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2022-231
2022-231
Commits
60030cd3
Commit
60030cd3
authored
Oct 08, 2022
by
Tharushika P.R
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60030cd3
2022-09-28 03:35:38,922:INFO:Initializing load_model()
2022-09-28 03:35:38,923:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:42:51,821:INFO:Initializing load_model()
2022-09-28 03:42:51,822:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:43:04,200:INFO:Initializing load_model()
2022-09-28 03:43:04,200:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:44:08,732:INFO:Initializing load_model()
2022-09-28 03:44:08,733:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:44:16,515:INFO:Initializing load_model()
2022-09-28 03:44:16,515:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:46:07,803:INFO:Initializing load_model()
2022-09-28 03:46:07,803:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:46:45,179:INFO:Initializing load_model()
2022-09-28 03:46:45,179:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:48:45,628:INFO:Initializing load_model()
2022-09-28 03:48:45,629:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:49:58,134:INFO:Initializing load_model()
2022-09-28 03:49:58,134:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:51:20,764:INFO:Initializing load_model()
2022-09-28 03:51:20,764:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:52:08,054:INFO:Initializing load_model()
2022-09-28 03:52:08,055:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:53:38,203:INFO:Initializing load_model()
2022-09-28 03:53:38,203:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 03:57:19,784:INFO:Initializing load_model()
2022-09-28 03:57:19,785:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 04:01:11,365:INFO:Initializing predict_model()
2022-09-28 04:01:11,365:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:01:11,365:INFO:Checking exceptions
2022-09-28 04:01:11,365:INFO:Preloading libraries
2022-09-28 04:04:41,461:INFO:Initializing load_model()
2022-09-28 04:04:41,461:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 04:04:49,345:INFO:Initializing predict_model()
2022-09-28 04:04:49,345:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:04:49,345:INFO:Checking exceptions
2022-09-28 04:04:49,345:INFO:Preloading libraries
2022-09-28 04:04:52,735:INFO:Initializing predict_model()
2022-09-28 04:04:52,736:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:04:52,736:INFO:Checking exceptions
2022-09-28 04:04:52,736:INFO:Preloading libraries
2022-09-28 04:05:01,387:INFO:Initializing predict_model()
2022-09-28 04:05:01,387:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:05:01,387:INFO:Checking exceptions
2022-09-28 04:05:01,387:INFO:Preloading libraries
2022-09-28 04:05:41,957:INFO:Initializing predict_model()
2022-09-28 04:05:41,957:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:05:41,957:INFO:Checking exceptions
2022-09-28 04:05:41,957:INFO:Preloading libraries
2022-09-28 04:05:48,092:INFO:Initializing predict_model()
2022-09-28 04:05:48,092:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:05:48,092:INFO:Checking exceptions
2022-09-28 04:05:48,092:INFO:Preloading libraries
2022-09-28 04:06:02,543:INFO:Initializing predict_model()
2022-09-28 04:06:02,543:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:06:02,543:INFO:Checking exceptions
2022-09-28 04:06:02,543:INFO:Preloading libraries
2022-09-28 04:06:17,243:INFO:Initializing predict_model()
2022-09-28 04:06:17,244:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:06:17,244:INFO:Checking exceptions
2022-09-28 04:06:17,244:INFO:Preloading libraries
2022-09-28 04:06:48,669:INFO:Initializing load_model()
2022-09-28 04:06:48,670:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 04:06:49,587:INFO:Initializing predict_model()
2022-09-28 04:06:49,588:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:06:49,588:INFO:Checking exceptions
2022-09-28 04:06:49,588:INFO:Preloading libraries
2022-09-28 04:07:30,400:INFO:Initializing predict_model()
2022-09-28 04:07:30,400:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:07:30,400:INFO:Checking exceptions
2022-09-28 04:07:30,400:INFO:Preloading libraries
2022-09-28 04:07:39,519:INFO:Initializing predict_model()
2022-09-28 04:07:39,519:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:07:39,519:INFO:Checking exceptions
2022-09-28 04:07:39,519:INFO:Preloading libraries
2022-09-28 04:07:53,320:INFO:Initializing predict_model()
2022-09-28 04:07:53,321:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:07:53,321:INFO:Checking exceptions
2022-09-28 04:07:53,321:INFO:Preloading libraries
2022-09-28 04:08:07,171:INFO:Initializing predict_model()
2022-09-28 04:08:07,171:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:08:07,171:INFO:Checking exceptions
2022-09-28 04:08:07,171:INFO:Preloading libraries
2022-09-28 04:08:31,470:INFO:Initializing predict_model()
2022-09-28 04:08:31,471:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:08:31,471:INFO:Checking exceptions
2022-09-28 04:08:31,471:INFO:Preloading libraries
2022-09-28 04:09:30,002:INFO:Initializing predict_model()
2022-09-28 04:09:30,002:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:09:30,003:INFO:Checking exceptions
2022-09-28 04:09:30,003:INFO:Preloading libraries
2022-09-28 04:09:40,326:INFO:Initializing predict_model()
2022-09-28 04:09:40,326:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:09:40,326:INFO:Checking exceptions
2022-09-28 04:09:40,327:INFO:Preloading libraries
2022-09-28 04:10:48,206:INFO:Initializing load_model()
2022-09-28 04:10:48,206:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 04:15:18,402:INFO:Initializing load_model()
2022-09-28 04:15:18,402:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-09-28 04:17:48,248:INFO:Initializing predict_model()
2022-09-28 04:17:48,248:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-09-28 04:17:48,248:INFO:Checking exceptions
2022-09-28 04:17:48,248:INFO:Preloading libraries
2022-10-05 21:48:02,846:INFO:Initializing load_model()
2022-10-05 21:48:02,846:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-05 21:48:12,224:INFO:Initializing load_model()
2022-10-05 21:48:12,225:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 05:30:54,665:INFO:Initializing load_model()
2022-10-07 05:30:54,666:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 05:31:04,690:INFO:Initializing load_model()
2022-10-07 05:31:04,692:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 06:07:56,805:INFO:Initializing load_model()
2022-10-07 06:07:56,806:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 06:07:57,413:INFO:Initializing predict_model()
2022-10-07 06:07:57,413:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:07:57,414:INFO:Checking exceptions
2022-10-07 06:07:57,414:INFO:Preloading libraries
2022-10-07 06:10:10,747:INFO:Initializing predict_model()
2022-10-07 06:10:10,762:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:10:10,763:INFO:Checking exceptions
2022-10-07 06:10:10,763:INFO:Preloading libraries
2022-10-07 06:10:26,855:INFO:Initializing predict_model()
2022-10-07 06:10:26,855:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:10:26,855:INFO:Checking exceptions
2022-10-07 06:10:26,855:INFO:Preloading libraries
2022-10-07 06:10:52,293:INFO:Initializing predict_model()
2022-10-07 06:10:52,293:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:10:52,293:INFO:Checking exceptions
2022-10-07 06:10:52,293:INFO:Preloading libraries
2022-10-07 06:10:58,620:INFO:Initializing predict_model()
2022-10-07 06:10:58,620:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:10:58,620:INFO:Checking exceptions
2022-10-07 06:10:58,620:INFO:Preloading libraries
2022-10-07 06:13:46,044:INFO:Initializing predict_model()
2022-10-07 06:13:46,045:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 06:13:46,045:INFO:Checking exceptions
2022-10-07 06:13:46,045:INFO:Preloading libraries
2022-10-07 15:30:11,041:INFO:Initializing load_model()
2022-10-07 15:30:11,042:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:30:21,597:INFO:Initializing load_model()
2022-10-07 15:30:21,598:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:34:52,176:INFO:Initializing predict_model()
2022-10-07 15:34:52,177:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:34:52,177:INFO:Checking exceptions
2022-10-07 15:34:52,178:INFO:Preloading libraries
2022-10-07 15:36:50,341:INFO:Initializing load_model()
2022-10-07 15:36:50,341:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:36:59,061:INFO:Initializing load_model()
2022-10-07 15:36:59,062:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:37:21,045:INFO:Initializing predict_model()
2022-10-07 15:37:21,048:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:37:21,048:INFO:Checking exceptions
2022-10-07 15:37:21,048:INFO:Preloading libraries
2022-10-07 15:37:56,507:INFO:Initializing predict_model()
2022-10-07 15:37:56,507:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:37:56,507:INFO:Checking exceptions
2022-10-07 15:37:56,507:INFO:Preloading libraries
2022-10-07 15:40:30,093:INFO:Initializing load_model()
2022-10-07 15:40:30,093:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:40:30,532:INFO:Initializing predict_model()
2022-10-07 15:40:30,532:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:40:30,532:INFO:Checking exceptions
2022-10-07 15:40:30,532:INFO:Preloading libraries
2022-10-07 15:41:41,538:INFO:Initializing load_model()
2022-10-07 15:41:41,539:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:41:41,915:INFO:Initializing predict_model()
2022-10-07 15:41:41,916:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:41:41,916:INFO:Checking exceptions
2022-10-07 15:41:41,916:INFO:Preloading libraries
2022-10-07 15:42:21,484:INFO:Initializing load_model()
2022-10-07 15:42:21,484:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:42:21,841:INFO:Initializing predict_model()
2022-10-07 15:42:21,842:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:42:21,842:INFO:Checking exceptions
2022-10-07 15:42:21,842:INFO:Preloading libraries
2022-10-07 15:42:53,806:INFO:Initializing load_model()
2022-10-07 15:42:53,807:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:42:54,162:INFO:Initializing predict_model()
2022-10-07 15:42:54,162:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:42:54,162:INFO:Checking exceptions
2022-10-07 15:42:54,162:INFO:Preloading libraries
2022-10-07 15:45:25,112:INFO:Initializing load_model()
2022-10-07 15:45:25,112:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:45:25,569:INFO:Initializing predict_model()
2022-10-07 15:45:25,569:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:45:25,569:INFO:Checking exceptions
2022-10-07 15:45:25,569:INFO:Preloading libraries
2022-10-07 15:46:35,460:INFO:Initializing load_model()
2022-10-07 15:46:35,461:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:46:38,901:INFO:Initializing predict_model()
2022-10-07 15:46:38,909:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:46:38,909:INFO:Checking exceptions
2022-10-07 15:46:38,909:INFO:Preloading libraries
2022-10-07 15:47:57,803:INFO:Initializing load_model()
2022-10-07 15:47:57,803:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:47:58,157:INFO:Initializing predict_model()
2022-10-07 15:47:58,157:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:47:58,157:INFO:Checking exceptions
2022-10-07 15:47:58,157:INFO:Preloading libraries
2022-10-07 15:48:28,123:INFO:Initializing load_model()
2022-10-07 15:48:28,123:INFO:load_model(model_name=impact_of_news/lr, platform=None, authentication=None, verbose=True)
2022-10-07 15:48:28,496:INFO:Initializing predict_model()
2022-10-07 15:48:28,496:INFO:predict_model(estimator=Pipeline(steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=['Headline',
'Article'],
ml_usecase='classification',
target='target')),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='mean',
target_variable=None)),
('new_levels1',
New_Catagorical_Levels_in_TestData...
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='target')),
('fix_perfect', Remove_100(target='target')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough'),
['trained_model',
LogisticRegression(max_iter=1000, random_state=3631)]]), probability_threshold=None, encoded_labels=False, drift_report=False, raw_score=False, round=4, verbose=True, ml_usecase=MLUsecase.CLASSIFICATION, display=None, drift_kwargs=None)
2022-10-07 15:48:28,497:INFO:Checking exceptions
2022-10-07 15:48:28,497:INFO:Preloading libraries
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