HOW DOES MEAN ABSOLUTE ERROR (MAE) DIFFER FROM MEAN SQUARED ERROR (MSE) IN REGRESSION EVALUATION?
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Level:
Medium
Dive into a quirky quiz on ML linear regression! Challenge your understanding of slopes, errors, and stats with a fun twist.
Question Types: Multiple choice
Answers:
- MAE penalizes larger errors more than MSE
- MAE gives equal weight to all errors, while MSE penalizes larger errors more severely
- There is no difference between them
- MSE is only used for classification tasks
- MSE is always lower than MAE