MLS-C01 Modeling Practice Question
A data scientist is building a classification model and wants to evaluate its performance. Which TWO metrics are appropriate for a multi-class classification problem? (Choose 2)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Recall
Both precision and recall can be extended to multi-class via micro/macro averaging. R-squared is for regression; RMSE is for regression; Mean Absolute Error is for regression.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Mean Absolute Error (MAE)
Why it's wrong here
MAE is for regression.
- ✓
Recall
Why this is correct
Recall can be averaged across classes.
- ✓
Precision
Why this is correct
Precision can be averaged across classes.
- ✗
R-squared
Why it's wrong here
R-squared is for regression models.
- ✗
Root Mean Square Error (RMSE)
Why it's wrong here
RMSE is for regression.
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