The mean absolute error (MAE) is a metric used in regression analysis to determine the average magnitude of the error on a set of predicted values. The MAE is calculated as the sum of absolute errors divided by the sample size. The formula for MAE is as follows:
MAE = (1/n) * Σ|Pi – Oi|
- Σ = Sum over all considered values
- Pi = ith Predicted value
- Oi = ith Observed value
- n = sample size
You can use the MAE calculator below by entering a list of observed and predicted values in the boxes below, then click Calculate MAE.