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Tran et al., 2019 - Google Patents

Principal component analysis in an asymmetric norm

Tran et al., 2019

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Document ID
12798608683136084052
Author
Tran N
Burdejová P
Ospienko M
Härdle W
Publication year
Publication venue
Journal of Multivariate Analysis

External Links

Snippet

Principal component analysis (PCA) is a widely used dimension reduction tool in high- dimensional data analysis. In risk quantification in finance, climatology and many other applications, however, the interest lies in capturing the tail variations rather than variation …
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    • G06K9/6232—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247—Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
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