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ID 19717
Eprint ID
19717
FullText URL
Author
Hara Akira
Tanaka Haruko
Ichimura Takumi
Takahama Tetsuyuki
Abstract
When Genetic Programming (GP) is applied to rule extraction from databases, the attributes of the data are often used for the terminal symbols. However, in the case of the database with a large number of attributes, the search space becomes vast because the size of the terminal set increases. As a result, the search performance declines. For improving the search performance, we propose new methods for dealing with the large-scale terminal set. In the methods, the terminal symbols are clustered based on the similarities of the attributes. In the beginning of search, by reducing the number of terminal symbols, the rough and rapid search is performed. In the latter stage of search, by using the original attributes for terminal symbols, the local search is performed. By comparison with the conventional GP, the proposed methods showed the faster evolutional speed and extracted more accurate classification rules.
Published Date
2009-11-12
Publication Title
Proceedings : Fifth International Workshop on Computational Intelligence & Applications
Volume
volume2009
Issue
issue1
Publisher
IEEE SMC Hiroshima Chapter
Start Page
290
End Page
295
ISSN
1883-3977
NCID
BB00577064
Content Type
Conference Paper
language
英語
Copyright Holders
IEEE SMC Hiroshima Chapter
Event Title
5th International Workshop on Computational Intelligence & Applications IEEE SMC Hiroshima Chapter : IWCIA 2009
Event Location
東広島市
Event Location Alternative
Higashi-Hiroshima City
File Version
publisher
Refereed
True
Eprints Journal Name
IWCIA