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ID 28459
本文ファイル
Thumnail A1207.pdf 338 KB
著者
Hara, Akira
Tanaka, Haruko
Ichimura, Takumi
Takahama, Tetsuyuki
NDC
技術・工学
抄録(英)
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.
掲載誌名
5th International Workshop on Computational Intelligence & Applications Proceedings : IWCIA 2009
開始ページ
290
終了ページ
295
出版年月日
2009-11
出版者
IEEE SMC Hiroshima Chapter
ISSN
1883-3977
言語
英語
NII資源タイプ
会議発表論文
広大資料タイプ
会議発表論文
DCMIタイプ
text
フォーマット
application/pdf
著者版フラグ
publisher
権利情報
(c) Copyright by IEEE SMC Hiroshima Chapter.
関連情報URL
部局名
工学研究科