An Improved Training Algorithm for Kernel Fisher Discriminants

Mika, S; Schölkopf, B; Smola, AJ

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An Improved Training Algorithm for Kernel Fisher Discriminants

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http://www.gatsby.ucl.ac.uk/aistats/aistats2001/files/mika187.pdf
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Mika, S., Schölkopf, B., & Smola, A. (2001). An Improved Training Algorithm for Kernel Fisher Discriminants. In T. Richardson, & T. Jaakkola (Eds.), 8th International Conference on Artificial Intelligence and Statistics (AISTATS 2001) (pp. 98-104). Society for Artificial Intelligence and Statistics.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-E30C-2

Abstract

We present a fast training algorithm for the kernel Fisher discriminant classifier. It uses a greedy approximation technique and has an empirical scaling behavior which improves upon the state of the art by more than an order of magnitude, thus rendering the kernel Fisher algorithm a viable option also for large datasets.