Linear discriminant analysis

LDA assumes class-conditional Gaussian distributions with a shared covariance matrix, producing affine log odds.

Kernel linear discriminant analysis performs regularized linear discriminant analysis in a Reproducing-kernel Hilbert space, using kernel evaluations to obtain nonlinear decision boundaries in the original input space.