I am doing regression task - do I need to normalize (or scale) data for randomForest (R package)? And is it neccessary to scale also target values? And if - I want to use sc
Guess, what will happen in the following example? Imagine, you have 20 predictive features, 18 of them are in [0;10] range and the other 2 in [0;1,000,000] range (taken from a real-life example). Question1: what feature importances will Random Forest assign. Question2: what will happen to the feature importance after scaling the 2 large-range features?
Scaling is important. It is that Random Forest is less sensitive to the scaling then other algorithms and can work with "roughly"-scaled features.