Clustering Based on Rough Set Knowledge Discovery

被引：0

作者：

Shan, Chen ^{[1
]}

机构：

[1] Linyi Univ, Sch Informat, Linyi, Peoples R China

来源：

FUTURE COMPUTER, COMMUNICATION, CONTROL AND AUTOMATION | 2011年 / 119卷

关键词：

Component; Data mining; Rough set; High dimensional; Clustering;

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：

The rough set knowledge discovery process for the clustering, the use of the properties have defined the similarity between two objects on the Complete Works of calculation, find the selected object and all other equivalence classes of objects of different equivalence classes Complete access to the property on the intersection of the object that the initial equivalence class, then the initial indiscernibility equivalence classes of modified, merged subclasses, a final clustering results. Proved by the rough clustering derived knowledge discovery method is feasible, improve the speed of cluster computing, clustering results are reasonable.

引用

页码：561 / 565

页数：5