Evolving Classification Rules by Unconstrained Gene Expression Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Jianwei Zhang and Zhijian Wu and Jinglei Guo and 
                 Min Peng and Yingjiang Zhang and Chunzhi Wang",
  title =        "Evolving Classification Rules by Unconstrained Gene
                 Expression Programming",
  booktitle =    "International Workshop on Intelligent Systems and
                 Applications, ISA 2009",
  year =         "2009",
  month =        may,
  abstract =     "Unconstrained Gene Expression Programming (UGEP), a
                 new unconstrained linear encoded Gene Expression
                 Programming (GEP), is introduced and applied to solve
                 classification problems in this paper. Different from
                 GEP, both amount and length of the genes are
                 dynamically adjusted in the UGEP chromosome during the
                 evolution process. Experiment results indicate that
                 UGEP perform better than GEP in classification
  keywords =     "genetic algorithms, genetic programming, gene
                 expression programming, classification rules, data
                 mining, data mining",
  DOI =          "doi:10.1109/IWISA.2009.5072858",
  notes =        "Also known as \cite{5072858}",

Genetic Programming entries for Jianwei Zhang Zhijian Wu Jinglei Guo Min Peng Yingjiang Zhang Chunzhi Wang