DocumentCode :
786022
Title :
A constraint-based genetic algorithm approach for mining classification rules
Author :
Chiu, Chaochang ; Hsu, Pei-Lun
Author_Institution :
Dept. of Inf. Manage., Yuan Ze Univ., Taiwan, Taiwan
Volume :
35
Issue :
2
fYear :
2005
fDate :
5/1/2005 12:00:00 AM
Firstpage :
205
Lastpage :
220
Abstract :
Data mining is an information extraction process that aims to discover valuable knowledge in databases. Existing genetic algorithms (GAs) designed for rule induction evaluates the rules as a whole via a fitness function. Major drawbacks of GAs for rule induction include computation inefficiency, accuracy and rule expressiveness. In this paper, we propose a constraint-based genetic algorithm (CBGA) approach to reveal more accurate and significant classification rules. This approach allows constraints to be specified as relationships among attributes according to predefined requirements, user´s preferences, or partial knowledge in the form of a constraint network. The constraint-based reasoning is employed to produce valid chromosomes using constraint propagation to ensure the genes to comply with the predefined constraint network. The proposed approach is compared with a regular GA and C4.5 using two UCI repository data sets. Better classification accurate rates from CBGA are demonstrated.
Keywords :
constraint handling; constraint theory; data mining; genetic algorithms; inference mechanisms; knowledge based systems; UCI repository data sets; chromosomes; constraint propagation; constraint satisfaction problems; constraint-based genetic algorithm approach; constraint-based reasoning; data mining; information extraction process; predefined constraint network; rules induction; Algorithm design and analysis; Biological cells; Chaos; Data analysis; Data mining; Databases; Decision making; Genetic algorithms; Learning systems; Statistics; Constraint-based reasoning; constraint satisfaction problems; data mining; genetic algorithms; rules induction;
fLanguage :
English
Journal_Title :
Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on
Publisher :
ieee
ISSN :
1094-6977
Type :
jour
DOI :
10.1109/TSMCC.2004.841919
Filename :
1424195
Link To Document :
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