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Hyperparameter for Germany #9
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Actually, I did not mean to report a bug, I just wanted to ask for some explanation about the outcome. I ran the recalibrating dnn simpified.py first. I used the "https://sandbox.zenodo.org/api/files/fb5bae17-de91-4ce7-b348-0d62e52824b5/DE.csv" which is the dataset you mentioned for Germany. Then reran it for other markets such as PJM or BE and for both, sMAPE and MAE were noticeably lower than Germany's results. for example, sMAPE for Germany was above 30 % but for PJM was around 5%. Considering the above explanation, I wondered if you also ran the Hyperparameter optimization script (with max evals 1500) for DE dataset to get |
I understand now. So a couple of things:
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Hi,
I tried to replicate the forecast for the day ahead electricity prices for Germany, but the sMAPEs are too high, contrasting with the markets, like PJM, BE, and NP.
Did you also run the Hyperparameter optimization (with max evals 1500) for DE? If yes, why the forecast for the DE market is not accurate?
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