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Intuitionistic Fuzzy Classifier for Imbalanced Classes

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Artificial Intelligence and Soft Computing (ICAISC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7894))

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Abstract

Imbalanced classes are a real challenge for the classifiers. Imbalanced classes are the classes smaller than other classes but not necessary small ones. Most often the smaller classes are more interested from an user point of view but more difficult to be seen by a classifier. In this paper, which is a continuation of our previous works, we discuss a classifier using some inherited features of Atanassov’s intuitionistic fuzzy sets (A-IFSs for short) making them a good tool for recognizing imbalanced classes. We illustrate our considerations on benchmark examples paying attention to detailed behavior of the classifier proposed (several measures besides general accuracy are examined). We use simple cross validation method (with 10 experiments). Results are compared with a fuzzy classifier known as a good one from literature. We also consider a problem of granulation (symmetric or asymmetric granulation, and a number of the intervals used) and its influence on the results.

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Author information

Authors and Affiliations

  1. Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447, Warsaw, Poland

    Eulalia Szmidt, Janusz Kacprzyk & Marta Kukier

  2. Warsaw School of Information Technology, ul. Newelska 6, 01-447, Warsaw, Poland

    Eulalia Szmidt & Janusz Kacprzyk

Authors
  1. Eulalia Szmidt
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  2. Janusz Kacprzyk
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  3. Marta Kukier
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Michiewicza 30, 30-059, KrakĂłw, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Electrical and Computer Engineering, University of Louisville, 405 Lutz Hall, 40292, Louisville, KY, USA

    Jacek M. Zurada

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Szmidt, E., Kacprzyk, J., Kukier, M. (2013). Intuitionistic Fuzzy Classifier for Imbalanced Classes. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2013. Lecture Notes in Computer Science(), vol 7894. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38658-9_43

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  • DOI: https://doi.org/10.1007/978-3-642-38658-9_43

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38657-2

  • Online ISBN: 978-3-642-38658-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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