このエントリーをはてなブックマークに追加
ID 28459
file
A1207.pdf 338 KB
creator
Hara, Akira
Tanaka, Haruko
Ichimura, Takumi
Takahama, Tetsuyuki
NDC
Technology. Engineering
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.
journal title
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
start page
290
end page
295
date of issued
2009-11
publisher
IEEE SMC Hiroshima Chapter
issn
1883-3977
language
eng
nii type
Conference Paper
HU type
Conference Papers
DCMI type
text
format
application/pdf
text version
publisher
rights
(c) Copyright by IEEE SMC Hiroshima Chapter.
relation url
department
Graduate School of Engineering