2025-03-06 06:49:27,508 - main.py - DEBUG - 63 - loading sales data..
2025-03-06 06:49:28,349 - reading_data.py - DEBUG - 129 - start date: 2022-03-01 00:00:00 end date: 2025-05-31 00:00:00
2025-03-06 06:50:03,025 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-03-06 06:50:03,195 - algorithm.py - DEBUG - 78 - shape: (91728, 269) start: 2022-03-01 00:00:00 end: 2024-12-06 00:00:00
2025-03-06 06:50:11,730 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7f5c61b3daf0>,
'learning_rate': 0.01,
'max_depth': 7,
'missing': nan,
'n_estimators': 1100,
'n_jobs': -1,
'objective': 'reg:squarederror',
'reg_alpha': 0.01,
'reg_lambda': 1.0,
'subsample': 1.0}
2025-03-06 06:50:11,733 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 1).
2025-03-06 06:50:11,734 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:50:12,645 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 1)
2025-03-06 06:50:15,474 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 1)
2025-03-06 06:50:21,715 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 1).
2025-03-06 06:50:21,716 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:50:21,767 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 1)
2025-03-06 06:50:21,917 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 1)
2025-03-06 06:50:22,330 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-03-06 06:50:22,495 - algorithm.py - DEBUG - 78 - shape: (97209, 269) start: 2022-03-01 00:00:00 end: 2025-02-06 00:00:00
2025-03-06 06:50:31,380 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7f5c61b3daf0>,
'learning_rate': 0.01,
'max_depth': 7,
'missing': nan,
'n_estimators': 1100,
'n_jobs': -1,
'objective': 'reg:squarederror',
'reg_alpha': 0.01,
'reg_lambda': 1.0,
'subsample': 1.0}
2025-03-06 06:50:31,384 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 3).
2025-03-06 06:50:31,384 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:50:32,257 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 3)
2025-03-06 06:50:35,171 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 3)
2025-03-06 06:50:41,317 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 3).
2025-03-06 06:50:41,317 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:50:41,369 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 3)
2025-03-06 06:50:41,518 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 3)
2025-03-06 06:50:41,842 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-03-06 06:50:42,011 - algorithm.py - DEBUG - 78 - shape: (99848, 269) start: 2022-03-01 00:00:00 end: 2025-03-06 00:00:00
2025-03-06 06:50:50,991 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7f5c61b3daf0>,
'learning_rate': 0.01,
'max_depth': 7,
'missing': nan,
'n_estimators': 1100,
'n_jobs': -1,
'objective': 'reg:squarederror',
'reg_alpha': 0.01,
'reg_lambda': 1.0,
'subsample': 1.0}
2025-03-06 06:50:50,994 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 4).
2025-03-06 06:50:50,994 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:50:51,887 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 4)
2025-03-06 06:50:54,651 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 4)
2025-03-06 06:51:00,790 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 4).
2025-03-06 06:51:00,790 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-03-06 06:51:00,842 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 4)
2025-03-06 06:51:00,995 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 4)
2025-03-06 06:51:05,365 - functions.py - INFO - 87 - No duplicates found in predictions.
2025-03-06 06:51:11,298 - functions.py - DEBUG - 206 - metric: mae
2025-03-06 06:51:12,565 - functions.py - DEBUG - 206 - metric: mape
2025-03-06 06:51:13,826 - functions.py - DEBUG - 206 - metric: jensen_shannon
2025-03-06 06:51:15,094 - functions.py - DEBUG - 206 - metric: kullback_leibler
2025-03-06 06:51:16,883 - conversion_functions.py - DEBUG - 168 - business hours file: (1332, 9) Index(['fg_sg', 'fg_bez', 'Bundesland', 'year', 'month', 'weekday_hours', 'saturday_hours', 'weekday_hours_extra', 'saturday_hours_extra'], dtype='object')
2025-03-06 06:51:17,318 - conversion_functions.py - DEBUG - 168 - business hours file: (2664, 9) Index(['fg_sg', 'fg_bez', 'Bundesland', 'year', 'month', 'weekday_hours', 'saturday_hours', 'weekday_hours_extra', 'saturday_hours_extra'], dtype='object')
2025-03-06 06:51:17,574 - conversion_functions.py - DEBUG - 168 - business hours file: (3996, 9) Index(['fg_sg', 'fg_bez', 'Bundesland', 'year', 'month', 'weekday_hours', 'saturday_hours', 'weekday_hours_extra', 'saturday_hours_extra'], dtype='object')
2025-03-06 06:51:17,676 - conversion_functions.py - DEBUG - 168 - business hours file: (4662, 10) Index(['fg_sg', 'fg_bez', 'Bundesland', 'year', 'month', 'weekday_hours', 'saturday_hours', 'weekday_hours_extra', 'saturday_hours_extra', 'season'], dtype='object')