• Corpus ID: 11338479

Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance

@article{Wang2013ConvexHM,
  title={Convex Hull-Based Multi-objective Genetic Programming for Maximizing ROC Performance},
  author={Pu Wang and M. Emmerich and Rui Li and Ke Tang and Thomas B{\"a}ck and Xin Yao},
  journal={ArXiv},
  year={2013},
  volume={abs/1303.3145}
}
ROC is usually used to analyze the performance of classifiers in data mining. ROC convex hull (ROCCH) is the least convex major-ant (LCM) of the empirical ROC curve, and covers potential optima for the given set of classifiers. Generally, ROC performance maximization could be considered to maximize the ROCCH, which also means to maximize the true positive rate (tpr) and minimize the false positive rate (fpr) for each classifier in the ROC space. However, tpr and fpr are conflicting with each… 
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