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Kernel Fisher discriminant functions - a concise and rigorous introduction
2007
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In the article the application of kernel functions -the so-called »kernel trick«in the context of Fisher's approach to linear discriminant analysis is described for data sets subdivided into two groups and having real attributes. The relevant facts about functional Hilbert spaces and kernel functions including their proofs are presented. The approximative algorithm published in [Mik3] to compute a discriminant function given the data and a kernel function is briefly reviewed. As an illustration
doi:10.24406/publica-fhg-293763
fatcat:ejeb3glxinetrcf5i4gly6jfn4