In statistics, mean absolute error (MAE) is a measure of errors between paired observations expressing the same phenomenon. ... This is known as a scale-dependent accuracy measure and therefore cannot be used to make comparisons between series using different scales.
What does mean absolute error tell us?
The absolute error is the absolute value of the difference between the forecasted value and the actual value. MAE tells us how big of an error we can expect from the forecast on average. ... Mean Absolute Percentage Error (MAPE) allows us to compare forecasts of different series in different scales.
How do you calculate mean absolute error?
Find all of your absolute errors, xi – x. Add them all up. Divide by the number of errors. For example, if you had 10 measurements, divide by 10.
...
Mean Absolute Error
...
Mean Absolute Error
- n = the number of errors,
- Σ = summation symbol (which means “add them all up”),
- |xi – x| = the absolute errors.
