Context: I have a training dataset with 10000 features and i have selected the most important through a Random Forest. I used my subset dataset to train a Neuronal Net.
Problem: When i use the validation dataset should i just drop the variables from the RF subset dataset? Doesn't imply that the data came from the same distribution, so no need for a non-parametric approach?