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Type-2 Fuzzy Decision Trees

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Artificial Intelligence and Soft Computing – ICAISC 2008 (ICAISC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5097))

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Abstract

This paper presents type-2 fuzzy decision trees (T2FDTs) that employ type-2 fuzzy sets as values of attributes. A modified fuzzy double clustering algorithm is proposed as a method for generating type-2 fuzzy sets. This method allows to create T2FDTs that are easy to interpret and understand. To illustrate performace of the proposed T2FDTs and in order to compare them with results obtained for type-1 fuzzy decision trees (T1FDTs), two benchmark data sets, available on the internet, have been used.

This work was partly supported by the Foundation for Polish Science (Professorial Grant 2005-2008) and the Polish State Committee for Scientific Research (Grant N518 035 31/3292), Special Research Project 2006-2009, Polish-Singapore Research Project 2008-2010, Research Project 2008-2010.

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Authors and Affiliations

  1. Department of Computer Engineering, Czestochowa University of Technology, Poland

    Łukasz Bartczuk & Danuta Rutkowska

Authors
  1. Łukasz Bartczuk
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  2. Danuta Rutkowska
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Editor information

Leszek Rutkowski Ryszard Tadeusiewicz Lotfi A. Zadeh Jacek M. Zurada

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Bartczuk, Ł., Rutkowska, D. (2008). Type-2 Fuzzy Decision Trees. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2008. ICAISC 2008. Lecture Notes in Computer Science(), vol 5097. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69731-2_20

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  • DOI: https://doi.org/10.1007/978-3-540-69731-2_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-69572-1

  • Online ISBN: 978-3-540-69731-2

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