So I am trying to use RF recursive feature elimination to extract the most predictive features from my data-set. I've gotten the code to run fine and it gives me a nice table of rankings. However, when I try re-running it it gives me a whole other set of most predictive features than it did the first time. I'm at a loss here guys. Why could this be?
I've done this both with K-fold cross validation and without and get the same problem.
My variables are ordinal so I scale them with MinMaxScaler, which should be correct?
I've tried both using a train test split with the same random seed and without still I keep getting different features each time I run it.
So essentially its all random and meaningless. Am I missing something here? Or am I doing something wrong?
P.S I don't know if I should post my code or not. If so let me know and I'll edit it in. But the code seems fine everything runs I just feel Im missing some step or something that I am doing wrong.