An Improved Attribute Reduction Algorithm based on Granular Computing

被引：0
|
作者：
Tang, X. [1 ,2 ]
Shu, L. [1 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 611731, Peoples R China
[2] Sichuan Normal Univ, Coll Math & Software Sci, Chengdu 610066, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL | 2015年 / 10卷 / 06期
关键词：
attribute reduction; granular computing; rough set; attribute significance;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Granular computing is a new intelligent computing method based on problem solving, information processing and pattern classification. Granular computing based attribute reduction method is an important application of Granular computing. These algorithms are mostly based on reduction core. However, some information systems may have no reduction core, especially in the actual application data. For this case, those algorithms are powerless. In this paper, an improved reduction algorithm based on granular computing is proposed. The algorithm is validated by the experimental result.
引用
收藏
页码：856 / 864
页数：9
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