Approach to generating rules for expert systems using rough set theory

被引：0
|
作者：
Phuong, NH [1 ]
Phong, LL [1 ]
Santiprabhob, P [1 ]
De Baets, B [1 ]
机构：
[1] Assumption Univ, Fac Sci & Technol, Intelligent Syst Lab, Bangkok 10240, Thailand
来源：
JOINT 9TH IFSA WORLD CONGRESS AND 20TH NAFIPS INTERNATIONAL CONFERENCE, PROCEEDINGS, VOLS. 1-5 | 2001年
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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：
The problem of data mining and knowledge discovery as generating rules from databases becomes a great research interest of many researchers. There were many methods such as induction learning, ID3 etc developed. Recently, a new approach based on rough set theory has been proposed. Rough set theory has been proposed by Zdzislaw Pawlak in years 1980 to deal with inconsistent problems. Our work is to apply this theory in extracting rules from given medical databases. This results with a set of decision rules, which will be provided to one of our diagnostic systems as a part of its knowledge base.
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页码：877 / 882
页数：6
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