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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 ...