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- W62477 abstract "We focus on covariance criteria for flnding a suitable sub- space for regression in a reproducing kernel Hilbert space: kernel princi- pal component analysis, kernel partial least squares and kernel canonical correlation analysis, and we demonstrate how this flts within a more gen- eral context of subspace regression. For the kernel partial least squares case some variants are considered and the methods are illustrated and compared on a number of examples." @default.
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- W62477 date "2003-01-01" @default.
- W62477 modified "2023-09-25" @default.
- W62477 title "Kernel PLS variants for regression" @default.
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