Kernel Fisher discriminant functions – a concise and rigorous introduction
- 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 of the technique an artificial data set is analysed using the algorithm just mentioned.
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| Author: | H. Knaf |
|---|---|
| URN: | urn:nbn:de:hbz:386-kluedo-15393 |
| Series (Serial Number): | Berichte des Fraunhofer-Instituts für Techno- und Wirtschaftsmathematik (ITWM Report) (117) |
| Document Type: | Report |
| Language of publication: | English |
| Year of Completion: | 2007 |
| Year of first Publication: | 2007 |
| Publishing Institution: | Fraunhofer-Institut für Techno- und Wirtschaftsmathematik |
| Date of the Publication (Server): | 2008/05/28 |
| Tag: | discriminant analysis; functional Hilbert space; kernel function; reproducing kernel |
| Faculties / Organisational entities: | Fraunhofer (ITWM) |
| DDC-Cassification: | 5 Naturwissenschaften und Mathematik / 510 Mathematik |
| Licence (German): |  Standard gemäß KLUEDO-Leitlinien vor dem 27.05.2011 |