It is easy to show that, after appropriate scaling of the predictor matrix X,
Fisher's Linear Discriminant Analysis is equivalent to Discriminant Analysis
in the space of the fitted values from the linear regression of the
nlearn x K indicator matrix of the class labels on X.
This gives rise to 'nonlinear discrimant analysis' methods that expand
X in a suitable, more flexible basis. In order to avoid overfitting,
penalization is used. In the implemented version, the linear model is replaced
by a generalized additive one, using the package mgcv.
flexdaCMA.