Data Science & ML
Basic

Mean Absolute Error (MAE)

Average of absolute differences between predictions and actual values.

Formula

MAE=1n∑i=1n∣yi−y^i∣MAE = \frac{1}{n}\sum_{i=1}^{n}|y_i - \hat{y}_i|

Variables

y_iActual
\hat{y}_iPredicted
nSamples

Example

For errors 2, -1, 3: MAE = (2+1+3)/3 = 2

Did You Know?

MAE is more robust to outliers than MSE.

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