How would you design a cost-sensitive metric for a business?
PICTURE THIS: HOW TO EXPLAIN IT
Simple meaning
Assign a rupee or dollar cost to false positives and false negatives, then minimize expected cost on validation.
WHY — Metrics instead of guessing?
Why interviewers care about Metrics:
question about Metrics.
trade-offs, and what you would actually do on a AI / ML project - not buzzwords.
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:
- 1Assign a rupee or
dollar cost to false positives and false negatives, then minimize expected cost on validation.
- 2You can bake those
costs into class weights or into the threshold.
- 3Shipping accuracy when the
two errors have different prices is a common interview miss.
- 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
Assign a rupee or dollar cost to false positives and false negatives, then minimize expected cost on validation. You can bake those costs into class weights or into the threshold.