Stepwise process for model selection with EBM classifier about interpret

[paulbkoch]

Hi @fcaleca1 -- If you wanted to build a model one feature at a time, the way to do it would be through the init_score parameter of the fit function. You would build an initial EBM with whatever features you wanted in the base EBM (which could be just 1). To add a new feature you'd create a new EBM and on the call to fit for that EBM you would give it the previous EBM in the init_score parameter. To make predictions you'd need to call predict in the same order that you called fit using the init_score parameter of the predict_proba function. It wouldn't be a very integrated EBM as you'd end up with separate models, but you could still visualize them individually.

[fcaleca1]

Hi @paulbkoch -- Thanks for your suggestion on how to build a model one feature at a time. What do you think about using Akaike information criterion as a guideline? Is it possible?