Optimized generalized decision in dominance-based rough set approach

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

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Abstract

Dominance-based Rough Set Approach (DRSA) has been proposed to deal with multi-criteria classification problems, where data may be inconsistent with respect to the dominance principle. However, in real-life datasets, in the presence of noise, the notions of lower and upper approximations handling inconsistencies were found to be excessively restrictive which led to the proposal of the variable consistency variant of the theory. In this paper, we deal with a new approach based on DRSA, whose main idea is based on the error corrections. A new definition of the rough set concept known as generalized decision is introduced, the optimized generalized decision. We show its connections with statistical inference and dominance-based rough set theory.