Communications of the ACM
Variable Consistency Model of Dominance-Based Rough Sets Approach
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
An Algorithm for Induction of Decision Rules Consistent with the Dominance Principle
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Statistical Model for Rough Set Approach to Multicriteria Classification
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Constructive and algebraic methods of the theory of rough sets
Information Sciences: an International Journal
Incremental versus non-incremental rule induction for multicriteria classification
Transactions on Rough Sets II
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Dominance-based rough set introduced by Greco et al. is an extension of Pawlak¡¯s classical rough set theory by using dominance relations in place of equivalence relations for approximating sets of preference ordered decision classes satisfying upward and downward union properties. This paper introduces the concept of indexed blocks for representing dominance-based approximation spaces. Indexed blocks are sets of objects indexed by pairs of decision values. In our study, inconsistent information is represented by exclusive neighborhoods of indexed blocks. They are used to define approximations of decision classes. It turns out that a set of indexed blocks with exclusive neighborhoods forms a partition on the universe of objects. Sequential rules for updating indexed blocks incrementally are considered and illustrated with examples.