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The M-Relative Reduct Problem

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Book cover Rough Sets and Knowledge Technology (RSKT 2006)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4062))

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Abstract

Since there may exist many relative reducts for a decision table, some attributes that are very important from the viewpoint of human experts may fail to be included in relative reduct(s) computed by certain reduction algorithms. In this paper we present the concepts of M-relative reduct and core where M is a user specified attribute set to deal with this problem. M-relative reducts and cores can be obtained using M-discernibility matrices and functions. Their relationships with traditional definitions of relative reduct and core are closely investigated.

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References

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Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, P.R. China

    Fan Min, Qihe Liu, Hao Tan & Leiting Chen

Authors
  1. Fan Min
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  2. Qihe Liu
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  3. Hao Tan
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  4. Leiting Chen
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Editor information

Editors and Affiliations

  1. College of Computer Science and Technology, Chongqing, University of Posts and Telecommunication, 400065, Chongqing, P.R. China

    Guo-Ying Wang

  2. Department of Electrical and Computer Engineering, University of Manitoba, R3T 5V6, Winnipeg, Manitoba, Canada

    James F. Peters

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

    Andrzej Skowron

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

    Yiyu Yao

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© 2006 Springer-Verlag Berlin Heidelberg

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Min, F., Liu, Q., Tan, H., Chen, L. (2006). The M-Relative Reduct Problem. In: Wang, GY., Peters, J.F., Skowron, A., Yao, Y. (eds) Rough Sets and Knowledge Technology. RSKT 2006. Lecture Notes in Computer Science(), vol 4062. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11795131_25

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  • DOI: https://doi.org/10.1007/11795131_25

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-36297-5

  • Online ISBN: 978-3-540-36299-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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