I'm trying to do some non-linear predictions and am going to use a random forest with Sk-learn. However my question has to do with data pre-processing.
I'm planning on using minmaxscaler to normalize the temperature, wind, and humidity data...however I have two other variables class, and month. Class is a category data feature which I'm going to use OneHotEncoder to pre-process. However do I want to normalize or do anything with the month data? (Normalize on scale of 0 to 1? Or leave 1-12?) What might be the best approach?