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Chapter

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Title

Bayesian Decision Theory for Dominance-Based Rough Set Approach

Authors

[ 1 ] Instytut Informatyki (II), Wydział Informatyki i Zarządzania, Politechnika Poznańska | [ P ] employee

Year of publication

2007

Chapter type

paper

Publication language

english

Keywords
EN
  • Bayesian Decision Theory
  • Dominance
  • Rough Set Theory
  • Variable Consistency
  • Cost of Misclassification
Abstract

EN 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.

Pages (from - to)

134 - 141

DOI

10.1007/978-3-540-72458-2_16

URL

https://link.springer.com/chapter/10.1007/978-3-540-72458-2_16

Book

Rough Sets and Knowledge Technology. Second International Conference, RSKT 2007, Toronto, Canada, May 14-16, 2007. Proceedings

Presented on

2nd International Conference on Rough Sets and Knowledge Technology, RSKT 2007, 14-16.05.2007, Toronto, Canada

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