Keith Battocchi

Sorry for the slow response. For 1) and 3), one goal of the class is to automate model-fitting so that users don't need to manage the fitting process themselves; as...

1. It's hard to say; first of all, if you're using 'automl' for your first stage models, then if, say, Lasso converges poorly on your data then hopefully a different...

Sorry for the slow response - a couple of thoughts: 1. It would help if you could provide a simplified repro; are a significant number of units treated and untreated...

One simple comparison that would be useful is how the memory consumption of standard sklearn RandomForests compares on dataframes of the same size, since much of the EconML tree code...

That's correct - if you set `discrete_outcome=True` then your y_model should be an sklearn classifier rather than a regressor and we'll use `predict_proba` rather than `predict`, so the residuals can...

@brandongreenwell-8451 I don't think discreteness of the outcome should pose any particular problem - I believe the theory just requires that you can model E[Y|X,W], which is what using `predict_proba`...

If you could provide a concrete reproduction of your issues that might help narrow down any issues, but here are a few thoughts. For question 1, predict_proba gives the fraction...

This indicates that none of the models for your features were successfully trained when you were fitting the CausalAnalysis class. I don't think that this logic should succeed, but we...

@gaugup @Advitya17 although it's possible that something has changed on our end I think it's pretty unlikely - CausalAnalysis is basically in maintenance mode and so we only make minor...

> Interestingly, if I remove discrete_treatment = True, and if I put a regressor for model_y (even though y is binary in my case), the code will run; but not...