AI engineering glossary · Evaluation metrics
What is median absolute error?
Median absolute error (also called MedAE): The middle value of all the absolute prediction errors. Because it looks at the median rather than the mean, a handful of extreme mistakes barely moves it, making it a robust description of typical error when the data contains outliers.
Median absolute error: an example
Absolute errors 5, 2, 2, 20 sort to 2, 2, 5, 20, so the median absolute error is (2 + 5) / 2 = 3.5, while the mean is 7.25.
Related terms
More Evaluation metrics terms
- METEOR
- Micro averaging
- Negative predictive value
- Normalised discounted cumulative gain
- Normalised mutual information
- Normalised RMSE
- Operating point
- Partial AUC
Where you learn it
Median absolute error is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.