Nonlinear Principal Component Analysis And Its Applications
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This book expounds the principle and related applications of nonlinear principal component analysis (PCA), which is useful method to analyze mixed measurement l
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The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering alg
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This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems relate
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Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and dev
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Principal components analysis (PCA) is a popular dimension reduction method and is applied to analyze quantitative data. For PCA to qualitative data, nonlinear
