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International Workshop on Rough Sets, Fuzzy Sets, Data Mining, and Granular-Soft Computing

RSFDGrC 2003: Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing pp 138–145Cite as

An Application of Rough Sets to Monk’s Problems Solving

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2639))

Abstract

In this paper, the main techniques of inductive machine learning are united to the knowledge reduction theory based on rough sets from the theoretical point of view. And then the Monk’s problems are resolved again employing rough sets. As far as accuracy and conciseness are concerned, the learning algorithms based on rough sets have remarkable superiority to the previous methods.

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References

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Author information

Authors and Affiliations

  1. Dpt. of Computer Science, Tongji University, Shanghai, 200092, P. R. China

    Duoqian Miao

  2. Tongji Branch, National High Performance Computing Center, Shanghai, 200092, P. R. China

    Duoqian Miao

  3. Dpt of Mathematics, Shanxi University, Taiyuan, 030006, P. R. China

    Lishan Hou

Authors
  1. Duoqian Miao
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  2. Lishan Hou
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Editor information

Editors and Affiliations

  1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, P.R. China

    Guoyin Wang

  2. Department of Computer Science, Nanchang University, Nanchang, 330029, P.R. China

    Qing Liu

  3. Department of Computer Science, University of Regina, Regina, Saskatchewan, S4S 0A2, Canada

    Yiyu Yao

  4. Institute of Mathematics, Warsaw University, Banacha 2, 02-097, Warsaw, Poland

    Andrzej Skowron

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© 2003 Springer-Verlag Berlin Heidelberg

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Cite this paper

Miao, D., Hou, L. (2003). An Application of Rough Sets to Monk’s Problems Solving. In: Wang, G., Liu, Q., Yao, Y., Skowron, A. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. RSFDGrC 2003. Lecture Notes in Computer Science(), vol 2639. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-39205-X_18

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  • DOI: https://doi.org/10.1007/3-540-39205-X_18

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-14040-5

  • Online ISBN: 978-3-540-39205-7

  • eBook Packages: Springer Book Archive

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