Predict an unbalanced class
I'm pretty new with RM so apologize if I'm asking someting straightfoward.
I'm trying to train a predictor on a class that is heavely unbalanced - say churn rate(on average I have 1 observation with chur every 999 observation without).
I read that boosted trees could be a good choice as algorthm, but I have some difficulties to understand if there is a way to have a "penalized" version of this.. how can I achieve this?
Another approach that I could follow would be to generate new data based on the distribution of the other variables in the data set, is that possible to do in RM?
many thanks for your help!