platt scaling

A model can rank perfectly and still emit meaningless probabilities. The signal is knowing exactly when calibration matters, how to measure it, and the post-hoc fixes. Here is the answer most candidates miss.

A model can rank perfectly and still lie about its probabilities; its 0.9 may be right 70% of the time. The signal is knowing the three fixes, which data size each needs, and how to measure the gap. Here is the answer.