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ESANN
2003

Kernel PLS variants for regression

10 years 2 months ago
Kernel PLS variants for regression
Abstract. We focus on covariance criteria for finding a suitable subspace for regression in a reproducing kernel Hilbert space: kernel principal component analysis, kernel partial least squares and kernel canonical correlation analysis, and we demonstrate how this fits within a more general 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.
Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewall
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where ESANN
Authors Luc Hoegaerts, Johan A. K. Suykens, Joos Vandewalle, Bart De Moor
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