Moderate Metrics Question 203 of 223

When is accuracy a bad metric?

AI & Data Analytics · Speak this in 60–90 seconds · Faridabad & Delhi NCR

IdeaMetrics

HowWhat happens inside

Why they askShows real use

On imbalanced data, predicting the majority class always looks accurate but useless.

Why interviewers care about Metrics:

They are checking judgment

on Metrics.

A good answer names

the situation, the default choice, and one exception - that reads as experience.

Stay structured

Name the idea, why it exists, then one short example.

Close cleanly

End with when you use it and one common pitfall.

Before you speak the answer, walk the interviewer through these steps:

1
On imbalanced data, predicting
the majority class always looks accurate but useless.
2
Precision, recall, and F1
tell a fairer story.
3
Fraud and disease screening
are classic examples.
4
Give an example
One tiny concrete case you can say aloud.
5
Common mistake
What juniors usually get wrong.
6
Close
When you pick this over the alternative.

Here's a short line you can speak, broken into clear beats:

Say this line

“Precision, recall, and F1 tell a fairer story.”

Break into beats

PrecisionrecallandF1tella

Speaking order

2987408337471632900

Note: Adapt this scaffold to your own project — keep it under 60–90 seconds.

On imbalanced data, predicting the majority class always looks accurate but useless. Precision, recall, and F1 tell a fairer story.