Test-cost-sensitive based rough set approach

被引：0
作者：
Ju H. [1 ,4 ]
Zhou X. [1 ,2 ]
Yang P. [1 ,3 ]
Li H. [1 ]
Yang X. [4 ]
机构：
[1] School of Management and Engineering, Nanjing University, Nanjing
[2] Research Center for Novel Technology of Intelligent Equipments, Nanjing University, Nanjing
[3] State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing
[4] School of Computer Science and Engineering, Jiangsu University of Science and Technology, Zhenjiang
来源：
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice | 2017年 / 37卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Attribute reduction; Rough set; Test-cost-sensitive; α quantitative indiscernibility relation;
D O I：
10.12011/1000-6788(2017)01-0228-13
中图分类号：
学科分类号：
摘要：
In rough set model, α quantitative indiscernibility relation is a generalization of both strong and weak indiscernibility relations. However, such three indiscernibility relations based rough sets do not take the test costs of the attributes into consideration. To solve this problem, a test-cost-sensitive α quantitative indiscernibility relation based rough set is proposed. From the viewpoint of the binary relation, the new rough set is then sensitive to test costs. Moreover, the relationships among strong, weak, α quantitative and test-cost-sensitive α quantitative indiscernibility relations based rough sets are explored. Finally, it is noticed that the traditional heuristic algorithm does not take the decreasing of cost into account. Therefore, not only a new fitness function is proposed, but also such fitness function is carried out in genetic algorithm for obtaining reduct with minor test cost. The experimental results show that such approach not only decreases the uncertainty comes from boundary region, but also decreases the cost of reduct. © 2017, Editorial Board of Journal of Systems Engineering Society of China. All right reserved.
引用
收藏
页码：228 / 240
页数：12
相关论文
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