[streetcat1]

Again, my point is that for a given data set, an auto ml system is much more efficient and radically cheaper than human modeler.

You are pointing to an area outside the realm of automl (feature engineering/generation) , which is domain specific. But this was not my original question.

[autokad]

this has nothing to do with feature engineering and generation. I never added or changed any features in the example. It is exactly in the realm of automl, you run a model, -because- you are missing data, your model is making wrong assumptions.

You could argue (which you didn't) that this would fall under model interpretation, but a model in this example would probably fail to generalize and make bad predictions in the future: IE slamming home values because they have large square footage.