Issue with #791: Missing data allowed when training, but not inferencing

[esbraun]

#791 ought to allow missing data when inferencing if allow_missing = True, but currently an error is thrown when the inference data includes missing data. RE: below for a working example based on the "Metalearner Examples" notebook for a demonstration of the issue.

https://colab.research.google.com/drive/1QT-IdwRWRUiQNDwqJ0EXPXSftDuIg3uE?usp=sharing

[Ftrejo23]

I'm seeing the same issue

[fverac]

Thanks for raising this issue. In the original PR we originally only considered missing data during training, but it seems there is interest in extending this to inferencing as well.

[erasedcitizen11]

Hi there, just wondering if there any update on this as running into the same problems (doesn't allow missing values when computing CATE/ATE).

[esbraun]

@erasedcitizen11 I created a fork that disables the missing value checks which is a requirement for our use cases. Use at your own risk: https://github.com/esbraun/EconML/tree/main