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AI & Machine Learning · Foundational

Mean Absolute Error (MAE)

The average of absolute differences between predicted and actual values.

Definition

MAE treats all errors linearly, so it is more robust to outliers than MSE or RMSE and easy to explain. It is in the target's units.

Exam tip

Choose MAE when outliers should not dominate the error metric.

Related terms