AutoML Vision: Predictions include --other-- field

Question

I have just trained a new model with a binary outcome (elite/non-elite). The model trained well, but when I tested a new image on it in the GUI it returned a third label --other--. I am not sure how/why that has appeared. Any ideas?

Answer 1

When multi-class (single-label) classification is used, there is an assumption that the confidence of all predictions must sum to 1 (as one and exactly one valid label is assumed). This is achieved by using softmax function. It normalizes all predictions to sum to 1 - which has some drawbacks - for example if both predictions are very low - for example prediction of "elite" is 0.0001 and Non_elite is 0.0002 - after normalization the predictions would be 0.333 and 0.666 respectively.

To work around that the automl system allows to use extra label (--other--) to indicate that none of the allowed predictions seems valid. This label is implementation detail and shouldn't be returned by the system (should be filtered out). This should get fixed in the near future.