Problem
Scenario
You have a classification model that outputs probabilities, and stakeholders want to use those scores for decision-making rather than just ranking. You need to judge whether the predicted probabilities can be trusted as stated, for example whether cases scored at 0.8 really occur about 80% of the time.
Question
How would you determine whether a model is well calibrated?
What This Tests
- Calibration versus discrimination
- Reliability plots and bin-wise observed rates
- Log loss and probability quality
- Confidence intervals on calibration estimates
- Threshold implications after recalibration
Practicing as: Data Scientist interview at OpenTextHi, I'll play your OpenText interviewer for the Data Scientist role. Candidates describe these interviews as mostly positive and moderately difficult, so expect me to be friendly and conversational. Take your time with the question above and answer like we're in the room.
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