An efficient accelerator for attribute reduction from incomplete data in rough set framework

Feature selection (attribute reduction) from large-scale incomplete data is a challenging problem in areas such as pattern recognition, machine learning and data mining. In rough set theory, feature selection from incomplete data aims to retain the discriminatory power of original features. To addre...

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Veröffentlicht in:Pattern recognition 2011-08, Vol.44 (8), p.1658-1670
Hauptverfasser: Qian, Yuhua, Liang, Jiye, Pedrycz, Witold, Dang, Chuangyin
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Sprache:eng
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