G3P-MI: A genetic programming algorithm for multiple instance learning

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@Article{Zafra20104496,
  author =       "Amelia Zafra and Sebastian Ventura",
  title =        "{G3P-MI:} A genetic programming algorithm for multiple
                 instance learning",
  journal =      "Information Sciences",
  volume =       "180",
  number =       "23",
  pages =        "4496--4513",
  year =         "2010",
  ISSN =         "0020-0255",
  DOI =          "doi:10.1016/j.ins.2010.07.031",
  URL =          "http://www.sciencedirect.com/science/article/B6V0C-50S2RDP-1/2/4591b7540f8c35538e14824742bb8343",
  keywords =     "genetic algorithms, genetic programming, Multiple
                 instance learning, Rule learning",
  abstract =     "This paper introduces a new Grammar-Guided Genetic
                 Programming algorithm for resolving multi-instance
                 learning problems. This algorithm, called G3P-MI, is
                 evaluated and compared to other multi-instance
                 classification techniques in different application
                 domains. Computational experiments show that the G3P-MI
                 often obtains consistently better results than other
                 algorithms in terms of accuracy, sensitivity and
                 specificity. Moreover, it makes the knowledge discovery
                 process clearer and more comprehensible, by expressing
                 information in the form of IF-THEN rules. Our results
                 confirm that evolutionary algorithms are very
                 appropriate for dealing with multi-instance learning
                 problems.",
}

Genetic Programming entries for Amelia Zafra Gomez Sebastian Ventura

Citations