Fisher discriminant analysis with kernels

Sebastian Mika; Gunnar Ratsch; Jason Weston; Bernhard Scholkopf; Klaus Robert Muller

Fisher discriminant analysis with kernels

Sebastian Mika, Gunnar Ratsch, Jason Weston, Bernhard Scholkopf, Klaus Robert Muller

Research output: Contribution to conference › Paper › peer-review

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.

Original language	English
Pages	41-48
Number of pages	8
Publication status	Published - 1999
Externally published	Yes
Event	Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) - Madison, WI, USA Duration: 1999 Aug 23 → 1999 Aug 25

Other

Other	Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99)
City	Madison, WI, USA
Period	99/8/23 → 99/8/25

ASJC Scopus subject areas

Signal Processing
Software
Electrical and Electronic Engineering

Cite this

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title = "Fisher discriminant analysis with kernels",

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.",

author = "Sebastian Mika and Gunnar Ratsch and Jason Weston and Bernhard Scholkopf and Muller, {Klaus Robert}",

year = "1999",

language = "English",

pages = "41--48",

note = "Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99) ; Conference date: 23-08-1999 Through 25-08-1999",

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TY - CONF

T1 - Fisher discriminant analysis with kernels

AU - Mika, Sebastian

AU - Ratsch, Gunnar

AU - Weston, Jason

AU - Scholkopf, Bernhard

AU - Muller, Klaus Robert

PY - 1999

Y1 - 1999

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0033337021&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033337021&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0033337021

SP - 41

EP - 48

T2 - Proceedings of the 1999 9th IEEE Workshop on Neural Networks for Signal Processing (NNSP'99)

Y2 - 23 August 1999 through 25 August 1999

ER -

Fisher discriminant analysis with kernels

Abstract

Other

ASJC Scopus subject areas

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