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Enhancing Recognition of a Weak Class – Comparative Study Based on Biological Population Data Mining

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Artificial Intelligence and Soft Computing (ICAISC 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7268))

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Abstract

This paper presents an overview of several methods that can be used to improve recognition of a weak class in binary classification problem. We illustrated this problem in the context of data mining based on a biological population data. We analyze feasibility of several approaches such as boosting, non-symmetric cost of misclassification events, and combining several weak classifiers (metalearning). We show that metalearning seems counter-productive if the goal is to enhance the recognition of a weak class, and that the method of choice would consist in combining boosting with the non-symmetric cost approach.

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Author information

Authors and Affiliations

  1. Institute of Computer Engineering, Control and Robotics, Wroclaw University of Technology, Wybrzeże Wyspiańskiego 27, 50-370, Wrocław, Poland

    Henryk Maciejewski, Olgierd Unold & Paweł Skrobanek

  2. Department of Horse Breeding and Riding, Wroclaw University of Environmental and Life Sciences, Kożuchowska 6, 51-631, Wrocaw, Poland

    Ewa Walkowicz

Authors
  1. Henryk Maciejewski
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  2. Ewa Walkowicz
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  3. Olgierd Unold
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  4. Paweł Skrobanek
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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, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

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

    Lotfi A. Zadeh

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

    Jacek M. Zurada

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© 2012 Springer-Verlag Berlin Heidelberg

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Maciejewski, H., Walkowicz, E., Unold, O., Skrobanek, P. (2012). Enhancing Recognition of a Weak Class – Comparative Study Based on Biological Population Data Mining. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_16

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  • DOI: https://doi.org/10.1007/978-3-642-29350-4_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29349-8

  • Online ISBN: 978-3-642-29350-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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