A Genetic Programming-Based Learning Algorithms for Pruning Cost-Sensitive Classifiers

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@Article{journals/ijcia/NikdelB12,
  author =       "Zahra Nikdel and Hamid Beigy",
  title =        "A Genetic Programming-Based Learning Algorithms for
                 Pruning Cost-Sensitive Classifiers",
  journal =      "International Journal of Computational Intelligence
                 and Applications",
  year =         "2012",
  volume =       "11",
  number =       "2",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming, Evolutionary
                 algorithms, decision tree, cost-sensitive
                 classification, machine learning",
  bibdate =      "2012-10-18",
  bibsource =    "DBLP,
                 http://dblp.uni-trier.de/db/journals/ijcia/ijcia11.html#NikdelB12",
  DOI =          "doi:10.1142/S1469026812500113",
  abstract =     "In this paper, we introduce a new hybrid learning
                 algorithm, called DTGP, to construct cost-sensitive
                 classifiers. This algorithm uses a decision tree as its
                 basic classifier and the constructed decision tree will
                 be pruned by a genetic programming algorithm using a
                 fitness function that is sensitive to misclassification
                 costs. The proposed learning algorithm has been
                 examined through six cost-sensitive problems. The
                 experimental results show that the proposed learning
                 algorithm outperforms in comparison to some other known
                 learning algorithms like C4.5 or naive Bayesian.",
}

Genetic Programming entries for Zahra Nikdel Hamid Beigy

Citations