Why is a 0.5 probability threshold not automatically correct?
PICTURE THIS: DATA SPLIT
Fit on train, tune on val, report on test once.
Simple meaning
5 only matches equal costs and a well-calibrated model with balanced classes.
WHY — Logistic Regression instead of guessing?
Why interviewers care about Logistic Regression:
on Logistic Regression.
the situation, the default choice, and one exception - that reads as experience.
Name the idea, why it exists, then one short example.
End with when you use it and one common pitfall.
STEPS — What happens step by step?
Before you speak the answer, walk the interviewer through these steps:
- 10.5 only matches equal
costs and a well-calibrated model with balanced classes.
- 2You should pick the
threshold on validation using precision, recall, or dollar cost.
- 3Prevalence and operating constraints
almost always move that cutoff.
- 4Give an example
One tiny concrete case you can say aloud.
- 5Common mistake
What juniors usually get wrong.
- 6Close
When you pick this over the alternative.
EXAMPLE — See it in action
Here's a short line you can speak, broken into clear beats:
Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.
Key takeaway
5 only matches equal costs and a well-calibrated model with balanced classes. You should pick the threshold on validation using precision, recall, or dollar cost.