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 (MASE)× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 1985 | 2006 |
| 提出者≠ | J. Scott Armstrong | Rob J. Hyndman and Anne B. Koehler |
| 类型≠ | Symmetric percentage-based evaluation metric | Scale-independent baseline comparison 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 | Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. DOI ↗ |
| 别名≠ | sMAPE, SMAPE, symmetric MAPE | MASE |
| 相关 | 4 | 4 |
| 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 Scaled Error is a scale-independent metric that measures prediction accuracy relative to a simple baseline (naive forecast). Introduced by Hyndman and Koehler (2006), MASE directly compares model performance to a reference method, overcoming limitations of MAPE and other percentage-based metrics. |
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