Alexander Hess af82951485 Add OrderHistory.choose_tactical_model() ... - the method implements a heuristic from the first research paper that chooses the most promising forecasting `*Model` based on the average daily demand in a `Pixel` for a given `train_horizon` - adjust the test scenario => `LONG_TRAIN_HORIZON` becomes `8` as that is part of the rule implemented in the heuristic		2021-02-02 11:29:27 +01:00
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methods	Add extrapolate_season.predict() function	2021-02-01 11:32:10 +01:00
timify	Add OrderHistory.choose_tactical_model()	2021-02-02 11:29:27 +01:00
__init__.py	Add extrapolate_season.predict() function	2021-02-01 11:32:10 +01:00
conftest.py	Add OrderHistory.avg_daily_demand()	2021-02-01 21:50:42 +01:00
test_models.py	Add OrderHistory.avg_daily_demand()	2021-02-01 21:50:42 +01:00