GEPCLASS: A Classification Rule Discovery Tool Using Gene Expression Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @InProceedings{conf/adma/WeinertL06,
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title = "{GEPCLASS}: {A} Classification Rule Discovery Tool
Using Gene Expression Programming",
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author = "Wagner R. Weinert and Heitor S. Lopes",
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booktitle = "Advanced Data Mining and Applications, Proceedings of
the Second International Conference, {ADMA}",
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year = "2006",
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editor = "Xue Li and Osmar R. Za{\"i}ane and Zhanhuai Li",
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volume = "4093",
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series = "Lecture Notes in Computer Science",
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pages = "871--880",
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address = "Xi'an, China",
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month = aug # " 14-16",
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publisher = "Springer",
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bibdate = "2006-08-21",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/adma/adma2006.html#WeinertL06",
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keywords = "genetic algorithms, genetic programming, Gene
Expression Programming",
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ISBN = "3-540-37025-0",
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DOI = "doi:10.1007/11811305_95",
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abstract = "This work describes the use of a recently proposed
technique gene expression programming for knowledge
discovery in the data mining task of data
classification. We propose a new method for rule
encoding and genetic operators that preserve rule
integrity, and implemented a system, named GEPCLASS.
Due to its encoding scheme, the system allows the
automatic discovery of flexible rules, better fitted to
data. The performance of GEPCLASS was compared with two
genetic programming systems and with C4.5, over four
data sets in a five-fold cross-validation procedure.
The predictive accuracy for the methods compared were
similar, but the computational effort needed by
GEPCLASS was significantly smaller than the other.
GEPCLASS was able to find simple and accurate rules as
it can handle continuous and categorical attributes.",
- }
Genetic Programming entries for
Wagner R Weinert
Heitor Silverio Lopes
Citations