Experiments¶
Description of Train and Test Data¶
Todo
- Simple test-train split.
- Train data from 2017.
- Test data from 2018.
- Calendar heatmap graphic.
Evaluation Metrics¶
Todo
- MAE vs. MSE
- MAPE vs. sMAPE
- R^2
- day-night vs day-only
Preprocess & Feature Selection¶
Todo
- What features are useful?
- Computed time-of-day and time-of-year features.
- Training with day-night vs day-only.
Empirical Learning Curve¶
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- Error vs amount of training data used.
- Linear regression vs. Random Forest vs. GBTs.
Reference Time vs Forecast Time¶
Todo
- Error for each (reftime, forecast time) pair.
- Heatmap.