Survey on Attribute Reduction Algorithm of Rough Set

被引：0
|
作者：
Zhou T. [1 ,4 ]
Lu H.-L. [2 ]
Ren H.-L. [3 ]
Huo B.-Q. [1 ]
机构：
[1] School of Computer Science and Engineering, North Minzu University, Yinchuan
[2] School of Science, Ningxia Medical University, Yinchuan
[3] The First People's Hospital of Yinchuan City, Yinchuan
[4] Key Laboratory of Images & Graphics Intelligent Processing of State Ethnic Affairs Commission, North Minzu University, Yinchuan
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2021年 / 49卷 / 07期
关键词：
Attribute reduction; Dynamic decision; Incompatible decision; Incomplete decision; Rough set;
D O I：
10.12263/DZXB.20200330
中图分类号：
学科分类号：
摘要：
Attribute reduction is an important research direction in rough set. This paper summarizes attribute reduction algorithms based on rough sets from eight aspects, including incomplete decision information tables, incompatible decision information tables, continuous attribute decision information tables, dynamic decision information table, ordered data decision information table, attribute reduction algorithm based on rough extension model, attribute reduction algorithm based on attribute importance degree and attribute reduction algorithm based on intelligent optimization algorithm. Through summarizing eight aspects of attribute reduction algorithms based on rough set, positive significance is shown for further research on attribute reduction algorithm of rough set. © 2021, Chinese Institute of Electronics. All right reserved.
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页码：1439 / 1449
页数：10
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