I am trying to learn more about how to build ensembles of predictions in R and coming to a roadblock, and am hoping one can offer guidance.
I often read about people automatically identifying how they should weight each model through the use of OLS. How do people do this? Do you just insert your prediction from each model as a regressor in the model?
E.g., Final_Prediction = b0 + b1*prediction_from_GBM + b2*prediction_from_SVM + bkxk + e
and just fit the line above to combine your predictions?
What about when you are predicting class membership.... do you get the probabilities from each model and fit them in a logistic model similarly?
Any resources that are R specific or any thoughts / clarifications are greatly appreciated. I have not been able to find anything.