I have a Regression problem solved with both Deep Feedforward NN (in keras) and Random Forest (sklearn). The results are pretty good. Now I would like to know if I can change the importance of only one feature (among the 41) so that the algorithms would learn better the relation between such feature and the output proving a way to be able to generalize even in case such feature change it parameter ranges.
is it possible in keras and sklearn? and also could it make sense?
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