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Rule extraction by successive regularization
http://hdl.handle.net/10228/2413
http://hdl.handle.net/10228/24138cdf7b3b-af2c-4087-a43e-50977719f70e
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successrev3.pdf (269.4 kB)
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successrev3.ps (517.9 kB)
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Item type | 学術雑誌論文 = Journal Article(1) | |||||
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公開日 | 2009-07-13 | |||||
資源タイプ | ||||||
資源タイプ識別子 | http://purl.org/coar/resource_type/c_6501 | |||||
資源タイプ | journal article | |||||
タイトル | ||||||
タイトル | Rule extraction by successive regularization | |||||
言語 | ||||||
言語 | eng | |||||
著者 |
石川, 眞澄
× 石川, 眞澄 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | Knowledge acquisition is, needless to say, important, because it is a key to the solution to one of the bottlenecks in artificial intelligence. Recently, knowledge acquisition using neural networks, called rule extraction, is attracting wide attention because of its computational simplicity and ability to generalize. Proposed in this paper is a novel approach to rule extraction named successive regularization. It generates a small number of dominant rules at an earlier stage and less dominant rules or exceptions at later stages. It has various advantages such as robustness of computation, better understanding, and similarity to child development. It is applied to the classification of mushrooms, the recognition of promoters in DNA sequences and the classification of irises. Empirical results indicate superior performance of rule extraction in terms of the number and the size of rules for explaining data. | |||||
書誌情報 |
Neural Networks 巻 13, 号 10, p. 1171-1183, 発行日 2000-12-01 |
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出版社 | ||||||
出版者 | Elsevier | |||||
DOI | ||||||
関連タイプ | isVersionOf | |||||
識別子タイプ | DOI | |||||
関連識別子 | https://doi.org/10.1016/S0893-6080(00)00072-1 | |||||
ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 0893-6080 | |||||
著作権関連情報 | ||||||
権利情報 | Copyright (c) 2000 Elsevier Science Ltd. | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Rule extraction | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Successive regularization | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Rules and exceptions | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Structural learning | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Forgetting | |||||
キーワード | ||||||
主題Scheme | Other | |||||
主題 | Classification | |||||
出版タイプ | ||||||
出版タイプ | AM | |||||
出版タイプResource | http://purl.org/coar/version/c_ab4af688f83e57aa | |||||
査読の有無 | ||||||
値 | yes | |||||
研究者情報 | ||||||
https://hyokadb02.jimu.kyutech.ac.jp/html/3_ja.html | ||||||
連携ID | ||||||
1 | ||||||
業績ID | ||||||
FC3954B57D32037F49256E8C0018A088 | ||||||
資料タイプ | ||||||
内容記述タイプ | Other | |||||
内容記述 | Journal Article | |||||
著者別名 | ||||||
姓名 | Ishikawa, Masumi | |||||
言語 | en | |||||
姓名 | 石川, 眞澄 | |||||
言語 | ja | |||||
姓名 | イシカワ, マスミ | |||||
言語 | ja-Kana | |||||
著者所属 | ||||||
Department of Brain Science and Engineering, Graduate School of Life Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka, Fukuoka 820-8502, Japan | ||||||
情報源 | ||||||
識別子タイプ | URI | |||||
関連識別子 | http://www.sciencedirect.com/science/journal/08936080 | |||||
関連名称 | http://www.sciencedirect.com/science/journal/08936080 |