Data mining with a parallel rule induction system based on gene expression programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.8098
- @Article{Weinert:2015:IJICA,
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author = "Wagner Rodrigo Weinert and Heitor Silverio Lopes",
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title = "Data mining with a parallel rule induction system
based on gene expression programming",
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journal = "International Journal of Innovative Computing and
Applications",
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publisher = "Inderscience Publishers",
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year = "2015",
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month = mar # "~21",
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volume = "3",
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number = "3",
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pages = "136--143",
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keywords = "genetic algorithms, genetic programming, evolutionary
computation, gene expression programming, GEP, data
mining, parallel rule induction, data classification,
bioinformatics",
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bibsource = "OAI-PMH server at www.inderscience.com",
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ISSN = "1751-6498",
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URL = "http://www.inderscience.com/link.php?id=41914",
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DOI = "doi:10.1504/IJICA.2011.041914",
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abstract = "A parallel rule induction system based on gene
expression programming (GEP) is reported in this paper.
The system was developed for data classification. The
parallel processing environment was implemented on a
cluster using a message-passing interface. A
master-slave GEP was implemented according to the
Michigan approach for representing a solution for a
classification problem. A multiple master-slave system
(islands) was implemented in order to observe the
co-evolution effect. Experiments were done with ten
datasets, and algorithms were systematically compared
with C4.5. Results were analysed from the point of view
of a multi-objective problem, taking into account both
predictive accuracy and comprehensibility of induced
rules. Overall results indicate that the proposed
system achieves better predictive accuracy with shorter
rules, when compared with C4.5.",
- }
Genetic Programming entries for
Wagner R Weinert
Heitor Silverio Lopes
Citations