Mika, S.
Ratsch, G.
Weston, J.
Scholkopf, B.
Mullers, K.R.
GMD FIRST, Berlin;
This paper appears in: Neural Networks for Signal Processing IX, 1999. Proceedings of the 1999 IEEE Signal Processing Society Workshop
Publication Date: Aug 1999
On page(s): 41-48
Meeting Date: 08/23/1999 - 08/25/1999
Location: Madison, WI, USA
ISBN: 0-7803-5673-x
References Cited: 19
INSPEC Accession Number: 6497095
DOI: 10.1109/NNSP.1999.788121
Posted online: 2002-08-06 22:37:53.0
Abstract
A non-linear classification technique based on Fisher's
discriminant is proposed. The main ingredient is the kernel trick which
allows the efficient computation of 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
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