Welcome to IEEE Xplore 2.0: Fisher discriminant analysis with kernels

Cart | Sitemap | Help

Abstract


	BROWSE	SEARCH	IEEE XPLORE GUIDE	SUPPORT

View TOC

Fisher discriminant analysis with kernels
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
Digital Object Identifier: 10.1109/NNSP.1999.788121
Current Version Published: 2002-08-06

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

Index Terms
Available to subscribers and IEEE members.

References
Available to subscribers and IEEE members.

Citing Documents
Available to subscribers and IEEE members.