third commit

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Bairly 2025-03-24 17:06:38 +08:00
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@ -69,8 +69,9 @@
2. 每次预测均采用该时间点以前的真实数据,即每次预测均为单步预测。
3. 使用随机搜索法参数调优。
4. 评估指标:效果很好
- RMSE: 12.30
- R-squared: 0.92
- MAE: 7.87
5. 重要特征观察图AQI_lag_1,2,3最为重要即该时刻的AQI主要由前3个观测时刻决定。day_of_week显示影响较小但不是完全没有。
6. 其实也做了利用递归直接预测一整个月的,效果看图就很明了了![](./images/XG_pred_by_recursion.png)
- RMSE: 11.815
- R-squared: 0.929
- MAE: 7.722
5. 预测图:![](./images/xg_by_step.png)
6. 重要特征观察图AQI_lag_1最为重要即该时刻的AQI主要由前1个观测时刻决定。AQI_lag_21也较为重要。day_of_week显示影响较小但不是完全没有。
7. 其实也做了利用递归直接预测一整个月的,效果看图就很明了了![](./images/XG_pred_by_recursion.png)