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Approximate Reducts of an Information System

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2003)

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

Abstract

Rough set is a tool for data mining. From an information system, we find reducts to generate decision rules for classification. However, for an information system has some noises, reducts may become meaningless or not appropriate for classification.

In this paper, we propose some indices to find approximate reducts. For finding indeices to measure subsets of attributes, we introduce the contingency matrix based on the number of objects in each class of the information system. The main advantage of using the contingency matrix is that there are some good properties for finding approximate reducts.

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References

  1. Beynon, M.: Reducts within the variable precision rough sets model: a further investigation. European journal of operational research 134(2001) 592–605

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Author information

Authors and Affiliations

  1. Department of Industrial Engineering and Management, Tokyo Institute of Technology, 2-12-1, O-okayama, Meguro-ku, Tokyo, 152-8552, Japan

    Tien-Fang Kuo & Yasutoshi Yajima

Authors
  1. Tien-Fang Kuo
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  2. Yasutoshi Yajima
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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

Kuo, TF., Yajima, Y. (2003). Approximate Reducts of an Information System. 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_41

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  • DOI: https://doi.org/10.1007/3-540-39205-X_41

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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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