2025-02-25 11:33:12,047 - main.py - DEBUG - 63 - loading sales data..
2025-02-25 11:33:12,880 - reading_data.py - DEBUG - 129 - start date: 2022-03-01 00:00:00 end date: 2025-04-30 00:00:00
2025-02-25 11:33:46,890 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-02-25 11:33:47,060 - algorithm.py - DEBUG - 78 - shape: (91727, 269) start: 2022-03-01 00:00:00 end: 2024-12-06 00:00:00
2025-02-25 11:33:55,754 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7dfc3013eaf0>,
'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}
2025-02-25 11:33:55,757 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 1).
2025-02-25 11:33:55,757 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:33:56,653 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 1)
2025-02-25 11:33:59,461 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 1)
2025-02-25 11:34:05,724 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 1).
2025-02-25 11:34:05,724 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:34:05,774 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 1)
2025-02-25 11:34:05,922 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 1)
2025-02-25 11:34:06,236 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-02-25 11:34:06,400 - algorithm.py - DEBUG - 78 - shape: (97208, 269) start: 2022-03-01 00:00:00 end: 2025-02-06 00:00:00
2025-02-25 11:34:15,432 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7dfc3013eaf0>,
'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}
2025-02-25 11:34:15,435 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 3).
2025-02-25 11:34:15,435 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:34:16,296 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 3)
2025-02-25 11:34:19,106 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 3)
2025-02-25 11:34:25,433 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 3).
2025-02-25 11:34:25,433 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:34:25,482 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 3)
2025-02-25 11:34:25,624 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 3)
2025-02-25 11:34:25,940 - algorithm.py - DEBUG - 72 - start training with xgboost...
2025-02-25 11:34:26,110 - algorithm.py - DEBUG - 78 - shape: (99847, 269) start: 2022-03-01 00:00:00 end: 2025-03-06 00:00:00
2025-02-25 11:34:35,327 - algorithm.py - INFO - 117 - parameters:
{ 'colsample_bytree': 0.85,
'enable_categorical': False,
'eval_metric': <function mean_absolute_percentage_error at 0x7dfc3013eaf0>,
'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}
2025-02-25 11:34:35,331 - main.py - INFO - 95 - Successfully trained xgb9 xgboost for month (2025, 4).
2025-02-25 11:34:35,331 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:34:36,303 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 4)
2025-02-25 11:34:39,090 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 4)
2025-02-25 11:34:45,407 - main.py - INFO - 95 - Successfully trained agp agp for month (2025, 4).
2025-02-25 11:34:45,407 - prediction_task.py - DEBUG - 21 - predictions starting...
2025-02-25 11:34:45,457 - prediction_task.py - DEBUG - 31 - test data not found for 29 Kelheim II in period (2025, 4)
2025-02-25 11:34:45,604 - prediction_task.py - DEBUG - 31 - test data not found for 96 Hof in period (2025, 4)
2025-02-25 11:34:49,946 - functions.py - INFO - 87 - No duplicates found in predictions.
2025-02-25 11:34:55,845 - functions.py - DEBUG - 206 - metric: mae
2025-02-25 11:34:57,093 - functions.py - DEBUG - 206 - metric: mape
2025-02-25 11:34:58,334 - functions.py - DEBUG - 206 - metric: jensen_shannon
2025-02-25 11:34:59,589 - functions.py - DEBUG - 206 - metric: kullback_leibler
2025-02-25 11:35:01,364 - 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')
2025-02-25 11:35:01,624 - 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')
2025-02-25 11:35:01,882 - 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')
2025-02-25 11:35:01,981 - 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')