Nonlinear Component Analysis as a Kernel Eigenvalue Problem
Published in Neural Computation • Jul 1, 1998
Authors:,,
Bernhard Schölkopf
Alexander Smola
Klaus-Robert Müller
Abstract
A new method for performing a nonlinear form of principal component analysis is proposed. By the use of integral operator kernel functions, one can efficiently compute principal components in high-dimensional feature spaces, related to input space by some nonlinear map—for instance, the space of all...
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