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- W2348696341 abstract "The general model and the existing technology of text categorization system are analyzed.With application of the kernel principal component analysis(KPCA) for the characteristical dimension-reduction,a text classification algorithm based on a sample center radiate basis function(RBF) neural network,is proposed,the core idea of clustering algorithm introduced,and fairly slow convergence of the back-propagation(BP) neural network classification algorithm improved.Experimental results show that,compared with BP network,RBF network has higher speed and stronger nonlinear mapping capacity,including better classification effectiveness in convergence speed and accuracy." @default.
- W2348696341 created "2016-06-24" @default.
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- W2348696341 date "2011-01-01" @default.
- W2348696341 modified "2023-09-26" @default.
- W2348696341 title "An Improved RBF Algorithm for Text Classification" @default.
- W2348696341 hasPublicationYear "2011" @default.
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