Kernel Fisher Discriminant Analysis (KFDA)

Kernel Fisher Discriminant Analysis (KFDA) - A nonlinear extension of Fisher Discriminant Analysis where training samples are first mapped to a high-dimensional feature space F using nonlinear mapping φ, then standard Fisher Discriminant Analysis is performed in this kernel-induced space.