標題: Classifier design with feature selection and feature extraction using layered genetic programming
作者: Lin, Jung-Yi
Ke, Hao-Ren
Chien, Been-Chian
Yang, Wei-Pang
資訊工程學系
Department of Computer Science
關鍵字: feature generation;feature selection;pattern classification;genetic programming;multi-population genetic programming;layered genetic programming
公開日期: 1-二月-2008
摘要: This paper proposes a novel method called FLGP to construct a classifier device of capability in feature selection and feature extraction. FLGP is developed with layered genetic programming that is a kind of the multiple-population genetic programming. Populations advance to an optimal discriminant function to divide data into two classes. Two methods of feature selection are proposed. New features extracted by certain layer are used to be the training set of next layer's populations. Experiments on several well-known datasets are made to demonstrate performance of FLGP. (C) 2007 Elsevier Ltd. All rights reserved.
URI: http://dx.doi.org/10.1016/j.eswa.2007.01.006
http://hdl.handle.net/11536/9716
ISSN: 0957-4174
DOI: 10.1016/j.eswa.2007.01.006
期刊: EXPERT SYSTEMS WITH APPLICATIONS
Volume: 34
Issue: 2
起始頁: 1384
結束頁: 1393
顯示於類別:期刊論文


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