| from .data import load_dataset, SEASONALITY_MAP | |
| from .fit_model import fit_predict_with_model, MODEL_NAME_TO_CLASS | |
| from .score import score_predictions | |
| AVAILABLE_MODELS = list(MODEL_NAME_TO_CLASS.keys()) | |
| AVAILABLE_DATASETS = [ | |
| "car_parts_without_missing", | |
| "cif_2016", | |
| "covid_deaths", | |
| "electricity_hourly", | |
| "electricity_weekly", | |
| "fred_md", | |
| "hospital", | |
| "kaggle_web_traffic_weekly", | |
| "kdd_cup_2018_without_missing", | |
| "m1_monthly", | |
| "m1_quarterly", | |
| "m1_yearly", | |
| "m3_monthly", | |
| "m3_other", | |
| "m3_quarterly", | |
| "m3_yearly", | |
| "m4_daily", | |
| "m4_hourly", | |
| "m4_weekly", | |
| "m4_yearly", | |
| "m4_monthly", | |
| "m4_quarterly", | |
| "nn5_daily_without_missing", | |
| "nn5_weekly", | |
| "pedestrian_counts", | |
| "tourism_monthly", | |
| "tourism_quarterly", | |
| "tourism_yearly", | |
| "uber_tlc_without_missing", | |
| ] | |