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  Fisher discriminant analysis with kernels.

Mika, S., Rätsch, G., Weston, J., Schölkopf, B., & Müller, K.-R. (1999). Fisher discriminant analysis with kernels. In Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop (pp. 41-48). Piscataway, NJ, USA: IEEE.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-E75B-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0005-C160-4
Genre: Conference Paper

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 Creators:
Mika, S, Author
Rätsch, G, Author              
Weston, J, Author              
Schölkopf, B1, Author              
Müller, K-R, Author              
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1External Organizations, ou_persistent22              

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 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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 Dates: 1999-08
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: 812
DOI: 10.1109/NNSP.1999.788121
 Degree: -

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Title: 1999 IEEE Signal Processing Society Workshop
Place of Event: Madison, WI, USA
Start-/End Date: 1999-08-25

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Title: Neural Networks for Signal Processing IX: Proceedings of the 1999 IEEE Signal Processing Society Workshop
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: Piscataway, NJ, USA : IEEE
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 41 - 48 Identifier: ISBN: 0-7803-5673-X