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Handling missing values in support vector machine classifiers

โœ Scribed by K. Pelckmans; J. De Brabanter; J.A.K. Suykens; B. De Moor


Publisher
Elsevier Science
Year
2005
Tongue
English
Weight
369 KB
Volume
18
Category
Article
ISSN
0893-6080

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We propose a method of modifying a kernel function to improve the performance of a support vector machine classifier. This is based on the structure of the Riemannian geometry induced by the kernel function. The idea is to enlarge the spatial resolution around the separating boundary surface, by a c