Add example to docs that shows lambda X, y: y.isna()

[juanitorduz]

Hey! First of all: this is a very cool project ;) I have been thinking about potential new "reasons" to doubt and I personally often look into predictions generated by a model whenever the data instance had missing values (and part of the model-pipeline imputes them)... So I wonder if it would be useful to have a FillNaNReason (or something similar) based, for example in the MissingIndicator transformer.

[koaning]

If you have a look at the implementation details you'll notice that internally all the reasons are just objects with __call__ implemented. That means that you may also use whatever lambda function that you can come up with.

That means that you can already check for nan via;

DoubtEnsemble(
    wrong_pred=lambda X, y: (model.predict(X) != y).astype(float16), 
    nan_label=lambda X, y: y.isnan(),
)

Since the lambda variant is very straightforward I'd prefer not to over-populate the reasons.

[juanitorduz]

Alright! Yes, makes sense. Thanks! In this case I'll close this issue and maybe you could think if adding this case to the examples can be useful ;)

[koaning]

An extra segment in the docs along the lines of "useful tricks" might be good, for sure. I'll re-open the issue and change the title so it's a todo.

[koaning]

merging PR now.