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Schematics of the transformations used in Fisher Discriminant Analysis (FDA) and Kernel Fisher Discriminant Analysis (KFDA): (a) In FDA, the dot product of vector w with data sample x is calculated to obtain the projected value t; (b) KFDA first maps each sample x to a higher-dimensional space f according to the nonlinear transformation φ(x). The dot product of w with f (rather than with x) is then calculated to obtain the projection t.
