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.
Publication Year: 2003
Publication Date: 2003-01-20
Language: en
Type: article
Indexed In: ['crossref']
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Cited By Count: 2606
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