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Rough set based feature selection: A Review
2013
The 5th Conference on Information and Knowledge Technology
Feature selection aims to determine a minimal feature subset from a problem domain while retaining a suitably high accuracy in representing the original features. Rough set theory (RST) has been used as such a tool with much success. RST enables the discovery of data dependencies and the reduction of the number of attributes contained in a dataset using the data alone, requiring no additional information. This chapter describes the fundamental ideas behind RST-based approaches and reviews
doi:10.1109/ikt.2013.6620083
fatcat:pfkzxaaymjemroxv7hdkmjti5e