Bayesian decision theory for dominance-based rough set approach

Authors:
Salvatore Greco;Roman Słowiński;Yiyu Yao
Affiliations:
Faculty of Economics, University of Catania, Catania, Italy;Institute of Computing Science, Poznan University of Technology, Poznan and Institute for Systems Research, Polish Academy of Sciences, Warsaw, Poland;Department of Computer Science, University of Regina, Regina, Saskatchewan, Canada
Venue:
RSKT'07 Proceedings of the 2nd international conference on Rough sets and knowledge technology
Year:
2007

Citing 2
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Abstract

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.