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A Robust Fuzzy Rough Set Model Based on Minimum Enclosing Ball

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Rough Set and Knowledge Technology (RSKT 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6401))

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Abstract

Fuzzy rough set theory was introduced as a useful mathematical tool to handle real-valued data. Unluckily, its sensitivity to noise has a great impact on the application in real world. So it is necessary to enhance the robustness of fuzzy rough sets. In this work, based on the minimum enclosing ball problem we introduce a robust model of fuzzy rough sets. In addition, we define a robust fuzzy dependency function and apply it to evaluate features corrupted by noise. Experimental results show that the new model is robust to noise.

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Author information

Authors and Affiliations

  1. Harbin Institute of Technology, Harbin, 150001, P.R. China

    Shuang An, Qinghua Hu & Daren Yu

Authors
  1. Shuang An
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  2. Qinghua Hu
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  3. Daren Yu
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Editor information

Editors and Affiliations

  1. School of Computer and Information Technology, Beijing Jiaotong University, 100044, Beijing, China

    Jian Yu

  2. Faculty of Economics, University of Catania, Corso Italia, 55, 95129, Catania, Italy

    Salvatore Greco

  3. Department of Mathematics and Computing Science, Saint Mary’s University, B3H 3C3, Halifax, Nova Scotia, Canada

    Pawan Lingras

  4. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, 400065, Chongqing, China

    Guoyin Wang

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

    Andrzej Skowron

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An, S., Hu, Q., Yu, D. (2010). A Robust Fuzzy Rough Set Model Based on Minimum Enclosing Ball. In: Yu, J., Greco, S., Lingras, P., Wang, G., Skowron, A. (eds) Rough Set and Knowledge Technology. RSKT 2010. Lecture Notes in Computer Science(), vol 6401. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16248-0_19

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  • DOI: https://doi.org/10.1007/978-3-642-16248-0_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-16247-3

  • Online ISBN: 978-3-642-16248-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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