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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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