urban-meal-delivery/tests/forecasts/timify
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
..
__init__.py Add OrderHistory class 2021-01-09 16:29:58 +01:00
test_aggregate_orders.py Shorten a couple of names 2021-01-31 20:20:55 +01:00
test_avg_daily_demand.py Add OrderHistory.choose_tactical_model() 2021-02-02 11:29:27 +01:00
test_make_time_series.py Add OrderHistory.choose_tactical_model() 2021-02-02 11:29:27 +01:00
test_order_history.py Add OrderHistory.first/last_order() methods 2021-01-31 21:46:20 +01:00