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A Feature Seletion Method Based on Variable Precision Tolerance Rough Sets

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Rough Sets and Knowledge Technology (RSKT 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8818))

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Abstract

Feature selection is an important notions in rough sets. This paper presents a method combining tolerance relation together with rough sets. There is noise data in practical data sets. This paper investigates the feature selection method based on variable precision tolerance rough sets. The parameter was discussed and the parameter interval was described. With the change of the parameter value, the feature selection was different. The efficiency of the proposed method can be illustrated by an experiment with standard dataset from UCI database.

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Author information

Authors and Affiliations

  1. Department of Information Science and Technology, East China University of Political Science and Law, Shanghai, 201804, P.R. China

    Na Jiao

Authors
  1. Na Jiao
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Corresponding author

Correspondence to Na Jiao .

Editor information

Editors and Affiliations

  1. Tongji University, Shanghai, China

    Duoqian Miao

  2. Department of Electrical and Computer En, University of Alberta, Edmonton, Alberta, Canada

    Witold Pedrycz

  3. University of Warsaw, Warsaw, Poland

    Dominik Ślȩzak

  4. University of Applied Sciences, München, Germany

    Georg Peters

  5. Tianjin University, Tianjin, China

    Qinghua Hu

  6. Tongji University, Shanghai, China

    Ruizhi Wang

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© 2014 Springer International Publishing Switzerland

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Jiao, N. (2014). A Feature Seletion Method Based on Variable Precision Tolerance Rough Sets. In: Miao, D., Pedrycz, W., Ślȩzak, D., Peters, G., Hu, Q., Wang, R. (eds) Rough Sets and Knowledge Technology. RSKT 2014. Lecture Notes in Computer Science(), vol 8818. Springer, Cham. https://doi.org/10.1007/978-3-319-11740-9_46

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  • DOI: https://doi.org/10.1007/978-3-319-11740-9_46

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11739-3

  • Online ISBN: 978-3-319-11740-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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