Bias and stability of single variable classifiers for feature ranking and selection

Abstract

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings… (More)
DOI: 10.1016/j.eswa.2014.05.007

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Cite this paper

@article{Fakhraei2014BiasAS, title={Bias and stability of single variable classifiers for feature ranking and selection}, author={Shobeir Fakhraei and Hamid Soltanian-Zadeh and Farshad Fotouhi}, journal={Expert systems with applications}, year={2014}, volume={14 15}, pages={6945-6958} }