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題名 A knowledge-acquisition strategy based on genetic programming
作者 Kuo, Chan-Sheng;Hong, T.-P.;Chen, C.-L.
郭展盛
貢獻者 資管系
關鍵詞 Classification (of information); Computer programming; Genetic algorithms; Genetic programming; Information technology; Separation; Technology; Technology transfer; Acquisition strategies; Breast cancers; Classification rules; Classification trees; Evolutionary processes; Genetic operators; International conferences; Knowledge creations; Knowledge evolution; Learning strategies; Sub trees; Three phases; Knowledge acquisition
日期 2007
上傳時間 13-Jul-2015 16:29:13 (UTC+8)
摘要 In this paper, we have modified our previous GP-based learning strategy to search for an appropriate classification tree. The proposed approach consists of three phases: knowledge creation, knowledge evolution, and knowledge output. One new genetic operator, separation, is designed in the proposed approach to remove contradiction, thus producing more accurate classification rules. A subtree pruning technique is also used to restrain the classification trees excessively expanding in the evolutionary process. Experimental results from diagnosis of breast cancers also show the feasibility of the proposed algorithm. © 2007 IEEE.
關聯 2007 International Conference on Convergence Information Technology, ICCIT 2007
2nd International Conference on Convergent Information Technology, ICCIT 07,21 November 2007 through 23 November 2007,Gyongju
資料類型 conference
DOI http://dx.doi.org/10.1109/ICCIT.2007.4420263
dc.contributor 資管系
dc.creator (作者) Kuo, Chan-Sheng;Hong, T.-P.;Chen, C.-L.
dc.creator (作者) 郭展盛zh_TW
dc.date (日期) 2007
dc.date.accessioned 13-Jul-2015 16:29:13 (UTC+8)-
dc.date.available 13-Jul-2015 16:29:13 (UTC+8)-
dc.date.issued (上傳時間) 13-Jul-2015 16:29:13 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76518-
dc.description.abstract (摘要) In this paper, we have modified our previous GP-based learning strategy to search for an appropriate classification tree. The proposed approach consists of three phases: knowledge creation, knowledge evolution, and knowledge output. One new genetic operator, separation, is designed in the proposed approach to remove contradiction, thus producing more accurate classification rules. A subtree pruning technique is also used to restrain the classification trees excessively expanding in the evolutionary process. Experimental results from diagnosis of breast cancers also show the feasibility of the proposed algorithm. © 2007 IEEE.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) 2007 International Conference on Convergence Information Technology, ICCIT 2007
dc.relation (關聯) 2nd International Conference on Convergent Information Technology, ICCIT 07,21 November 2007 through 23 November 2007,Gyongju
dc.subject (關鍵詞) Classification (of information); Computer programming; Genetic algorithms; Genetic programming; Information technology; Separation; Technology; Technology transfer; Acquisition strategies; Breast cancers; Classification rules; Classification trees; Evolutionary processes; Genetic operators; International conferences; Knowledge creations; Knowledge evolution; Learning strategies; Sub trees; Three phases; Knowledge acquisition
dc.title (題名) A knowledge-acquisition strategy based on genetic programming
dc.type (資料類型) conferenceen
dc.identifier.doi (DOI) 10.1109/ICCIT.2007.4420263
dc.doi.uri (DOI) http://dx.doi.org/10.1109/ICCIT.2007.4420263