In what situations would RMSE be a more appropriate metric than MAE?
- When larger errors are more critical to penalize
- When smaller errors are more critical to penalize
- When the model needs to be robust to outliers
- When the model requires a metric in squared units
RMSE can be more appropriate than MAE when larger errors are more critical to penalize. Since RMSE squares the errors before averaging them, it gives more weight to larger errors compared to MAE. This characteristic of RMSE can be more suitable in applications where large deviations from the actual values are considered more detrimental than smaller ones.
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