Fisher discriminant analysis with kernels
Published 20 January 2003
Mika Sirén, Gunnar Rätsch, Jason Weston, Bernhard Schölkopf, K.R. Mullers
Citations2,661
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TL;DR
A non-linear classification technique based on Fisher's discriminant which allows the efficient computation of Fisher discriminant in feature space and large scale simulations demonstrate the competitiveness of this approach.
Abstract
A non-linear classification technique based on Fisher's discriminant is proposed. Main ingredient is the kernel trick which allows to efficiently compute the linear Fisher discriminant in feature space. The linear classification in feature space corresponds to a powerful non-linear decision function in input space. Large scale simulations demonstrate the competitiveness of our approach.
Keywords
Computer ScienceMathematics
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