DocumentCode :
1592495
Title :
A Method for Finding Implicating Rules Based on the Genetic Algorithm
Author :
Jun, Zhou ; Shu-You, Li ; Hong-Yan, Mei ; Hai-Xia, Liu
Author_Institution :
Liaoning Univ. of Technol., Dalian
Volume :
3
fYear :
2007
Firstpage :
400
Lastpage :
405
Abstract :
In information system, some rules have implicating relations (called implicating rules), but some rules have not. An approach of finding implicating rules based on the genetic algorithm is proposed. Some properties of independence and correlation of descriptions are discussed. It can obtain directly the implicating rules (including the positive and negative rules) with the correlation of two descriptions according to strength of implication defined in this paper. At the same time, an algorithm for finding optimized rules based on genetic algorithm is presented. By it, the problem of efficiency of finding rules is solved. At last, the efficiency and practicability of the method are illustrated by the experiment results.
Keywords :
data mining; genetic algorithms; rough set theory; data mining; genetic algorithm; implicating rules; information system; rough set theory; Artificial intelligence; Cognitive science; Computer science; Data analysis; Data mining; Genetic algorithms; Information systems; Learning systems; Machine learning; Set theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Natural Computation, 2007. ICNC 2007. Third International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2875-5
Type :
conf
DOI :
10.1109/ICNC.2007.61
Filename :
4344545
Link To Document :
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