Average Absolute Error (AAE)#
The mean of absolute differences between forecasts and outcomes.
Important
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What it is#
The average absolute error is the mean of the absolute errors — the average of \(|\text{forecast} - \text{actual}|\) across all points. It answers how big is the typical error? in the same units as the data, and is identical to the Mean Absolute Error (MAE) (often also called the Mean Absolute Deviation):
Properties#
Because it uses absolute (not squared) errors, AAE is robust to outliers — a few large misses do not dominate — and it treats over- and under-prediction symmetrically, ignoring the direction of error. The forecast that minimizes it is the median.
Limitation#
AAE is scale-dependent: you cannot compare it across series on different scales (an AAE of 10 is tiny for house prices, huge for temperatures). For that, switch to a percentage or relative metric.
Theme: Model Evaluation & Uncertainty · All terminology
Hint
Mind map — connected ideas
Forecast Error · Naïve Baseline Forecast · Relative accuracy · R² (R-squared) · Point Forecasts · Time Series Forecasting
Hint
More in Model Evaluation & Uncertainty
Baseline Heuristics · Bootstrap · Bootstrap Confidence Intervals (CIs) · Coverage · Cramér’s V · DeLong’s Test · KS Statistic (Kolmogorov–Smirnov Statistic) · Likelihood Ratio (LR) · Mann–Whitney U Test (also called the Wilcoxon rank-sum test) · MASE (Mean Absolute Scaled Error) · Mean Absolute Error (MAE) · Mean Absolute Percentage Error (MAPE) · Mean Squared Error (MSE) · Relative accuracy
See also
Source article Adapted (context, re-expressed) in our own words from: Average Absolute Error (AAE) (insightful-data-lab.com).