Journal
DATA & KNOWLEDGE ENGINEERING
Volume 68, Issue 11, Pages 1331-1347Publisher
ELSEVIER
DOI: 10.1016/j.datak.2009.07.007
Keywords
Decision rule; Dominance-based rough set; Dominance relation; Incomplete interval-valued information system; Knowledge reduction; Relative reduct
Funding
- Natural Science Foundation of China [60472060, 60572034, 60632050]
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Since preference order is a crucial feature of data concerning decision situations, the classical rough set model has been generalized by replacing the indiscernibility relation with a dominance relation. The purpose of this paper is to further investigate the dominance-based rough set in incomplete interval-valued information system, which contains both incomplete and imprecise evaluations of objects. By considering three types of unknown values in the incomplete interval-valued information system, a data complement method is used to transform the incomplete interval-valued information system into a traditional one. To generate the optimal decision rules from the incomplete interval-valued decision system, six types of relative reducts are proposed. Not only the relationships between these reducts but also the practical approaches to compute these reducts are then investigated. Some numerical examples are employed to substantiate the conceptual arguments. (C) 2009 Elsevier B.V. All rights reserved.
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