L.: On the idea of using granular rough mereological structures in classification of data. In: RSKT 2008. LNCS, vol. 5009, Springer, Heidelberg (in print 2008)Google Scholar
  3. [Po2]
    Polkowski, L.: The paradigm of granular rough computing. In: Zhang, D., Wang, Y., Kinsner, W. (eds.) ICCI 2007, pp. 145–163. IEEE Computer Society, Los Alamitos (2007)Google Scholar
  4. [Po3]
    Polkowski, L.: Formal granular calculi based on rough inclusions (a feature talk). In: Zhang, Y.-Q., Lin, T.Y. (eds.) IEEE GrC 2006, pp. 9–18. IEEE Press, Piscataway (2006)CrossRefGoogle Scholar
  5. [Po4]
    Polkowski, L.: Formal granular calculi based on rough inclusions (a feature talk). In: Hu, X., Liu, Q., Skowron, A., Lin, T.Y., Yager, R.R., Zhang, B. (eds.) IEEE GrC 2005, pp. 57–62. IEEE Press, Piscataway (2005)CrossRefGoogle Scholar
  6. [Po5]
    Polkowski, L.: Rough Sets. Mathematical Foundations. Physica, Heidelberg (2002)Google Scholar
  7. [PoA]
    Polkowski, L., Artiemjew, P.: On granular rough computing: Factoring clasifiers through granular structures. In: Kryszkiewicz, M., Peters, J.F., Rybinski, H., Skowron, A. (eds.) RSEISP 2007. LNCS (LNAI), vol. 4585, pp. 280–290. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  8. [RSES]
  9. [UCI]

Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Piotr Artiemjew
    • 1
  1. 1.University of Warmia and MazuryOlsztynPoland

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