A Large-Scale Data Classifying Approach Based on GP
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Wang:2010:IEEC,
-
author = "Sichun Wang and Yanhui Wu",
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title = "A Large-Scale Data Classifying Approach Based on GP",
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booktitle = "2nd International Symposium on Information Engineering
and Electronic Commerce (IEEC 2010)",
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year = "2010",
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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.",
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keywords = "genetic algorithms, genetic programming, data mining,
large scale data classifying approach, data mining,
pattern classification",
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DOI = "doi:10.1109/IEEC.2010.5533265",
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notes = "Eng. Manage. Inst., Hunan Univ. of Commerce, Changsha,
China Also known as \cite{5533265}",
- }
Genetic Programming entries for
Sichun Wang
Yanhui Wu
Citations