Undiagnosed samples aided rough set feature selection for medical data

@article{Guan2012UndiagnosedSA,
  title={Undiagnosed samples aided rough set feature selection for medical data},
  author={Donghai Guan and Weiwei Yuan and Zilong Jin and Sungyoung Lee},
  journal={2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing},
  year={2012},
  pages={639-644}
}
Medical data often consists of a large number of disease markers. For medical data analysis, some disease markers are not helpful and sometimes even have negative effects. Therefore, applying feature selection is necessary as it can remove those unimportant disease markers. Among many feature selection methods, rough set based feature selection (RSFS) has been widely used. Unlike other methods, RSFS is completely data-driven. It does not require any other information like probability… CONTINUE READING

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