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 |