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- W20242457 abstract "AbstractThis paper introduces the use of GA with a novel fitness function to eliminate noisy and irrelevant features. Fitness function of GA is based on the Area Under the receiver operating characteristics Curve (AUC). The aim of this feature selection is to improve the performance of k-NN algorithm. Experimental results show that the proposed method can substantially improve the classification performance of k-NN algorithm in comparison with the other classifiers (in the realm of feature selection) such as C4.5, SVM, and Relief. Furthermore,this method is able to eliminate the noisy irrelevant features from the synthetic data sets.KeywordsAUCGenetic algorithmFeature selectionNoisy feature elimination k-NN" @default.
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- W20242457 date "2012-01-01" @default.
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- W20242457 title "Improving Nearest Neighbor Classification by Elimination of Noisy Irrelevant Features" @default.
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