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Assessing the influence of observations on the generalization performance of the kernel Fisher discriminant classifier
(Stellenbosch : Stellenbosch University, 2008-12)
Kernel Fisher discriminant analysis (KFDA) is a kernel-based technique that can be used to classify observations of unknown origin into predefined groups. Basically, KFDA can be viewed as a non-linear extension of Fisher’s ...
Variable selection for kernel methods with application to binary classification
(Stellenbosch : University of Stellenbosch, 2008-03)
The problem of variable selection in binary kernel classification is addressed in this thesis. Kernel methods are fairly recent additions to the statistical toolbox, having originated approximately two decades ago in ...