I chose MRMR selection for the first selection and then forward
selection as further selection for my model. Now I want to justify my
choice.
So far, I would say MRMR is not expensive in compution
time and therefor good for a first selection (150 variables). And it is
better as other filter methods (also computional inexpensive methods) as
e.g select by weight by correlation /information gain
because it adresses the interferance of variables amongst each other.
What do you think of my reasoning? Is there an advantage of the MRMR algorithm I missed? Are there any recommondations where it is likely to use?