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The Variable Precision Rough Set Model for Data Mining in Inconsistent Information System

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Content Computing (AWCC 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3309))

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Abstract

The variable precision rough set (VPRS) model is an extension of original rough set model. For inconsistent information system, the VPRS model allows a flexible approximation boundary region by a precision variable. This paper is focused on data mining in inconsistent information system using the VPRS model. A method based on VPRS model is proposed to apply to data mining for inconsistent information system. By our method the deterministic and probabilistic classification rules are acquired from the inconsistent information system. An example is given to show that the method of data mining for inconsistent information system is effective.

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Author information

Authors and Affiliations

  1. Institute of Computer Application in Planning and Design, University of Karlsruhe, 76128, Karlsruhe, Germany

    Qingmin Zhou

  2. Institute of Product Development, University of Karlsruhe, 76128, Karlsruhe, Germany

    Chenbo Yin

  3. College of Information Science and Engineering, Nanjing University of Technology, 210009, Nanjing, P.R. China

    Qingmin Zhou

  4. College of Mechanical and Power Engineering, Nanjing University of Technology, 210009, Nanjing, P.R. China

    Chenbo Yin & Yongsheng Li

Authors
  1. Qingmin Zhou
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  2. Chenbo Yin
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  3. Yongsheng Li
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Editor information

Editors and Affiliations

  1. School of Software, Tsinghua University,  

    Chi-Hung Chi

  2. School of Software, Tsinghua University, Beijing, PR China

    Kwok-Yan Lam

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© 2004 Springer-Verlag Berlin Heidelberg

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Zhou, Q., Yin, C., Li, Y. (2004). The Variable Precision Rough Set Model for Data Mining in Inconsistent Information System. In: Chi, CH., Lam, KY. (eds) Content Computing. AWCC 2004. Lecture Notes in Computer Science, vol 3309. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30483-8_34

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  • DOI: https://doi.org/10.1007/978-3-540-30483-8_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23898-0

  • Online ISBN: 978-3-540-30483-8

  • eBook Packages: Springer Book Archive

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