Rough set based on modified ChiMerge algorithm and its application

被引：0

作者：

Gu, XH ^{[1
]}

Hou, DB ^{[1
]}

Zhou, ZK ^{[1
]}

Yu, D ^{[1
]}

机构：

[1] Zhejiang Univ, Dept Control Sci & Engn, Hangzhou 310027, Peoples R China

来源：

PROCEEDINGS OF 2005 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-9 | 2005年

关键词：

rough set theory; ChiMerge algorithm; QSAR problem;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Aimed at the rough set theory cannot be directly applied to deal with continuous attributes, a rough set based on modified ChiMerge algorithm is presented. The basic concepts of the rough set theory and the modified ChiMerge algorithm are introduced and adequately illustrated firstly. The modified ChiMerge algorithm presents a stop criterion without needing experience compared to ChiMerge algorithm. The additional information can be eliminated and the rules can be extracted directly from data based on rough set theory after continuous values are discretized by modified ChiMerge algorithm. Finally the rough set theory based on modified ChiMerge algorithm is applied to a QSAR (quantitative structure activity relationships) problem, the results show that the algorithm is a useful tool for the analysis of continuous, inexact, uncertain, or vague data.

引用

页码：1004 / 1008

页数：5

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