方法对比
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| 平均绝对误差 (MASE)× | 对称平均绝对百分比误差 (sMAPE)× | |
|---|---|---|
| 领域 | 模型评估 | 模型评估 |
| 方法族 | MCDM | MCDM |
| 起源年份≠ | 2006 | 1985 |
| 提出者≠ | Rob J. Hyndman and Anne B. Koehler | J. Scott Armstrong |
| 类型≠ | Scale-independent baseline comparison metric | Symmetric percentage-based evaluation metric |
| 开创性文献≠ | Hyndman, R. J., & Koehler, A. B. (2006). Another look at measures of forecast accuracy. International Journal of Forecasting, 22(4), 679-688. DOI ↗ | Armstrong, J. S. (1985). Long-range forecasting: from crystal ball to computer (2nd ed.). New York: John Wiley & Sons. ISBN: 978-0471082010 |
| 别名≠ | MASE | sMAPE, SMAPE, symmetric MAPE |
| 相关 | 4 | 4 |
| 摘要≠ | 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. | 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. |
| ScholarGate数据集 ↗ |
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