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A Fast Algorithm to Building a Fuzzy Rough Classifier

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Machine Learning and Cybernetics (ICMLC 2014)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 481))

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Abstract

In this paper, by strict mathematic reasoning, we discover the relation between the similarity relation and lower approximation. Based on this relation, we design a fast algorithm to build a rule based fuzzy rough classifier. Finally, the numerical experiments demonstrate the efficiency and the affectivity of the proposed algorithm.

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Author information

Authors and Affiliations

  1. The Macau University of Science and Technology, Taipa, Macau, China

    Eric C. C. Tsang

  2. Key Laboratory of Data Engineering and Knowledge Engineering, Renmin University of China, MOE, Beijing, 100872, China

    Suyun Zhao

Authors
  1. Eric C. C. Tsang
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  2. Suyun Zhao
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Corresponding author

Correspondence to Eric C. C. Tsang .

Editor information

Editors and Affiliations

  1. Hebei University, Baoding, China

    Xizhao Wang

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

    Witold Pedrycz

  3. South China University of Technology, Guangzhou, China

    Patrick Chan

  4. Hebei University, Baoding, China

    Qiang He

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© 2014 Springer-Verlag Berlin Heidelberg

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Tsang, E.C.C., Zhao, S. (2014). A Fast Algorithm to Building a Fuzzy Rough Classifier. In: Wang, X., Pedrycz, W., Chan, P., He, Q. (eds) Machine Learning and Cybernetics. ICMLC 2014. Communications in Computer and Information Science, vol 481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45652-1_41

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  • DOI: https://doi.org/10.1007/978-3-662-45652-1_41

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-45651-4

  • Online ISBN: 978-3-662-45652-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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