Computer Science ›› 2017, Vol. 44 ›› Issue (9): 67-69, 92.doi: 10.11896/j.issn.1002-137X.2017.09.013

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Attribute Reduction Based on Multicost Decision-theoretic Rough Set

YANG Zhi-rong, WANG Yu and YANG Xi-bei   

  • Online:2018-11-13 Published:2018-11-13

Abstract: Compared with classic rough set,traditional decision-theoretic rough set takes the cost into consideration,using cost matrix to generate a pair of thresholds.But decision-theoretic rough set doesn’t meet the monotonicity that has been widely used in classic rough set,which has brought a new challenge for us in the study of attribute reduction in rough set. Cost matrix in traditional decision-theoretic rough set is only one,doesn’t think about the variability of cost.The pessimistic decision rules and the optimistic rules of muticost decision-theoretic rough set are introduced at first and the thresholds which generated by multiple cost matrix are applied to attribute reduction.An heuristic Local attribute reduction method is proposed not on whole decision class but on individual decision class,which can get more positive rules from relevant experiment results in optimistic conditions than in pessimistic conditions,when it compared with the method based on the whole decision class.

Key words: Decision-theoretic rough set,Multi-cost,Three-way decision-theoretic

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