Improving the Mann-Whitney statistical test for feature selection: An approach in breast cancer diagnosis on mammography

@article{Prez2015ImprovingTM,
  title={Improving the Mann-Whitney statistical test for feature selection: An approach in breast cancer diagnosis on mammography},
  author={Noel P{\'e}rez and Miguel {\'A}ngel Guevara-L{\'o}pez and Augusto Silva and Isabel Ramos},
  journal={Artificial intelligence in medicine},
  year={2015},
  volume={63 1},
  pages={
          19-31
        }
}
OBJECTIVE This work addresses the theoretical description and experimental evaluation of a new feature selection method (named uFilter). The uFilter improves the Mann-Whitney U-test for reducing dimensionality and ranking features in binary classification problems. Also, it presented a practical uFilter application on breast cancer computer-aided diagnosis (CADx). MATERIALS AND METHODS A total of 720 datasets (ranked subsets of features) were formed by the application of the chi-square (CHI2… CONTINUE READING

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