Optimized generalized decision in dominance-based rough set approach

K. Dembczynski, Salvatore Greco, W. Kotlowski, R. Slowinski

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

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.
Original languageEnglish
Title of host publicationRough sets and knowledge technology: proceedings of the second international conference
EditorsJ. Yao, P. Lingras, W. Wu, M. Szczuka, N. Cercone, D. Slezak
Place of PublicationBerlin
PublisherSpringer
Pages118-125
Number of pages8
Volume4481
Edition4481
ISBN (Print)9783540724575
DOIs
Publication statusPublished - 2007

Publication series

NameLecture notes in computer science
PublisherSpringer
Number4481

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