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The notions of explanation-radius and the local information based on the data distribution are proposed. The former measures the injective degree and the latter depicts the difference between the original data and the reduction data. Thereafter, through the experiments, the linear and nonlinear dimension-reduction is analyzed, included PCA (Principal(More)
The paper proposed the method of the local invariant projection for dealing with high-dimensional data sets. The method not only has the nature to maintain the geometry and topology structure of the data sets unchanged in the dimension reduction of the high-dimensional data, but the advantages of convenient and rapid calculation in the linear dimension(More)
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