Stacking Models For Improved Predictions
Stacking models is a great technique for squeezing out more performance.
First, let me describe what I mean by stacking. The idea is to divide the training set into several pieces like you would do in k-folds cross validation. For each fold, the rest of the folds are used to obtain a predictions using all the models 1…M.