Data mining with a parallel rule induction system based on gene expression programming

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@Article{Weinert:2015:IJICA,
  author =       "Wagner Rodrigo Weinert and Heitor Silverio Lopes",
  title =        "Data mining with a parallel rule induction system
                 based on gene expression programming",
  journal =      "International Journal of Innovative Computing and
                 Applications",
  publisher =    "Inderscience Publishers",
  year =         "2015",
  month =        mar # "~21",
  volume =       "3",
  number =       "3",
  pages =        "136--143",
  keywords =     "genetic algorithms, genetic programming, evolutionary
                 computation, gene expression programming, GEP, data
                 mining, parallel rule induction, data classification,
                 bioinformatics",
  bibsource =    "OAI-PMH server at www.inderscience.com",
  ISSN =         "1751-6498",
  URL =          "http://www.inderscience.com/link.php?id=41914",
  DOI =          "doi:10.1504/IJICA.2011.041914",
  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

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