MAE

Creator
Creator
Seonglae Cho
Created
Created
2025 Mar 24 15:22
Editor
Edited
Edited
2025 Mar 24 15:30

Mean absolute error

If we assume the error ϵ=yy^\epsilon = y - \hat{y} follows a normal distribution, the log likelihood is logp(ϵ)=ϵb+const\log p(\epsilon) = -\frac{|\epsilon|}{b} +\text{const}. Maximizing this leads to the derivation of MAE.
Analogous to assuming Laplace-distributed errors and Less sensitive to outliers.
 
 
 
 
 
 
 
 

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