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