This instrument computes the common absolute distinction between predicted and precise values in a dataset. For instance, if a mannequin predicts home costs and the variations between the predictions and actual costs are $5,000, $10,000, and $2,000, the common of those absolute variations represents the metric’s output. This supplies a simple measure of prediction accuracy in simply comprehensible models.
Averaging the magnitude of errors provides a transparent, interpretable metric for mannequin efficiency analysis. In contrast to different metrics delicate to outliers, this method treats all errors equally, offering robustness in varied purposes like forecasting and regression evaluation. Its historic roots lie in primary statistical strategies, predating extra complicated analysis strategies, and its simplicity continues to make it a precious instrument for fast assessments of predictive accuracy.
