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Advances in Machine Learning I pp 321–344Cite as

An Analysis of the FURIA Algorithm for Fuzzy Rule Induction

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 262))

Abstract

This paper elaborates on a novel fuzzy rule-based classification method called FURIA, which is short for “Fuzzy Unordered Rule Induction Algorithm”. FURIA has recently been developed as an extension of the well-known RIPPER algorithm. It learns fuzzy rules instead of conventional rules and unordered rule sets instead of rule lists. Moreover, to deal with uncovered examples, it makes use of an efficient rule stretching method. First experimental results have shown that FURIA significantly outperforms the original RIPPER in terms of classification accuracy. Elaborating on the advantages of a fuzzy approach, this paper makes an attempt to distill and quantify the influence of rule fuzzification on the performance of the algorithm. Moreover, going beyond the conventional classification problem, we investigate the performance of FURIA in the context of bipartite ranking, in which a fuzzy approach appears to be even more appealing.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Marburg, Hans-Meerwein-Straße, 35039, Marburg, Germany

    Jens Christian Hühn & Eyke Hüllermeier

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  1. Jens Christian Hühn
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  2. Eyke Hüllermeier
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Editor information

Editors and Affiliations

  1. Institute of Computer Science, Polish Academy of Sciences, ul.Ordona 21, 01-237, Warsaw, Poland

    Jacek Koronacki  & Sławomir T. Wierzchoń  & 

  2. Woodward Hall 430C University of North Carolina, 9201 University City Blvd., N.C. 28223, Charlotte, USA

    Zbigniew W. Raś

  3. Systems Research Institute, Polish Academy of Sciences, ul.Newelska 6, 01-447, Warsaw, 01-447

    Janusz Kacprzyk

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Hühn, J.C., Hüllermeier, E. (2010). An Analysis of the FURIA Algorithm for Fuzzy Rule Induction. In: Koronacki, J., Raś, Z.W., Wierzchoń, S.T., Kacprzyk, J. (eds) Advances in Machine Learning I. Studies in Computational Intelligence, vol 262. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05177-7_16

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  • DOI: https://doi.org/10.1007/978-3-642-05177-7_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05176-0

  • Online ISBN: 978-3-642-05177-7

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