Feature Selection For Datasets With Imbalanced Class Distributions

Publisher:
World Scientific Publ Co Pte Ltd
Publication Type:
Journal Article
Citation:
International Journal Of Software Engineering And Knowledge Engineering, 2010, 20 (2), pp. 113 - 137
Issue Date:
2010-01
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Feature selection for supervised learning concerns the problem of selecting a number of important features (w.r.t. the class labels) for the purposes of training accurate prediction models. Traditional feature selection methods, however, fail to take the
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