I have a pretty specific question regarding the caret package however I still hope to finde help here.
I recently worked with the caret package and trained a multilayer perceptron with
method = 'mlp'.
I looked up the github page of Max Kuhn (developer of caret), and it says that you only need to tune one hyperparameter: the size (number of neurons in the hidden layer). Which is really convinient.
However it further states that caret for the training builds on the RSNNS Package (by Bergmeier). The mlp model implemented in this RSNNS package has additional tunable parameters over just the size hyperparameter (i.e. learnFunc,hiddenActFunc,Std_Backpropagation, maxit).
So I asked myself what values caret uses for those parameters? Default values or are those optmizied?