DocumentCode :
428748
Title :
An incremental rule extracting algorithm based on Pawlak reduction
Author :
Yong, Liu ; Congfu, Xu ; Yunhe, Pan
Author_Institution :
Inst. of Artificial Intelligence, Zhejiang Univ., China
Volume :
6
fYear :
2004
fDate :
10-13 Oct. 2004
Firstpage :
5964
Abstract :
Although the rough set theory first introduced by Z. Pawlak in 1982, is a kind of very useful mathematical tools to deal with vagueness, uncertainty, and imprecision information, it is relatively difficult to apply it to the analysis of incremental data sets. In this paper, a novel rule-extracting algorithm from incremental data sets based on the Pawlak reduction (also called independence reduction) is proposed. The main idea, description, analysis, and proof about this algorithm are discussed in details. Finally, an example is presented to illustrate the main characteristics of this new incremental algorithm.
Keywords :
data mining; knowledge based systems; rough set theory; Pawlak reduction; incremental rule extracting algorithm; independence reduction; rough set theory; rule-extracting algorithm; Artificial intelligence; Data analysis; Data mining; Databases; Decision support systems; Information analysis; Knowledge acquisition; Laboratories; Machine learning; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 2004 IEEE International Conference on
ISSN :
1062-922X
Print_ISBN :
0-7803-8566-7
Type :
conf
DOI :
10.1109/ICSMC.2004.1401149
Filename :
1401149
Link To Document :
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