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International Conference on Artificial Intelligence and Soft Computing

ICAISC 2006: Artificial Intelligence and Soft Computing – ICAISC 2006 pp 499–508Cite as

Additive Preference Model with Piecewise Linear Components Resulting from Dominance-Based Rough Set Approximations

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4029))

Abstract

Dominance-based Rough Set Approach (DRSA) has been proposed for multi-criteria classification problems in order to handle inconsistencies in the input information with respect to the dominance principle. The end result of DRSA is a decision rule model of Decision Maker preferences. In this paper, we consider an additive function model resulting from dominance-based rough approximations. The presented approach is similar to UTA and UTADIS methods. However, we define a goal function of the optimization problem in a similar way as it is done in Support Vector Machines (SVM). The problem may also be defined as the one of searching for linear value functions in a transformed feature space obtained by exhaustive binarization of criteria.

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Author information

Authors and Affiliations

  1. Institute of Computing Science, Poznań University of Technology, 60-965, Poznań, Poland

    Krzysztof Dembczyński, Wojciech Kotłowski & Roman Słowiński

  2. Polish Academy of Sciences, Institute for Systems Research, 01-447, Warsaw, Poland

    Roman Słowiński

Authors
  1. Krzysztof Dembczyński
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  2. Wojciech Kotłowski
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  3. Roman Słowiński
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Editor information

Editors and Affiliations

  1. Department of Artificial Intelligence, Academy of Humanities and Economics, Poland

    Leszek Rutkowski

  2. Institute of Automatics, AGH University of Science and Technology, Al. Mickiewicza 30, PL-30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Berkeley Initiative in Soft Computing (BISC), University of California, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Żurada

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© 2006 Springer-Verlag Berlin Heidelberg

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Dembczyński, K., Kotłowski, W., Słowiński, R. (2006). Additive Preference Model with Piecewise Linear Components Resulting from Dominance-Based Rough Set Approximations. In: Rutkowski, L., Tadeusiewicz, R., Zadeh, L.A., Żurada, J.M. (eds) Artificial Intelligence and Soft Computing – ICAISC 2006. ICAISC 2006. Lecture Notes in Computer Science(), vol 4029. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11785231_53

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  • DOI: https://doi.org/10.1007/11785231_53

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-35748-3

  • Online ISBN: 978-3-540-35750-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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