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Region Vector Based Attribute Reducts in Decision-Theoretic Rough Sets

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Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9437))

Abstract

When removing some attributes, the partition induced by a smaller set of attributes will be coarser and the decision regions may be changed. In this paper, we analyze the decision region changes when removing attributes and propose a new type of attribute reducts from the point of view of vector based three-way approximations of a partition. We also present a reduct construction method by using a discernibility matrix.

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Acknowledgements

This work was supported in part by the Project of Department of Education of Guangdong Province (no. 2014KTSCX152) and a Discovery Grant from NSERC, Canada.

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Authors and Affiliations

  1. School of Science, Foshan University, Foshan, 528000, China

    Guoshun Huang

  2. Department of Computer Science, University of Regina, Regina, SK, S4S 0A2, Canada

    Guoshun Huang & Yiyu Yao

Authors
  1. Guoshun Huang
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  2. Yiyu Yao
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Corresponding author

Correspondence to Guoshun Huang .

Editor information

Editors and Affiliations

  1. University of Regina, Regina, SK, Canada

    Yiyu Yao

  2. Tianjin University, Tianjin, China

    Qinghua Hu

  3. Chongqing University of Posts and Telecommunications, Chongqing, China

    Hong Yu

  4. University of Kansas, Lawrence, KS, USA

    Jerzy W. Grzymala-Busse

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Huang, G., Yao, Y. (2015). Region Vector Based Attribute Reducts in Decision-Theoretic Rough Sets. In: Yao, Y., Hu, Q., Yu, H., Grzymala-Busse, J.W. (eds) Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Lecture Notes in Computer Science(), vol 9437. Springer, Cham. https://doi.org/10.1007/978-3-319-25783-9_32

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  • DOI: https://doi.org/10.1007/978-3-319-25783-9_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25782-2

  • Online ISBN: 978-3-319-25783-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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