AI engineering glossary · Evaluation metrics
What is max error?
Max error (also called maximum error): The single largest absolute difference between a prediction and its true value across the test set. It captures the worst case and is used where one big miss is unacceptable, for instance in safety or engineering tolerances.
Max error: an example
With absolute errors 5, 2, 2 and 20 lakh, the max error is 20 lakh.
Related terms
More Evaluation metrics terms
- Maximum calibration error
- McNemar's test
- Mean absolute error
- Mean absolute percentage error
- Mean absolute scaled error
- Mean average precision
- Mean bias error
- Mean reciprocal rank
Where you learn it
Max 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.