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A Multi-View Decision Model Based on Decision-Theoretic Rough Set

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Book cover Rough Sets and Knowledge Technology (RSKT 2009)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5589))

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Abstract

A review of Pawlak rough set models and probabilistic rough set models is presented, and a multi-view decision method based on decision-theoretic rough set model is proposed, in which optimistic decision, pessimistic decision, and indifferent decision are provided according to the cost of misclassification, which are well interpreted based on both practical examples and theoretic analysis.

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Author information

Authors and Affiliations

  1. School of Management and Engineering, Nanjing University, Nanjing, Jiangsu, 210093, P.R. China

    Xianzhong Zhou & Huaxiong Li

  2. State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing, Jiangsu, 210093, P.R. China

    Xianzhong Zhou

Authors
  1. Xianzhong Zhou
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  2. Huaxiong Li
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Editor information

Editors and Affiliations

  1. Faculty of Engineering and Surveying and Engineering, University of Southern Queensland, QLD 4350, Australia

    Peng Wen

  2. School of Information Technology, Queensland University of Technology, QLD 4001, Brisbane, Australia

    Yuefeng Li

  3. Institute of Mathematics, Warsaw University of Technology, Koszykowa 86, 02008, Warsaw, Poland

    Lech Polkowski

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

    Yiyu Yao

  5. Faculty of Medicine, Department of Medical Informatics, Shimane University, 89-1 Enya-cho, Izumo, 693-8501, Shimane, Japan

    Shusaku Tsumoto

  6. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

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© 2009 Springer-Verlag Berlin Heidelberg

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Zhou, X., Li, H. (2009). A Multi-View Decision Model Based on Decision-Theoretic Rough Set. In: Wen, P., Li, Y., Polkowski, L., Yao, Y., Tsumoto, S., Wang, G. (eds) Rough Sets and Knowledge Technology. RSKT 2009. Lecture Notes in Computer Science(), vol 5589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02962-2_82

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  • DOI: https://doi.org/10.1007/978-3-642-02962-2_82

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02961-5

  • Online ISBN: 978-3-642-02962-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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