A Large-Scale Data Classifying Approach Based on GP

Created by W.Langdon from gp-bibliography.bib Revision:1.7630

@InProceedings{Wang:2010:IEEC,

• author = "Sichun Wang and Yanhui Wu",
• title = "A Large-Scale Data Classifying Approach Based on GP",
• booktitle = "2nd International Symposium on Information Engineering and Electronic Commerce (IEEC 2010)",
• year = "2010",
• month = "23-25 " # jul,
• abstract = "The method that the utility of genetic programming (GP) is used to create and use ensembles in data mining is demonstrated in the paper . Given its representational power in the model of complex non-linearities in the data, GP is seen to be effective at learning diverse patterns in the data. With different models capturing varied data relationships, GP models are ideally suited for combination in ensembles. Experimental results show that different GP models are dissimilar both in terms of the functional form as well as with respect to the variables defining the models.",
• keywords = "genetic algorithms, genetic programming, data mining, large scale data classifying approach, data mining, pattern classification",
• DOI = "doi:10.1109/IEEC.2010.5533265",
• notes = "Eng. Manage. Inst., Hunan Univ. of Commerce, Changsha, China Also known as \cite{5533265}",

}

Genetic Programming entries for Sichun Wang Yanhui Wu

Citations