Real-time error correction for time series forecasting
In brief
- EFC corrects time series forecasts by using past errors as causal feedback.
- It employs a Causal Error Diagonal (CED) and Cumulative Error Transport (CET) to adjust future predictions.
- Experiments demonstrate improved performance without excessive overcorrection.
A new method called Error Feedback Calibration (EFC) enables real-time correction of time series forecasts using past errors. It leverages causal feedback mechanisms to adjust future predictions without retraining the model. Tests show significant performance gains while avoiding harmful overcorrection.
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