Function Sequence Genetic Programming for pattern classification

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Shixian Wang and Qingjie Zhao and Yuehui Chen and 
                 Peng Wu",
  title =        "Function Sequence Genetic Programming for pattern
  booktitle =    "Seventh International Conference on Natural
                 Computation (ICNC 2011)",
  year =         "2011",
  month =        "26-28 " # jul,
  volume =       "2",
  pages =        "1092--1096",
  address =      "Shanghai",
  size =         "5 pages",
  abstract =     "Pattern classification is one of the most researched
                 problems in Artificial Intelligence. Genetic
                 Programming (GP) has been used to construct classifiers
                 by many researchers. Function Sequence Genetic
                 Programming (FSGP) is a new variant of GP, base on
                 which constructing classifier has not been investigated
                 now. This paper explores the application of FSGP to
                 pattern classification. Base on FSGP, binary classifier
                 and multi-classifier are constructed. Experiments on
                 four well-known data sets are made to demonstrate the
                 classification performance of FSGP.",
  keywords =     "genetic algorithms, genetic programming, FSGP, GP,
                 artificial intelligence, classifier construction,
                 function sequence genetic programming, pattern
                 classification, artificial intelligence, pattern
  DOI =          "doi:10.1109/ICNC.2011.6022170",
  ISSN =         "2157-9555",
  notes =        "WBCD, Pima, Iris, Wine (UCI)

                 Also known as \cite{6022170}",

Genetic Programming entries for Shixian Wang Qingjie Zhao Yuehui Chen Peng Wu