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- W2362829263 abstract "As a new kind of nonlinear dimensionality reduction method,manifold learning is capturing increasing interests of researchers.To understand manifold learning better,the principle is firstly introduced,and then its development history and different representations are summarized,finally several major method are introduced,whose basic thoughts,steps and advantages are pointed out respectively.By the experiments on Swiss-Roll,the selection of neighbors and noise effect are analyzed,the results shows:compared with traditional linear method,manifold learning can discover the intrinsic structure of the samples better.Finally the prospect of manifold learning was discussed for more developments." @default.
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- W2362829263 date "2012-01-01" @default.
- W2362829263 modified "2023-09-23" @default.
- W2362829263 title "Nonlinear Dimensionality Reduction Method Based on Manifold Learning" @default.
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