Classifier Ensembles Integration with Self-configuring Genetic Programming Algorithm

Created by W.Langdon from gp-bibliography.bib Revision:1.4216

  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 =          "",
  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

Genetic Programming entries for Maria Semenkina Eugene Semenkin