Approximate Reduction Algorithm Based on Rough Set Theory

被引:0
|
作者
Shao Bin [1 ]
Jiang Yunhang [1 ]
Shen Qing [1 ]
机构
[1] Huzhou Teachers Coll, Sch Informat Engn, Huzhou, Zhejiang, Peoples R China
关键词
Rough set; Attribute reduction strategy; Discernibility matrix; Approximate reduction;
D O I
10.1109/CW.2008.44
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The attribute reduction of information system can enhance accuracy and efficiency of knowledge discovery, machine learning, etc. After studying reduction strategy in rough set theory, the concept of approximate reduction and an approximate reduction algorithm are proposed in this paper. This algorithm can retain minimal attributes in the basic style of information system, i.e. reduce as many attributes as possible. That can save much time for the system's later disposal. The algorithm's lime complexity hasn't been improved, but attributes after reduction are reduced greatly. The original information system has a certain loss, but this can be accepted under a certain significance level. Lastly, the reduction strategy is compared with approximate reduction strategy by nine attributes which belong to the information system.
引用
收藏
页码:410 / 415
页数:6
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