| 2023-08-02 14:12:27,447:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-02 14:12:27,447:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-02 14:12:27,447:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-02 14:12:27,447:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-02 14:12:59,595:WARNING:/Users/macbookpro/.pyenv/versions/3.9.16/lib/python3.9/site-packages/sklearn/base.py:493: FutureWarning: The feature names should match those that were passed during fit. Starting version 1.2, an error will be raised. |
| Feature names unseen at fit time: |
| - Unnamed: 0 |
| - default |
| |
| warnings.warn(message, FutureWarning) |
|
|
| 2023-08-02 14:13:32,228:INFO:Initializing predict_model() |
| 2023-08-02 14:13:32,228:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x1780812b0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x178089430>) |
| 2023-08-02 14:13:32,229:INFO:Checking exceptions |
| 2023-08-02 14:13:32,229:INFO:Preloading libraries |
| 2023-08-02 14:13:32,229:INFO:Set up data. |
| 2023-08-02 14:13:32,236:INFO:Set up index. |
| 2023-08-02 14:14:55,424:INFO:Initializing predict_model() |
| 2023-08-02 14:14:55,424:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x1780c2310>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x1784c8940>) |
| 2023-08-02 14:14:55,425:INFO:Checking exceptions |
| 2023-08-02 14:14:55,425:INFO:Preloading libraries |
| 2023-08-02 14:14:55,425:INFO:Set up data. |
| 2023-08-02 14:14:55,430:INFO:Set up index. |
| 2023-08-03 07:20:31,034:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 07:20:31,035:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 07:20:31,035:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 07:20:31,035:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 07:20:41,626:INFO:Initializing predict_model() |
| 2023-08-03 07:20:41,626:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x16da13e20>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x17e0d9160>) |
| 2023-08-03 07:20:41,626:INFO:Checking exceptions |
| 2023-08-03 07:20:41,626:INFO:Preloading libraries |
| 2023-08-03 07:20:41,629:INFO:Set up data. |
| 2023-08-03 07:20:41,637:INFO:Set up index. |
| 2023-08-03 07:21:17,448:INFO:Initializing predict_model() |
| 2023-08-03 07:21:17,449:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x16dab19d0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x17e0d9dc0>) |
| 2023-08-03 07:21:17,449:INFO:Checking exceptions |
| 2023-08-03 07:21:17,449:INFO:Preloading libraries |
| 2023-08-03 07:21:17,449:INFO:Set up data. |
| 2023-08-03 07:21:17,455:INFO:Set up index. |
| 2023-08-03 07:22:14,797:INFO:Initializing predict_model() |
| 2023-08-03 07:22:14,797:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x16da4d670>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x16e275a60>) |
| 2023-08-03 07:22:14,797:INFO:Checking exceptions |
| 2023-08-03 07:22:14,797:INFO:Preloading libraries |
| 2023-08-03 07:22:14,798:INFO:Set up data. |
| 2023-08-03 07:22:14,801:INFO:Set up index. |
| 2023-08-03 10:58:46,504:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:58:46,505:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:58:46,505:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:58:46,505:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:58:55,777:WARNING:/Users/macbookpro/.pyenv/versions/3.9.16/lib/python3.9/site-packages/sklearn/base.py:493: FutureWarning: The feature names should match those that were passed during fit. Starting version 1.2, an error will be raised. |
| Feature names unseen at fit time: |
| - Unnamed: 0 |
|
|
| warnings.warn(message, FutureWarning) |
|
|
| 2023-08-03 10:59:21,797:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:59:21,797:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:59:21,797:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:59:21,797:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-03 10:59:29,378:INFO:Initializing predict_model() |
| 2023-08-03 10:59:29,379:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x15f564c70>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x15f4a9280>) |
| 2023-08-03 10:59:29,379:INFO:Checking exceptions |
| 2023-08-03 10:59:29,379:INFO:Preloading libraries |
| 2023-08-03 10:59:29,379:INFO:Set up data. |
| 2023-08-03 10:59:29,386:INFO:Set up index. |
| 2023-08-04 07:20:45,982:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:20:45,982:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:20:45,982:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:20:45,982:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:20:53,862:INFO:Initializing predict_model() |
| 2023-08-04 07:20:53,862:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x28219fd00>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x282183310>) |
| 2023-08-04 07:20:53,862:INFO:Checking exceptions |
| 2023-08-04 07:20:53,862:INFO:Preloading libraries |
| 2023-08-04 07:20:53,864:INFO:Set up data. |
| 2023-08-04 07:20:53,873:INFO:Set up index. |
| 2023-08-04 07:22:16,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:22:16,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:22:16,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:22:16,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:23:22,156:INFO:Initializing predict_model() |
| 2023-08-04 07:23:22,157:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x1715802e0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x171536dc0>) |
| 2023-08-04 07:23:22,157:INFO:Checking exceptions |
| 2023-08-04 07:23:22,157:INFO:Preloading libraries |
| 2023-08-04 07:23:22,159:INFO:Set up data. |
| 2023-08-04 07:23:22,167:INFO:Set up index. |
| 2023-08-04 07:30:25,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:30:25,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:30:25,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:30:25,503:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-04 07:30:33,393:INFO:Initializing predict_model() |
| 2023-08-04 07:30:33,393:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x2847f71c0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x2847c2550>) |
| 2023-08-04 07:30:33,393:INFO:Checking exceptions |
| 2023-08-04 07:30:33,393:INFO:Preloading libraries |
| 2023-08-04 07:30:33,395:INFO:Set up data. |
| 2023-08-04 07:30:33,403:INFO:Set up index. |
| 2023-08-08 22:18:02,376:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:18:02,376:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:18:02,376:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:18:02,376:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:26:27,519:INFO:Initializing predict_model() |
| 2023-08-08 22:26:27,519:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x285b30f70>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x2857929d0>) |
| 2023-08-08 22:26:27,519:INFO:Checking exceptions |
| 2023-08-08 22:26:27,519:INFO:Preloading libraries |
| 2023-08-08 22:26:27,522:INFO:Set up data. |
| 2023-08-08 22:26:27,534:INFO:Set up index. |
| 2023-08-08 22:27:05,991:INFO:Initializing predict_model() |
| 2023-08-08 22:27:05,992:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x16e1b5100>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x16e1c3550>) |
| 2023-08-08 22:27:05,992:INFO:Checking exceptions |
| 2023-08-08 22:27:05,992:INFO:Preloading libraries |
| 2023-08-08 22:27:05,992:INFO:Set up data. |
| 2023-08-08 22:27:05,998:INFO:Set up index. |
| 2023-08-08 22:45:35,556:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:45:35,556:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:45:35,556:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:45:35,556:WARNING: |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. |
| 2023-08-08 22:45:36,129:INFO:Initializing load_model() |
| 2023-08-08 22:45:36,129:INFO:load_model(model_name=model, platform=None, authentication=None, verbose=True) |
| 2023-08-08 22:45:39,904:INFO:Initializing load_model() |
| 2023-08-08 22:45:39,905:INFO:load_model(model_name=model, platform=None, authentication=None, verbose=True) |
| 2023-08-08 22:45:39,951:INFO:Initializing predict_model() |
| 2023-08-08 22:45:39,951:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x281b923d0>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x281bb7f70>) |
| 2023-08-08 22:45:39,952:INFO:Checking exceptions |
| 2023-08-08 22:45:39,952:INFO:Preloading libraries |
| 2023-08-08 22:45:39,954:INFO:Set up data. |
| 2023-08-08 22:45:39,960:INFO:Set up index. |
| 2023-08-08 22:46:02,637:INFO:Initializing load_model() |
| 2023-08-08 22:46:02,638:INFO:load_model(model_name=model, platform=None, authentication=None, verbose=True) |
| 2023-08-08 22:46:05,250:INFO:Initializing load_model() |
| 2023-08-08 22:46:05,250:INFO:load_model(model_name=model, platform=None, authentication=None, verbose=True) |
| 2023-08-08 22:46:05,281:INFO:Initializing predict_model() |
| 2023-08-08 22:46:05,281:INFO:predict_model(self=<pycaret.classification.oop.ClassificationExperiment object at 0x133e7d250>, estimator=Pipeline(memory=FastMemory(location=/var/folders/vh/81ldn_315vdf1b2_lnntkb080000gn/T/joblib), |
| steps=[('combine', |
| TransformerWrapper(transformer=TransformerWrapper(include=['ed'], |
| transformer=Combine()))), |
| ('remove outlier', |
| TransformerWrapper(transformer=TransformerWrapper(transformer=RemoveOutliers(random_state=42)))), |
| ('normalize', |
| TransformerWrapper(transformer=TransformerWrapper(exclude=['ed', |
| 'age'], |
| transformer=RobustScaler()))), |
| ('actual_estimator', |
| LogisticRegression(C=8.956999999999999, |
| class_weight='balanced', max_iter=1000, |
| random_state=42))]), probability_threshold=None, encoded_labels=False, raw_score=False, round=4, verbose=True, ml_usecase=None, preprocess=True, encode_labels=<function _SupervisedExperiment.predict_model.<locals>.encode_labels at 0x133e57ca0>) |
| 2023-08-08 22:46:05,281:INFO:Checking exceptions |
| 2023-08-08 22:46:05,281:INFO:Preloading libraries |
| 2023-08-08 22:46:05,282:INFO:Set up data. |
| 2023-08-08 22:46:05,286:INFO:Set up index. |
|
|
