

FAQ

How do I add a reason for nan values?

A reason in doubtlab is little more than a function that can attach a 0/1 doubt-label to a row of data. As explained here, that means that you can totally use lambda functions!

To implement this, you'll likely need to write something like:

from doubtlab.ensemble import DoubtEnsemble

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

Note that you can also add another reason for nan values that appear in X.