Feature selection using ROC curves on classification problems

@article{Serrano2010FeatureSU,
  title={Feature selection using ROC curves on classification problems},
  author={Antonio J. Serrano and Emilio Soria-Olivas and Jos{\'e} David Mart{\'i}n-Guerrero and Jos{\'e} Rafael Magdalena Benedito and Juan G{\'o}mez},
  journal={The 2010 International Joint Conference on Neural Networks (IJCNN)},
  year={2010},
  pages={1-6}
}
Feature Selection (FS) is one of the key stages in classification problems. This paper proposes the use of the area under Receiver Operator Characteristic curves to measure the individual importance of every input as well as a method to discover the variables that yield a statistically significant improvement in the discrimination power of the classification model. 
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