方法证据记录
Mean Absolute Error
Mean Absolute Error is a robust metric that measures the average absolute magnitude of prediction errors in regression models. Dating back to Pierre-Simon Laplace's work on observational errors (1799), MAE quantifies typical prediction deviation by averaging the absolute differences between observed and predicted values.
源记录
引文逐字复制自方法源记录。这些引文不代表任何层级的验证。
Mean Absolute Error
分类方法记录 · mcdm / model-evaluation
- Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat. · URL
- Brossier, C. L. (1999). Consistency of trimmed and Winsorized L-estimators of location and scale. Journal of the American Statistical Association, 74(368), 813-821. · URL
- Huber, P. J. (2009). Robust Statistics (2nd ed.). Hoboken, NJ: John Wiley & Sons. · ISBN 978-0470129906
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