Mean Absolute Error (MAE) is a statistical measure that quantifies the average magnitude of errors in a set of predictions, without considering their direction. It is calculated by taking the average of the absolute differences between predicted values and actual values, making it a valuable tool for assessing the accuracy of regression models used in impact estimation.
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