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An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough Classification

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Rough Sets and Current Trends in Computing (RSCTC 2010)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6086))

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Abstract

In this paper we present results of an experimental comparison (in terms of an error rate) of rule sets induced by the LERS data mining system with rule sets induced using the probabilistic rough classification (PRC). As follows from our experiments, the performance of LERS (possible rules) is significantly better than the best rule sets induced by PRC with any threshold (two-tailed test, 5% significance level). Additionally, the LERS possible rule approach to rule induction is significantly better than the LERS certain rule approach (two-tailed test, 5% significance level).

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Author information

Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS 66045, USA

    Jerzy W. Grzymala-Busse & Shantan R. Marepally

  2. Institute of Computer Science, Polish Academy of Sciences, 01–237, Warsaw, Poland

    Jerzy W. Grzymala-Busse

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

    Yiyu Yao

Authors
  1. Jerzy W. Grzymala-Busse
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  2. Shantan R. Marepally
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  3. Yiyu Yao
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Editor information

Editors and Affiliations

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

    Marcin Szczuka

  2. ICS, Warsaw University of Technology,,  

    Marzena Kryszkiewicz

  3. Department of Applied Computer Science, University of Winnipeg, R3B 2E9, Winnipeg, Manitoba, Canada

    Sheela Ramanna

  4. Dept. of Computer Science, The University of Wales, Aberystwyth, UK

    Richard Jensen

  5. Harbin Institute of Technology, PO Box 458, 150006, Harbin, China

    Qinghua Hu

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Grzymala-Busse, J.W., Marepally, S.R., Yao, Y. (2010). An Empirical Comparison of Rule Sets Induced by LERS and Probabilistic Rough Classification. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds) Rough Sets and Current Trends in Computing. RSCTC 2010. Lecture Notes in Computer Science(), vol 6086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13529-3_63

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  • DOI: https://doi.org/10.1007/978-3-642-13529-3_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-13528-6

  • Online ISBN: 978-3-642-13529-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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