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- W2365292518 abstract "Aiming at large computation and slow convergence speed of the traditional feature selection methods,a fast SVM-based feature selection method was proposed.A support vecor machine was employed as the classifier,and particle swarm optimization method was employed as the searching strategy.The proposed method reduced the iterations of training classifiers by taking advantage of the characteristics of linear and polynomial kernel functions,so that it could reduce the complexity of the calculation.Experimental results showed that the method accelerates feature selection in the case of no loss of the classification performances." @default.
- W2365292518 created "2016-06-24" @default.
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- W2365292518 date "2010-01-01" @default.
- W2365292518 modified "2023-09-28" @default.
- W2365292518 title "A fast SVM-based feature selection method" @default.
- W2365292518 hasPublicationYear "2010" @default.
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