Forecast vs Actual¶
| Tab | Description |
|---|---|
| Performance | Compares how different predictions behave from different forecast points to different times in the future. Time-aware only |
Forecast vs. Actual helps you to answer what, for your needs, is the best distance to predict. Forecasting out only one day may provide the best results, but it may not be the most actionable for your business. Forecasting the next three days out, however, may provide relatively good accuracy and give your business time to react to the information provided. If the experiment included calendar data, those events are displayed on this chart, providing insight into the effects of those events. Note that series-based experiments are sometimes compute-on-demand, depending on projected space and memory requirements.
Next steps¶
Continue evaluating forecast performance with these related time-aware insights.
- Forecasting Accuracy: See how prediction accuracy changes at each forecast distance in the forecast window.
- Period Accuracy: Compute aggregate error metric values for specific, important periods within the training dataset.
- Series Insights: Review series-specific distribution and metric scores for multiseries projects.