Fisher discriminant analysis with kernels
2003pp. 41–48
Citations Over TimeTop 1% of 2003 papers
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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