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- W2372187941 abstract "This paper points out the drawbacks of the general principal component analysis(PCA) when it is used to solve nonlinear problem firstly. The kernel principal component analysis(KPCA) and its drawbacks on computing are explained secondly. KPCA based on clustering is introduced in the end. The research result shows that the KPCA based on clustering has excellent performance of feature extraction." @default.
- W2372187941 created "2016-06-24" @default.
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- W2372187941 date "2005-01-01" @default.
- W2372187941 modified "2023-10-03" @default.
- W2372187941 title "The Application of Feature Extraction on Using Kernel Principal Component Analysis Based on Clustering" @default.
- W2372187941 hasPublicationYear "2005" @default.
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