Classifier design with feature selection and feature extraction using layered genetic programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{Lin:2007:ESA,

• author = "Jung-Yi Lin and Hao-Ren Ke and Been-Chian Chien and Wei-Pang Yang",
• title = "Classifier design with feature selection and feature extraction using layered genetic programming",
• journal = "Expert Systems with Applications",
• year = "2007",
• volume = "34",
• number = "2",
• pages = "1384--1393",
• month = feb,
• keywords = "genetic algorithms, genetic programming, Feature generation, Feature selection, Pattern classification, Multi-population genetic programming, Layered genetic programming",
• DOI = "doi:10.1016/j.eswa.2007.01.006",
• abstract = "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.",
• notes = "a Department of Computer Science, National Chiao Tung University, 1001 Ta Hsueh Road, HsinChu 300, Taiwan

  b Library and Institute of Information Management, National Chiao Tung University, Taiwan

  c Department of Computer Science and Information Engineering, National University of Tainan, Taiwan

  d Department of Information Management, National Dong Hwa University, Taiwan",

}

Genetic Programming entries for Mick Jung-Yi Lin Hao-Ren Ke Been-Chian Chien Wei-Pang Yang

Citations