Evolving Classification Rules by Unconstrained Gene Expression Programming

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@InProceedings{Zhang:2009:ISA,

• 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 problems.",
• 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

Citations