Features Selection based on Rough Membership and Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Chien:2006:ICSMC,

• author = "Been-Chian Chien and Jui-Hsiang Yang",
• title = "Features Selection based on Rough Membership and Genetic Programming",
• booktitle = "IEEE International Conference on Systems, Man and Cybernetics, ICSMC '06",
• year = "2006",
• volume = "5",
• pages = "4124--4129",
• address = "Taipei, Taiwan",
• month = "8-11 " # oct,
• publisher = "IEEE",
• keywords = "genetic algorithms, genetic programming",
• ISBN = "1-4244-0100-3",
• DOI = "doi:10.1109/ICSMC.2006.384780",
• abstract = "This paper discusses the feature selection problem upon supervised learning. A learning method based on rough sets and genetic programming is proposed to select significant features and classify numerical data. The proposed method uses rough membership to transform nominal data into numerical values, then selects important features and learns classification functions using genetic programming. We use several UCI data sets to show the performance of the proposed scheme and make comparisons with three different features selection approaches: distance measure, information measure and dependence measure. The results demonstrate that the proposed method is effective both in features selection and classification.",
• notes = "Member, IEEE, National University of Tainan, Tainan 700, Taiwan, R. O. C. Tel: +886-6-2606123 ext. 7707, fax:+886-6-2606125;",

}

Genetic Programming entries for Been-Chian Chien Jui-Hsiang Yang

Citations