标题:An attribute reduction algorithm based on the maximum dependency and minimum redundancy of attribute
作者:Wang, Chenxi ;Fan, Jiancong
通讯作者:Fan, Jiancong
作者机构:[Wang, Chenxi ;Fan, Jiancong ] College of Computer Science and Engineering, Provincial Experimental Teaching Demonstration Center of Computer, Shandon 更多
会议名称:14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery, ICNC-FSKD 2018
会议日期:July 28, 2018 - July 30, 2018
来源:ICNC-FSKD 2018 - 14th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery
出版年:2019
页码:568-574
DOI:10.1109/FSKD.2018.8687131
摘要:The classical attribute reduction algorithms based on attribute dependence in rough set theory only select attributes which have a larger degree of dependence on decision attribute and don't consider attribute redundancy. This paper points out that only selecting condition attributes with a large degree of dependence on decision attribute is not enough, the redundancy between condition attributes should also be taken into account. In allusion to this matter, an algorithm based on the maximum dependency and minimum redundancy of attribute is presented. The results of experiments which are carried out on the UCI data sets suggest that the presented algorithm has gained favorable results.
© 2018 IEEE.
收录类别:EI
资源类型:会议论文
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