I think overconfident and underconfident aren’t crisp terms to describe this. With binary outcomes, you can invert the prediction and it means the same thing (20% chance of X == 80% chance of not X). So being below the calibration line in the 90% bucket and above the line in the 10% bucket are functionally the same thing.
I think overconfident and underconfident aren’t crisp terms to describe this. With binary outcomes, you can invert the prediction and it means the same thing (20% chance of X == 80% chance of not X). So being below the calibration line in the 90% bucket and above the line in the 10% bucket are functionally the same thing.