方法对比
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| 对称平均绝对百分比误差 (sMAPE)× | 平均绝对误差 (MAE)× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 1985 | 1799 |
| 提出者≠ | J. Scott Armstrong | Pierre-Simon Laplace |
| 类型≠ | Symmetric percentage-based evaluation metric | Robust distance-based metric |
| 开创性文献≠ | Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010 | Laplace, P. S. (1799). Traité de Mécanique Céleste. Paris: J.B.M. Duprat. link ↗ |
| 别名 | sMAPE, SMAPE, symmetric MAPE | MAE, L1 error, mean absolute deviation |
| 相关≠ | 4 | 3 |
| 摘要≠ | Symmetric Mean Absolute Percentage Error is a refinement of MAPE that addresses its asymmetry by using the average of actual and predicted values as the denominator. Proposed by J. Scott Armstrong and refined by Makridakis (1993) and Hyndman & Koehler (2006), sMAPE treats over- and under-predictions symmetrically. | 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. |
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