Paul Koch

HI @nochimake -- For local importance, you can use the eval_terms function: https://interpret.ml/docs/python/api/ExplainableBoostingClassifier.html#interpret.glassbox.ExplainableBoostingClassifier.eval_terms If you also want the global importances, those can be obtained with the term_importances function: https://interpret.ml/docs/python/api/ExplainableBoostingClassifier.html#interpret.glassbox.ExplainableBoostingClassifier.term_importances

Hi @tylerjereddy -- Glad to hear you've been finding that EBMs perform well on many of your datasets, and hopefully we can make EBMs work on this one too. We...

On the question of memory leaks: I think what you're observing is due to the normal memory fragmentation that you'd expect to find in this kind of process. We run...

One more tip: We run the outer bags on separate cores, and we leave one core free by default on the machine. If you have 8 cores, then setting outer_bags...

Hi @prgarg007 -- We do not have support for multi-output models. You can do this though in a general way by constructing individual regression models and combining them using scikit-learn's...

This is not yet available. There are discussions of this in https://github.com/interpretml/interpret/issues/304 and https://github.com/interpretml/interpret/issues/403 Today if you want to pick your own interactions, you need to train the model a...

To be more exact, it is possible to train an initial EBM and then boost another EBM model on top of it using the init_score parameter of the fit function....

I made an example notebook to illustrate how you'd build custom pairs yourself and boost the pairs on top of the mains model. Just for fun I added some triples...

Thanks @DerWeh -- I've updated the link above to point to our documentation, which now has this example. At the top of the documentation link you can find a link...

Hi @oddwang -- We do support a number of alternative built-in loss functions, but to fully customize the loss function you currently need to modify the C++ slightly. I have...