Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm

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@InProceedings{conf/icannga/SemenkinaS13,
  author =       "Maria Semenkina and Eugene Semenkin",
  title =        "Classifier Ensembles Integration with Self-configuring
                 Genetic Programming Algorithm",
  booktitle =    "Proceedings 11th International Conference on Adaptive
                 and Natural Computing Algorithms, ICANNGA 2013",
  year =         "2013",
  editor =       "Marco Tomassini and Alberto Antonioni and 
                 Fabio Daolio and Pierre Buesser",
  volume =       "7824",
  series =       "Lecture Notes in Computer Science",
  pages =        "60--69",
  address =      "Lausanne, Switzerland",
  month =        apr # " 4-6",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming",
  isbn13 =       "978-3-642-37212-4",
  URL =          "http://dx.doi.org/10.1007/978-3-642-37213-1",
  DOI =          "doi:10.1007/978-3-642-37213-1_7",
  size =         "10 pages",
  abstract =     "Artificial neural networks and symbolic expression
                 based ensembles are used for solving classification
                 problems. Ensemble members and the ensembling method
                 are generated automatically with the self-configuring
                 genetic programming algorithm that does not need
                 preliminary adjusting. Performance of the approach is
                 demonstrated with real world problems. The proposed
                 approach demonstrates results competitive to known
                 techniques.",
}

Genetic Programming entries for Maria Semenkina Eugene Semenkin

Citations