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

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  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,
  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