|Table of Contents|

Research on Attribute Reduction Criteria in Decision-Theoretic Rough Set(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2015年01期
Page:
41-
Research Field:
计算机科学
Publishing date:

Info

Title:
Research on Attribute Reduction Criteria in Decision-Theoretic Rough Set
Author(s):
Ju Hengrong1; 2; Yang Xibei1; 2; 3; Yu Hualong1; Qi Yong3; Yang Jingyu2
(1.School of Computer Science and Engineering,Jiangsu University of Science and Technology,Zhenjiang 212003,China)(2.Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information,Nanjing University of Science and Technology,Ministry of Education,Nanjing 210094,China)(3.School of Economics and Management,Nanjing University of Science and Technology,Nanjing 210094,China)
Keywords:
attribute reduction; cost criterion; decision-theoretic rough set; decision-monotonicity; generality criterion
PACS:
TP18
DOI:
-
Abstract:
Attribute reduction is one of the important research issues in rough set theory. In classical Pawlak rough set,the lower and upper approximations are monotonic with respect to the set inclusion of attributes. However,in decision-theoretic rough set model,the lower and upper approximations may increase or decrease with respect to the increasing of attributes. To address this issue,from the viewpoint of optimization,fitness functions of the decision-monotonicity criterion,generality criterion and cost criterion have been proposed respectively. Genetic algorithm is also applied to compute reducts. The experimental results show that:the reducts based on decision-monotonicity criterion can generate more positive rules; the reducts based on generality criterion can generate most positive rules; the reducts based on cost criterion can obtain lowest decision costs.

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Last Update: 2015-03-30