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• W2007837309 abstract "In this paper, we propose a novel method to weight features for their relevance to the given classification problem. The weight of a feature is computed by its Localized Generalization Error model (L-GEM). Then, a Radial Basis Function Neural Network (RBFNN) is trained by those weighted features. Experimental results on image classification problem show that the proposed method is efficient and effective in comparison to current methods." @default.
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• W2007837309 date "2010-07-01" @default.
• W2007837309 modified "2023-09-28" @default.
• W2007837309 title "Feature weighting based on L-GEM" @default.
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• W2007837309 doi "https://doi.org/10.1109/icmlc.2010.5581062" @default.
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