The variable precision rough set model for data mining in inconsistent information system

被引：0

作者：

Zhou, QM ^{[1
]}

Yin, CB

Li, YS

机构：

[1] Univ Karlsruhe, Inst Comp Applicat Planning & Design, D-76128 Karlsruhe, Germany

[2] Univ Karlsruhe, Inst Prod Dev, D-76128 Karlsruhe, Germany

[3] Nanjing Univ Technol, Coll Informat Sci & Engn, Nanjing 210009, Peoples R China

[4] Nanjing Univ Technol, Coll Mech & Power Engn, Nanjing 210009, Peoples R China

来源：

CONTENT COMPUTING, PROCEEDINGS | 2004年 / 3309卷

关键词：

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

The variable precision rough set (VPRS) model is an extension of original rough set model. For inconsistent information system, the VPRS model allows a flexible approximation boundary region by a precision variable. This paper is focused on data mining in inconsistent information system using the VPRS model. A method based on VPRS model is proposed to apply to data mining for inconsistent information system. By our method the deterministic and probabilistic classification rules are acquired from the inconsistent information system. An example is given to show that the method of data mining for inconsistent information system is effective.

引用

页码：285 / 290

页数：6

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