Warianty tytułu
Języki publikacji
Abstrakty
Rough rule extraction refers to the rule induction method by using rough set theory. Although rough set theory is a powerful mathematical tool in dealing with vagueness and uncertainty in data sets, it is lack of effective rule extracting approach under complex conditions. This paper proposes several algorithms to perform rough rule extraction from data sets with different properties. Firstly, in order to obtain uncertainty rules from inconsistent data, we introduce the concept of confidence factor into the rule extracting process. Then, an improved incremental rule extracting algorithm is proposed based on the analysis of the incremental data categories. Finally, above algorithms are further extended to perform approximate rule extraction from huge data sets. Preliminary experiment results are encouraging.
Czasopismo
Rocznik
Tom
Strony
403-427
Opis fizyczny
bibliogr. 49 poz., wykr.
Twórcy
autor
autor
autor
autor
- State Key Lab. of Industrial Control Technology, Zhejiang University, 310027 Hangzhou, China yongliu@iipc.zju.edu.cn, yongliu@iipc.zju.edu.cn
Bibliografia
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- [48] Zhong, N., Dong, J., Ohsuga, S.: Using Rough Sets with Heuristics for Feature Selection., J. Intell. Inf. Syst, 16(3),2001,199-214.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS5-0015-0082