Bayesian Decision Theory for Dominance-Based Rough Set Approach

  • Salvatore Greco
  • Roman Słowiński
  • Yiyu Yao
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4481)


Dominance-based Rough Set Approach (DRSA) has been proposed to generalize classical rough set approach when consideration of monotonicity between degrees of membership to considered concepts has to be taken into account. This is typical for data describing various phenomena, e.g., “the larger the mass and the smaller the distance, the larger the gravity”, or “the more a tomato is red, the more it is ripe”. These monotonicity relationships are fundamental in rough set approach to multiple criteria decision analysis. In this paper, we propose a Bayesian decision procedure for DRSA. Our approach permits to take into account costs of misclassification in fixing parameters of the Variable Consistency DRSA (VC-DRSA), being a probabilistic model of DRSA.


Bayesian Decision Theory Dominance Rough Set Theory Variable Consistency Cost of Misclassification 


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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Salvatore Greco
    • 1
  • Roman Słowiński
    • 2
  • Yiyu Yao
    • 3
  1. 1.Faculty of Economics, University of Catania, Corso Italia, 55, 95129 CataniaItaly
  2. 2.Institute of Computing Science, Poznań University of Technology, 60-965 Poznań, and Institute for Systems Research, Polish Academy of Sciences, 01-447 WarsawPoland
  3. 3.Department of Computer Science, University of Regina, S4S0A2 Regina, SaskatchewanCanada

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