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logs.log
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2022-06-06 13:43:31,393:INFO:PyCaret Supervised Module
2022-06-06 13:43:31,394:INFO:ML Usecase: regression
2022-06-06 13:43:31,394:INFO:version 2.3.10
2022-06-06 13:43:31,395:INFO:Initializing setup()
2022-06-06 13:43:31,395:INFO:setup(target=Close, ml_usecase=regression, available_plots={'parameter': 'Hyperparameters', 'residuals': 'Residuals', 'error': 'Prediction Error', 'cooks': 'Cooks Distance', 'rfe': 'Feature Selection', 'learning': 'Learning Curve', 'manifold': 'Manifold Learning', 'vc': 'Validation Curve', 'feature': 'Feature Importance', 'feature_all': 'Feature Importance (All)', 'tree': 'Decision Tree', 'residuals_interactive': 'Interactive Residuals'}, train_size=0.7, test_data=None, preprocess=True, imputation_type=simple, iterative_imputation_iters=5, categorical_features=None, categorical_imputation=constant, categorical_iterative_imputer=lightgbm, ordinal_features=None, high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, numeric_iterative_imputer=lightgbm, date_features=None, ignore_features=None, normalize=False, normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear, pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05, remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=True, create_clusters=False, cluster_iter=20, polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None, group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_selection_method=classic, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, fix_imbalance=False, fix_imbalance_method=None, transform_target=False, transform_target_method=box-cox, data_split_shuffle=True, data_split_stratify=False, fold_strategy=kfold, fold=10, fold_shuffle=False, fold_groups=None, n_jobs=-1, use_gpu=False, custom_pipeline=None, html=True, session_id=123, log_experiment=False, experiment_name=None, experiment_custom_tags=None, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False, profile_kwargs=None, display=None)
2022-06-06 13:43:31,398:INFO:Checking environment
2022-06-06 13:43:31,398:INFO:python_version: 3.9.7
2022-06-06 13:43:31,398:INFO:python_build: ('default', 'Sep 16 2021 16:59:28')
2022-06-06 13:43:31,398:INFO:machine: AMD64
2022-06-06 13:43:31,398:INFO:platform: Windows-10-10.0.22000-SP0
2022-06-06 13:43:31,398:INFO:Memory: svmem(total=8412778496, available=2398437376, percent=71.5, used=6014341120, free=2398437376)
2022-06-06 13:43:31,398:INFO:Physical Core: 4
2022-06-06 13:43:31,398:INFO:Logical Core: 8
2022-06-06 13:43:31,398:INFO:Checking libraries
2022-06-06 13:43:31,398:INFO:pd==1.4.2
2022-06-06 13:43:31,398:INFO:numpy==1.19.5
2022-06-06 13:43:31,398:INFO:sklearn==0.23.2
2022-06-06 13:43:31,398:INFO:lightgbm==3.3.2
2022-06-06 13:43:31,572:INFO:catboost==1.0.6
2022-06-06 13:43:31,572:INFO:xgboost==1.6.1
2022-06-06 13:43:31,572:INFO:mlflow==1.26.1
2022-06-06 13:43:31,572:INFO:Checking Exceptions
2022-06-06 13:43:31,572:INFO:Declaring global variables
2022-06-06 13:43:31,572:INFO:USI: c244
2022-06-06 13:43:31,572:INFO:pycaret_globals: {'_all_models', '_all_metrics', 'pycaret_globals', 'data_before_preprocess', 'seed', 'prep_pipe', 'exp_name_log', 'y_train', 'master_model_container', 'log_plots_param', 'create_model_container', 'fold_groups_param', 'fold_param', 'iterative_imputation_iters_param', 'USI', '_all_models_internal', 'fix_imbalance_method_param', 'imputation_classifier', 'y_test', 'y', '_gpu_n_jobs_param', 'fold_groups_param_full', 'X_train', 'experiment__', 'logging_param', '_internal_pipeline', 'transform_target_param', 'dashboard_logger', 'gpu_param', 'display_container', 'html_param', 'stratify_param', 'n_jobs_param', 'fold_shuffle_param', 'X', 'fix_imbalance_param', 'fold_generator', 'imputation_regressor', 'X_test', '_available_plots', '_ml_usecase', 'transform_target_method_param', 'target_param'}
2022-06-06 13:43:31,572:INFO:Preparing display monitor
2022-06-06 13:43:31,572:INFO:Preparing display monitor
2022-06-06 13:43:31,583:INFO:Importing libraries
2022-06-06 13:43:31,583:INFO:Copying data for preprocessing
2022-06-06 13:43:31,589:INFO:Declaring preprocessing parameters
2022-06-06 13:43:31,590:INFO:Creating preprocessing pipeline
2022-06-06 13:43:31,594:INFO:Preprocessing pipeline created successfully
2022-06-06 13:43:31,595:ERROR:(Process Exit): setup has been interupted with user command 'quit'. setup must rerun.
2022-06-06 13:43:31,595:INFO:Creating global containers
2022-06-06 13:43:31,597:INFO:Internal pipeline: Pipeline(memory=None, steps=[('empty_step', 'passthrough')], verbose=False)
2022-06-06 13:43:43,393:INFO:Creating grid variables
2022-06-06 13:43:43,405:INFO:create_model_container: 0
2022-06-06 13:43:43,405:INFO:master_model_container: 0
2022-06-06 13:43:43,406:INFO:display_container: 1
2022-06-06 13:43:43,410:INFO:Pipeline(memory=None,
steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=[],
display_types=True, features_todrop=[],
id_columns=[], ml_usecase='regression',
numerical_features=[], target='Close',
time_features=[])),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='...
('scaling', 'passthrough'), ('P_transform', 'passthrough'),
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='Close')),
('fix_perfect', Remove_100(target='Close')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough')],
verbose=False)
2022-06-06 13:43:43,410:INFO:setup() succesfully completed......................................
2022-06-06 13:45:01,756:INFO:Initializing compare_models()
2022-06-06 13:45:01,756:INFO:compare_models(include=None, fold=None, round=4, cross_validation=True, sort=R2, n_select=3, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, display=None, exclude=None)
2022-06-06 13:45:01,756:INFO:Checking exceptions
2022-06-06 13:45:01,756:INFO:Preparing display monitor
2022-06-06 13:45:01,757:INFO:Preparing display monitor
2022-06-06 13:45:01,789:INFO:Initializing Linear Regression
2022-06-06 13:45:01,789:INFO:Total runtime is 0.0 minutes
2022-06-06 13:45:01,802:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:01,803:INFO:Initializing create_model()
2022-06-06 13:45:01,803:INFO:create_model(estimator=lr, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:01,803:INFO:Checking exceptions
2022-06-06 13:45:01,803:INFO:Importing libraries
2022-06-06 13:45:01,803:INFO:Copying training dataset
2022-06-06 13:45:01,804:INFO:Defining folds
2022-06-06 13:45:01,805:INFO:Declaring metric variables
2022-06-06 13:45:01,813:INFO:Importing untrained model
2022-06-06 13:45:01,822:INFO:Linear Regression Imported succesfully
2022-06-06 13:45:01,839:INFO:Starting cross validation
2022-06-06 13:45:01,843:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:08,041:INFO:Calculating mean and std
2022-06-06 13:45:08,043:INFO:Creating metrics dataframe
2022-06-06 13:45:08,074:INFO:Uploading results into container
2022-06-06 13:45:08,075:INFO:Uploading model into container now
2022-06-06 13:45:08,075:INFO:create_model_container: 1
2022-06-06 13:45:08,075:INFO:master_model_container: 1
2022-06-06 13:45:08,075:INFO:display_container: 2
2022-06-06 13:45:08,075:INFO:LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False)
2022-06-06 13:45:08,075:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:08,171:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:08,172:INFO:Creating metrics dataframe
2022-06-06 13:45:08,202:INFO:Initializing Lasso Regression
2022-06-06 13:45:08,202:INFO:Total runtime is 0.10687928994496664 minutes
2022-06-06 13:45:08,212:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:08,212:INFO:Initializing create_model()
2022-06-06 13:45:08,213:INFO:create_model(estimator=lasso, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:08,213:INFO:Checking exceptions
2022-06-06 13:45:08,213:INFO:Importing libraries
2022-06-06 13:45:08,213:INFO:Copying training dataset
2022-06-06 13:45:08,214:INFO:Defining folds
2022-06-06 13:45:08,215:INFO:Declaring metric variables
2022-06-06 13:45:08,223:INFO:Importing untrained model
2022-06-06 13:45:08,231:INFO:Lasso Regression Imported succesfully
2022-06-06 13:45:08,247:INFO:Starting cross validation
2022-06-06 13:45:08,247:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:08,296:INFO:Calculating mean and std
2022-06-06 13:45:08,296:INFO:Creating metrics dataframe
2022-06-06 13:45:08,312:INFO:Uploading results into container
2022-06-06 13:45:08,312:INFO:Uploading model into container now
2022-06-06 13:45:08,313:INFO:create_model_container: 2
2022-06-06 13:45:08,313:INFO:master_model_container: 2
2022-06-06 13:45:08,313:INFO:display_container: 2
2022-06-06 13:45:08,313:INFO:Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,
normalize=False, positive=False, precompute=False, random_state=123,
selection='cyclic', tol=0.0001, warm_start=False)
2022-06-06 13:45:08,313:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:08,383:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:08,384:INFO:Creating metrics dataframe
2022-06-06 13:45:08,414:INFO:Initializing Ridge Regression
2022-06-06 13:45:08,414:INFO:Total runtime is 0.11041266918182373 minutes
2022-06-06 13:45:08,423:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:08,423:INFO:Initializing create_model()
2022-06-06 13:45:08,423:INFO:create_model(estimator=ridge, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:08,423:INFO:Checking exceptions
2022-06-06 13:45:08,423:INFO:Importing libraries
2022-06-06 13:45:08,423:INFO:Copying training dataset
2022-06-06 13:45:08,424:INFO:Defining folds
2022-06-06 13:45:08,424:INFO:Declaring metric variables
2022-06-06 13:45:08,432:INFO:Importing untrained model
2022-06-06 13:45:08,442:INFO:Ridge Regression Imported succesfully
2022-06-06 13:45:08,458:INFO:Starting cross validation
2022-06-06 13:45:08,459:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:08,506:INFO:Calculating mean and std
2022-06-06 13:45:08,507:INFO:Creating metrics dataframe
2022-06-06 13:45:08,523:INFO:Uploading results into container
2022-06-06 13:45:08,523:INFO:Uploading model into container now
2022-06-06 13:45:08,523:INFO:create_model_container: 3
2022-06-06 13:45:08,523:INFO:master_model_container: 3
2022-06-06 13:45:08,523:INFO:display_container: 2
2022-06-06 13:45:08,524:INFO:Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
normalize=False, random_state=123, solver='auto', tol=0.001)
2022-06-06 13:45:08,524:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:08,594:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:08,594:INFO:Creating metrics dataframe
2022-06-06 13:45:08,622:INFO:Initializing Elastic Net
2022-06-06 13:45:08,623:INFO:Total runtime is 0.1138903776804606 minutes
2022-06-06 13:45:08,632:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:08,633:INFO:Initializing create_model()
2022-06-06 13:45:08,633:INFO:create_model(estimator=en, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:08,633:INFO:Checking exceptions
2022-06-06 13:45:08,633:INFO:Importing libraries
2022-06-06 13:45:08,633:INFO:Copying training dataset
2022-06-06 13:45:08,634:INFO:Defining folds
2022-06-06 13:45:08,634:INFO:Declaring metric variables
2022-06-06 13:45:08,641:INFO:Importing untrained model
2022-06-06 13:45:08,648:INFO:Elastic Net Imported succesfully
2022-06-06 13:45:08,667:INFO:Starting cross validation
2022-06-06 13:45:08,668:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:08,713:INFO:Calculating mean and std
2022-06-06 13:45:08,714:INFO:Creating metrics dataframe
2022-06-06 13:45:08,729:INFO:Uploading results into container
2022-06-06 13:45:08,729:INFO:Uploading model into container now
2022-06-06 13:45:08,729:INFO:create_model_container: 4
2022-06-06 13:45:08,729:INFO:master_model_container: 4
2022-06-06 13:45:08,729:INFO:display_container: 2
2022-06-06 13:45:08,730:INFO:ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,
max_iter=1000, normalize=False, positive=False, precompute=False,
random_state=123, selection='cyclic', tol=0.0001, warm_start=False)
2022-06-06 13:45:08,730:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:08,801:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:08,801:INFO:Creating metrics dataframe
2022-06-06 13:45:08,832:INFO:Initializing Least Angle Regression
2022-06-06 13:45:08,832:INFO:Total runtime is 0.11737635135650634 minutes
2022-06-06 13:45:08,839:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:08,840:INFO:Initializing create_model()
2022-06-06 13:45:08,840:INFO:create_model(estimator=lar, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:08,840:INFO:Checking exceptions
2022-06-06 13:45:08,840:INFO:Importing libraries
2022-06-06 13:45:08,841:INFO:Copying training dataset
2022-06-06 13:45:08,841:INFO:Defining folds
2022-06-06 13:45:08,841:INFO:Declaring metric variables
2022-06-06 13:45:08,848:INFO:Importing untrained model
2022-06-06 13:45:08,857:INFO:Least Angle Regression Imported succesfully
2022-06-06 13:45:08,875:INFO:Starting cross validation
2022-06-06 13:45:08,875:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:08,919:INFO:Calculating mean and std
2022-06-06 13:45:08,920:INFO:Creating metrics dataframe
2022-06-06 13:45:08,937:INFO:Uploading results into container
2022-06-06 13:45:08,937:INFO:Uploading model into container now
2022-06-06 13:45:08,937:INFO:create_model_container: 5
2022-06-06 13:45:08,937:INFO:master_model_container: 5
2022-06-06 13:45:08,937:INFO:display_container: 2
2022-06-06 13:45:08,938:INFO:Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,
jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',
random_state=123, verbose=False)
2022-06-06 13:45:08,938:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:09,007:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:09,007:INFO:Creating metrics dataframe
2022-06-06 13:45:09,036:INFO:Initializing Lasso Least Angle Regression
2022-06-06 13:45:09,036:INFO:Total runtime is 0.12076800266901651 minutes
2022-06-06 13:45:09,043:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:09,043:INFO:Initializing create_model()
2022-06-06 13:45:09,043:INFO:create_model(estimator=llar, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:09,043:INFO:Checking exceptions
2022-06-06 13:45:09,044:INFO:Importing libraries
2022-06-06 13:45:09,044:INFO:Copying training dataset
2022-06-06 13:45:09,044:INFO:Defining folds
2022-06-06 13:45:09,045:INFO:Declaring metric variables
2022-06-06 13:45:09,053:INFO:Importing untrained model
2022-06-06 13:45:09,060:INFO:Lasso Least Angle Regression Imported succesfully
2022-06-06 13:45:09,076:INFO:Starting cross validation
2022-06-06 13:45:09,077:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:09,121:INFO:Calculating mean and std
2022-06-06 13:45:09,121:INFO:Creating metrics dataframe
2022-06-06 13:45:09,139:INFO:Uploading results into container
2022-06-06 13:45:09,139:INFO:Uploading model into container now
2022-06-06 13:45:09,139:INFO:create_model_container: 6
2022-06-06 13:45:09,139:INFO:master_model_container: 6
2022-06-06 13:45:09,139:INFO:display_container: 2
2022-06-06 13:45:09,139:INFO:LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,
fit_path=True, jitter=None, max_iter=500, normalize=True,
positive=False, precompute='auto', random_state=123, verbose=False)
2022-06-06 13:45:09,139:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:09,211:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:09,211:INFO:Creating metrics dataframe
2022-06-06 13:45:09,241:INFO:Initializing Orthogonal Matching Pursuit
2022-06-06 13:45:09,241:INFO:Total runtime is 0.12419243653615314 minutes
2022-06-06 13:45:09,251:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:09,252:INFO:Initializing create_model()
2022-06-06 13:45:09,252:INFO:create_model(estimator=omp, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:09,252:INFO:Checking exceptions
2022-06-06 13:45:09,252:INFO:Importing libraries
2022-06-06 13:45:09,252:INFO:Copying training dataset
2022-06-06 13:45:09,253:INFO:Defining folds
2022-06-06 13:45:09,253:INFO:Declaring metric variables
2022-06-06 13:45:09,260:INFO:Importing untrained model
2022-06-06 13:45:09,267:INFO:Orthogonal Matching Pursuit Imported succesfully
2022-06-06 13:45:09,283:INFO:Starting cross validation
2022-06-06 13:45:09,283:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:09,336:INFO:Calculating mean and std
2022-06-06 13:45:09,336:INFO:Creating metrics dataframe
2022-06-06 13:45:09,353:INFO:Uploading results into container
2022-06-06 13:45:09,354:INFO:Uploading model into container now
2022-06-06 13:45:09,354:INFO:create_model_container: 7
2022-06-06 13:45:09,354:INFO:master_model_container: 7
2022-06-06 13:45:09,354:INFO:display_container: 2
2022-06-06 13:45:09,354:INFO:OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,
normalize=True, precompute='auto', tol=None)
2022-06-06 13:45:09,354:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:09,422:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:09,422:INFO:Creating metrics dataframe
2022-06-06 13:45:09,448:INFO:Initializing Bayesian Ridge
2022-06-06 13:45:09,448:INFO:Total runtime is 0.12763959566752114 minutes
2022-06-06 13:45:09,456:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:09,456:INFO:Initializing create_model()
2022-06-06 13:45:09,456:INFO:create_model(estimator=br, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:09,456:INFO:Checking exceptions
2022-06-06 13:45:09,457:INFO:Importing libraries
2022-06-06 13:45:09,457:INFO:Copying training dataset
2022-06-06 13:45:09,457:INFO:Defining folds
2022-06-06 13:45:09,457:INFO:Declaring metric variables
2022-06-06 13:45:09,464:INFO:Importing untrained model
2022-06-06 13:45:09,471:INFO:Bayesian Ridge Imported succesfully
2022-06-06 13:45:09,485:INFO:Starting cross validation
2022-06-06 13:45:09,486:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:09,531:INFO:Calculating mean and std
2022-06-06 13:45:09,531:INFO:Creating metrics dataframe
2022-06-06 13:45:09,545:INFO:Uploading results into container
2022-06-06 13:45:09,545:INFO:Uploading model into container now
2022-06-06 13:45:09,546:INFO:create_model_container: 8
2022-06-06 13:45:09,546:INFO:master_model_container: 8
2022-06-06 13:45:09,546:INFO:display_container: 2
2022-06-06 13:45:09,546:INFO:BayesianRidge(alpha_1=1e-06, alpha_2=1e-06, alpha_init=None,
compute_score=False, copy_X=True, fit_intercept=True,
lambda_1=1e-06, lambda_2=1e-06, lambda_init=None, n_iter=300,
normalize=False, tol=0.001, verbose=False)
2022-06-06 13:45:09,546:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:09,617:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:09,617:INFO:Creating metrics dataframe
2022-06-06 13:45:09,648:INFO:Initializing Passive Aggressive Regressor
2022-06-06 13:45:09,648:INFO:Total runtime is 0.13097441991170247 minutes
2022-06-06 13:45:09,656:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:09,656:INFO:Initializing create_model()
2022-06-06 13:45:09,656:INFO:create_model(estimator=par, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:09,656:INFO:Checking exceptions
2022-06-06 13:45:09,656:INFO:Importing libraries
2022-06-06 13:45:09,656:INFO:Copying training dataset
2022-06-06 13:45:09,657:INFO:Defining folds
2022-06-06 13:45:09,659:INFO:Declaring metric variables
2022-06-06 13:45:09,666:INFO:Importing untrained model
2022-06-06 13:45:09,673:INFO:Passive Aggressive Regressor Imported succesfully
2022-06-06 13:45:09,688:INFO:Starting cross validation
2022-06-06 13:45:09,688:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:09,738:INFO:Calculating mean and std
2022-06-06 13:45:09,739:INFO:Creating metrics dataframe
2022-06-06 13:45:09,755:INFO:Uploading results into container
2022-06-06 13:45:09,756:INFO:Uploading model into container now
2022-06-06 13:45:09,756:INFO:create_model_container: 9
2022-06-06 13:45:09,756:INFO:master_model_container: 9
2022-06-06 13:45:09,756:INFO:display_container: 2
2022-06-06 13:45:09,756:INFO:PassiveAggressiveRegressor(C=1.0, average=False, early_stopping=False,
epsilon=0.1, fit_intercept=True,
loss='epsilon_insensitive', max_iter=1000,
n_iter_no_change=5, random_state=123, shuffle=True,
tol=0.001, validation_fraction=0.1, verbose=0,
warm_start=False)
2022-06-06 13:45:09,756:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:09,825:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:09,826:INFO:Creating metrics dataframe
2022-06-06 13:45:09,855:INFO:Initializing Huber Regressor
2022-06-06 13:45:09,855:INFO:Total runtime is 0.1344275156656901 minutes
2022-06-06 13:45:09,862:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:09,862:INFO:Initializing create_model()
2022-06-06 13:45:09,862:INFO:create_model(estimator=huber, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:09,862:INFO:Checking exceptions
2022-06-06 13:45:09,862:INFO:Importing libraries
2022-06-06 13:45:09,863:INFO:Copying training dataset
2022-06-06 13:45:09,863:INFO:Defining folds
2022-06-06 13:45:09,864:INFO:Declaring metric variables
2022-06-06 13:45:09,871:INFO:Importing untrained model
2022-06-06 13:45:09,878:INFO:Huber Regressor Imported succesfully
2022-06-06 13:45:09,893:INFO:Starting cross validation
2022-06-06 13:45:09,894:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:09,948:INFO:Calculating mean and std
2022-06-06 13:45:09,949:INFO:Creating metrics dataframe
2022-06-06 13:45:09,965:INFO:Uploading results into container
2022-06-06 13:45:09,965:INFO:Uploading model into container now
2022-06-06 13:45:09,965:INFO:create_model_container: 10
2022-06-06 13:45:09,965:INFO:master_model_container: 10
2022-06-06 13:45:09,965:INFO:display_container: 2
2022-06-06 13:45:09,966:INFO:HuberRegressor(alpha=0.0001, epsilon=1.35, fit_intercept=True, max_iter=100,
tol=1e-05, warm_start=False)
2022-06-06 13:45:09,966:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:10,035:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:10,035:INFO:Creating metrics dataframe
2022-06-06 13:45:10,067:INFO:Initializing K Neighbors Regressor
2022-06-06 13:45:10,067:INFO:Total runtime is 0.1379592776298523 minutes
2022-06-06 13:45:10,074:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:10,075:INFO:Initializing create_model()
2022-06-06 13:45:10,075:INFO:create_model(estimator=knn, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:10,075:INFO:Checking exceptions
2022-06-06 13:45:10,075:INFO:Importing libraries
2022-06-06 13:45:10,075:INFO:Copying training dataset
2022-06-06 13:45:10,076:INFO:Defining folds
2022-06-06 13:45:10,076:INFO:Declaring metric variables
2022-06-06 13:45:10,084:INFO:Importing untrained model
2022-06-06 13:45:10,092:INFO:K Neighbors Regressor Imported succesfully
2022-06-06 13:45:10,109:INFO:Starting cross validation
2022-06-06 13:45:10,109:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:10,170:INFO:Calculating mean and std
2022-06-06 13:45:10,170:INFO:Creating metrics dataframe
2022-06-06 13:45:10,188:INFO:Uploading results into container
2022-06-06 13:45:10,188:INFO:Uploading model into container now
2022-06-06 13:45:10,188:INFO:create_model_container: 11
2022-06-06 13:45:10,188:INFO:master_model_container: 11
2022-06-06 13:45:10,188:INFO:display_container: 2
2022-06-06 13:45:10,189:INFO:KNeighborsRegressor(algorithm='auto', leaf_size=30, metric='minkowski',
metric_params=None, n_jobs=-1, n_neighbors=5, p=2,
weights='uniform')
2022-06-06 13:45:10,189:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:10,260:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:10,260:INFO:Creating metrics dataframe
2022-06-06 13:45:10,294:INFO:Initializing Decision Tree Regressor
2022-06-06 13:45:10,295:INFO:Total runtime is 0.1417596419652303 minutes
2022-06-06 13:45:10,304:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:10,305:INFO:Initializing create_model()
2022-06-06 13:45:10,305:INFO:create_model(estimator=dt, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:10,305:INFO:Checking exceptions
2022-06-06 13:45:10,305:INFO:Importing libraries
2022-06-06 13:45:10,305:INFO:Copying training dataset
2022-06-06 13:45:10,306:INFO:Defining folds
2022-06-06 13:45:10,306:INFO:Declaring metric variables
2022-06-06 13:45:10,313:INFO:Importing untrained model
2022-06-06 13:45:10,321:INFO:Decision Tree Regressor Imported succesfully
2022-06-06 13:45:10,336:INFO:Starting cross validation
2022-06-06 13:45:10,337:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:10,387:INFO:Calculating mean and std
2022-06-06 13:45:10,387:INFO:Creating metrics dataframe
2022-06-06 13:45:10,404:INFO:Uploading results into container
2022-06-06 13:45:10,404:INFO:Uploading model into container now
2022-06-06 13:45:10,404:INFO:create_model_container: 12
2022-06-06 13:45:10,404:INFO:master_model_container: 12
2022-06-06 13:45:10,404:INFO:display_container: 2
2022-06-06 13:45:10,404:INFO:DecisionTreeRegressor(ccp_alpha=0.0, criterion='mse', max_depth=None,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, presort='deprecated',
random_state=123, splitter='best')
2022-06-06 13:45:10,405:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:10,477:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:10,477:INFO:Creating metrics dataframe
2022-06-06 13:45:10,512:INFO:Initializing Random Forest Regressor
2022-06-06 13:45:10,512:INFO:Total runtime is 0.14537219603856405 minutes
2022-06-06 13:45:10,520:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:10,520:INFO:Initializing create_model()
2022-06-06 13:45:10,520:INFO:create_model(estimator=rf, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:10,520:INFO:Checking exceptions
2022-06-06 13:45:10,521:INFO:Importing libraries
2022-06-06 13:45:10,521:INFO:Copying training dataset
2022-06-06 13:45:10,521:INFO:Defining folds
2022-06-06 13:45:10,521:INFO:Declaring metric variables
2022-06-06 13:45:10,527:INFO:Importing untrained model
2022-06-06 13:45:10,535:INFO:Random Forest Regressor Imported succesfully
2022-06-06 13:45:10,552:INFO:Starting cross validation
2022-06-06 13:45:10,553:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:11,173:INFO:Calculating mean and std
2022-06-06 13:45:11,174:INFO:Creating metrics dataframe
2022-06-06 13:45:11,190:INFO:Uploading results into container
2022-06-06 13:45:11,190:INFO:Uploading model into container now
2022-06-06 13:45:11,190:INFO:create_model_container: 13
2022-06-06 13:45:11,190:INFO:master_model_container: 13
2022-06-06 13:45:11,190:INFO:display_container: 2
2022-06-06 13:45:11,191:INFO:RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=-1, oob_score=False,
random_state=123, verbose=0, warm_start=False)
2022-06-06 13:45:11,191:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:11,263:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:11,264:INFO:Creating metrics dataframe
2022-06-06 13:45:11,296:INFO:Initializing Extra Trees Regressor
2022-06-06 13:45:11,296:INFO:Total runtime is 0.15843886534372967 minutes
2022-06-06 13:45:11,304:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:11,305:INFO:Initializing create_model()
2022-06-06 13:45:11,305:INFO:create_model(estimator=et, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:11,305:INFO:Checking exceptions
2022-06-06 13:45:11,305:INFO:Importing libraries
2022-06-06 13:45:11,305:INFO:Copying training dataset
2022-06-06 13:45:11,306:INFO:Defining folds
2022-06-06 13:45:11,306:INFO:Declaring metric variables
2022-06-06 13:45:11,313:INFO:Importing untrained model
2022-06-06 13:45:11,320:INFO:Extra Trees Regressor Imported succesfully
2022-06-06 13:45:11,336:INFO:Starting cross validation
2022-06-06 13:45:11,336:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:11,824:INFO:Calculating mean and std
2022-06-06 13:45:11,825:INFO:Creating metrics dataframe
2022-06-06 13:45:11,841:INFO:Uploading results into container
2022-06-06 13:45:11,841:INFO:Uploading model into container now
2022-06-06 13:45:11,841:INFO:create_model_container: 14
2022-06-06 13:45:11,841:INFO:master_model_container: 14
2022-06-06 13:45:11,841:INFO:display_container: 2
2022-06-06 13:45:11,841:INFO:ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=-1, oob_score=False,
random_state=123, verbose=0, warm_start=False)
2022-06-06 13:45:11,841:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:11,912:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:11,912:INFO:Creating metrics dataframe
2022-06-06 13:45:11,948:INFO:Initializing AdaBoost Regressor
2022-06-06 13:45:11,948:INFO:Total runtime is 0.1693043351173401 minutes
2022-06-06 13:45:11,956:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:11,956:INFO:Initializing create_model()
2022-06-06 13:45:11,956:INFO:create_model(estimator=ada, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:11,956:INFO:Checking exceptions
2022-06-06 13:45:11,956:INFO:Importing libraries
2022-06-06 13:45:11,957:INFO:Copying training dataset
2022-06-06 13:45:11,957:INFO:Defining folds
2022-06-06 13:45:11,957:INFO:Declaring metric variables
2022-06-06 13:45:11,963:INFO:Importing untrained model
2022-06-06 13:45:11,971:INFO:AdaBoost Regressor Imported succesfully
2022-06-06 13:45:11,986:INFO:Starting cross validation
2022-06-06 13:45:11,987:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:12,194:INFO:Calculating mean and std
2022-06-06 13:45:12,195:INFO:Creating metrics dataframe
2022-06-06 13:45:12,212:INFO:Uploading results into container
2022-06-06 13:45:12,212:INFO:Uploading model into container now
2022-06-06 13:45:12,212:INFO:create_model_container: 15
2022-06-06 13:45:12,212:INFO:master_model_container: 15
2022-06-06 13:45:12,212:INFO:display_container: 2
2022-06-06 13:45:12,212:INFO:AdaBoostRegressor(base_estimator=None, learning_rate=1.0, loss='linear',
n_estimators=50, random_state=123)
2022-06-06 13:45:12,212:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:12,286:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:12,287:INFO:Creating metrics dataframe
2022-06-06 13:45:12,317:INFO:Initializing Gradient Boosting Regressor
2022-06-06 13:45:12,318:INFO:Total runtime is 0.17547299464543661 minutes
2022-06-06 13:45:12,326:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:12,327:INFO:Initializing create_model()
2022-06-06 13:45:12,327:INFO:create_model(estimator=gbr, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:12,327:INFO:Checking exceptions
2022-06-06 13:45:12,327:INFO:Importing libraries
2022-06-06 13:45:12,327:INFO:Copying training dataset
2022-06-06 13:45:12,327:INFO:Defining folds
2022-06-06 13:45:12,328:INFO:Declaring metric variables
2022-06-06 13:45:12,336:INFO:Importing untrained model
2022-06-06 13:45:12,344:INFO:Gradient Boosting Regressor Imported succesfully
2022-06-06 13:45:12,359:INFO:Starting cross validation
2022-06-06 13:45:12,359:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:12,495:INFO:Calculating mean and std
2022-06-06 13:45:12,495:INFO:Creating metrics dataframe
2022-06-06 13:45:12,510:INFO:Uploading results into container
2022-06-06 13:45:12,511:INFO:Uploading model into container now
2022-06-06 13:45:12,511:INFO:create_model_container: 16
2022-06-06 13:45:12,511:INFO:master_model_container: 16
2022-06-06 13:45:12,511:INFO:display_container: 2
2022-06-06 13:45:12,511:INFO:GradientBoostingRegressor(alpha=0.9, ccp_alpha=0.0, criterion='friedman_mse',
init=None, learning_rate=0.1, loss='ls', max_depth=3,
max_features=None, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, n_estimators=100,
n_iter_no_change=None, presort='deprecated',
random_state=123, subsample=1.0, tol=0.0001,
validation_fraction=0.1, verbose=0, warm_start=False)
2022-06-06 13:45:12,511:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:12,585:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:12,585:INFO:Creating metrics dataframe
2022-06-06 13:45:12,616:INFO:Initializing Extreme Gradient Boosting
2022-06-06 13:45:12,616:INFO:Total runtime is 0.18044031063715618 minutes
2022-06-06 13:45:12,624:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:12,625:INFO:Initializing create_model()
2022-06-06 13:45:12,625:INFO:create_model(estimator=xgboost, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:12,625:INFO:Checking exceptions
2022-06-06 13:45:12,625:INFO:Importing libraries
2022-06-06 13:45:12,625:INFO:Copying training dataset
2022-06-06 13:45:12,626:INFO:Defining folds
2022-06-06 13:45:12,626:INFO:Declaring metric variables
2022-06-06 13:45:12,633:INFO:Importing untrained model
2022-06-06 13:45:12,642:INFO:Extreme Gradient Boosting Imported succesfully
2022-06-06 13:45:12,658:INFO:Starting cross validation
2022-06-06 13:45:12,660:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:13,200:INFO:Calculating mean and std
2022-06-06 13:45:13,201:INFO:Creating metrics dataframe
2022-06-06 13:45:13,216:INFO:Uploading results into container
2022-06-06 13:45:13,216:INFO:Uploading model into container now
2022-06-06 13:45:13,216:INFO:create_model_container: 17
2022-06-06 13:45:13,216:INFO:master_model_container: 17
2022-06-06 13:45:13,216:INFO:display_container: 2
2022-06-06 13:45:13,217:INFO:XGBRegressor(base_score=None, booster='gbtree', callbacks=None,
colsample_bylevel=None, colsample_bynode=None,
colsample_bytree=None, early_stopping_rounds=None,
enable_categorical=False, eval_metric=None, gamma=None,
gpu_id=None, grow_policy=None, importance_type=None,
interaction_constraints=None, learning_rate=None, max_bin=None,
max_cat_to_onehot=None, max_delta_step=None, max_depth=None,
max_leaves=None, min_child_weight=None, missing=nan,
monotone_constraints=None, n_estimators=100, n_jobs=-1,
num_parallel_tree=None, objective='reg:squarederror',
predictor=None, random_state=123, reg_alpha=None, ...)
2022-06-06 13:45:13,217:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:13,289:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:13,289:INFO:Creating metrics dataframe
2022-06-06 13:45:13,322:INFO:Initializing Light Gradient Boosting Machine
2022-06-06 13:45:13,322:INFO:Total runtime is 0.19221116304397584 minutes
2022-06-06 13:45:13,329:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:13,330:INFO:Initializing create_model()
2022-06-06 13:45:13,330:INFO:create_model(estimator=lightgbm, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:13,330:INFO:Checking exceptions
2022-06-06 13:45:13,330:INFO:Importing libraries
2022-06-06 13:45:13,330:INFO:Copying training dataset
2022-06-06 13:45:13,331:INFO:Defining folds
2022-06-06 13:45:13,331:INFO:Declaring metric variables
2022-06-06 13:45:13,340:INFO:Importing untrained model
2022-06-06 13:45:13,349:INFO:Light Gradient Boosting Machine Imported succesfully
2022-06-06 13:45:13,367:INFO:Starting cross validation
2022-06-06 13:45:13,368:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:13,508:INFO:Calculating mean and std
2022-06-06 13:45:13,509:INFO:Creating metrics dataframe
2022-06-06 13:45:13,524:INFO:Uploading results into container
2022-06-06 13:45:13,525:INFO:Uploading model into container now
2022-06-06 13:45:13,525:INFO:create_model_container: 18
2022-06-06 13:45:13,525:INFO:master_model_container: 18
2022-06-06 13:45:13,525:INFO:display_container: 2
2022-06-06 13:45:13,525:INFO:LGBMRegressor(boosting_type='gbdt', class_weight=None, colsample_bytree=1.0,
importance_type='split', learning_rate=0.1, max_depth=-1,
min_child_samples=20, min_child_weight=0.001, min_split_gain=0.0,
n_estimators=100, n_jobs=-1, num_leaves=31, objective=None,
random_state=123, reg_alpha=0.0, reg_lambda=0.0, silent='warn',
subsample=1.0, subsample_for_bin=200000, subsample_freq=0)
2022-06-06 13:45:13,525:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:13,595:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:13,595:INFO:Creating metrics dataframe
2022-06-06 13:45:13,627:INFO:Initializing CatBoost Regressor
2022-06-06 13:45:13,628:INFO:Total runtime is 0.19731063842773439 minutes
2022-06-06 13:45:13,634:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:13,635:INFO:Initializing create_model()
2022-06-06 13:45:13,636:INFO:create_model(estimator=catboost, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:13,636:INFO:Checking exceptions
2022-06-06 13:45:13,636:INFO:Importing libraries
2022-06-06 13:45:13,636:INFO:Copying training dataset
2022-06-06 13:45:13,637:INFO:Defining folds
2022-06-06 13:45:13,637:INFO:Declaring metric variables
2022-06-06 13:45:13,643:INFO:Importing untrained model
2022-06-06 13:45:13,650:INFO:CatBoost Regressor Imported succesfully
2022-06-06 13:45:13,665:INFO:Starting cross validation
2022-06-06 13:45:13,666:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:13,994:WARNING:create_model() for catboost raised an exception or returned all 0.0, trying without fit_kwargs:
2022-06-06 13:45:13,999:WARNING:joblib.externals.loky.process_executor._RemoteTraceback:
"""
Traceback (most recent call last):
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\joblib\externals\loky\process_executor.py", line 407, in _process_worker
call_item = call_queue.get(block=True, timeout=timeout)
File "C:\Users\luuisotorres\anaconda3\lib\multiprocessing\queues.py", line 122, in get
return _ForkingPickler.loads(res)
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\catboost\__init__.py", line 1, in <module>
from .core import (
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\catboost\core.py", line 46, in <module>
from .plot_helpers import save_plot_file, try_plot_offline
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\catboost\plot_helpers.py", line 3, in <module>
from . import _catboost
ImportError: DLL load failed while importing _catboost: O arquivo de paginação é muito pequeno para que esta operação seja concluída.
"""
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "C:\Users\luuisotorres\AppData\Roaming\Python\Python39\site-packages\pycaret\internal\tabular.py", line 2203, in compare_models
model, model_fit_time = create_model_supervised(**create_model_args)
File "C:\Users\luuisotorres\AppData\Roaming\Python\Python39\site-packages\pycaret\internal\tabular.py", line 3200, in create_model_supervised
scores = cross_validate(
File "C:\Users\luuisotorres\AppData\Roaming\Python\Python39\site-packages\sklearn\utils\validation.py", line 72, in inner_f
return f(**kwargs)
File "C:\Users\luuisotorres\AppData\Roaming\Python\Python39\site-packages\sklearn\model_selection\_validation.py", line 242, in cross_validate
scores = parallel(
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\joblib\parallel.py", line 1056, in __call__
self.retrieve()
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\joblib\parallel.py", line 935, in retrieve
self._output.extend(job.get(timeout=self.timeout))
File "C:\Users\luuisotorres\anaconda3\lib\site-packages\joblib\_parallel_backends.py", line 542, in wrap_future_result
return future.result(timeout=timeout)
File "C:\Users\luuisotorres\anaconda3\lib\concurrent\futures\_base.py", line 445, in result
return self.__get_result()
File "C:\Users\luuisotorres\anaconda3\lib\concurrent\futures\_base.py", line 390, in __get_result
raise self._exception
joblib.externals.loky.process_executor.BrokenProcessPool: A task has failed to un-serialize. Please ensure that the arguments of the function are all picklable.
2022-06-06 13:45:13,999:INFO:Initializing create_model()
2022-06-06 13:45:13,999:INFO:create_model(estimator=catboost, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:13,999:INFO:Checking exceptions
2022-06-06 13:45:13,999:INFO:Importing libraries
2022-06-06 13:45:13,999:INFO:Copying training dataset
2022-06-06 13:45:14,001:INFO:Defining folds
2022-06-06 13:45:14,001:INFO:Declaring metric variables
2022-06-06 13:45:14,009:INFO:Importing untrained model
2022-06-06 13:45:14,016:INFO:CatBoost Regressor Imported succesfully
2022-06-06 13:45:14,032:INFO:Starting cross validation
2022-06-06 13:45:14,033:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:31,923:INFO:Calculating mean and std
2022-06-06 13:45:31,925:INFO:Creating metrics dataframe
2022-06-06 13:45:31,947:INFO:Uploading results into container
2022-06-06 13:45:31,947:INFO:Uploading model into container now
2022-06-06 13:45:31,947:INFO:create_model_container: 19
2022-06-06 13:45:31,947:INFO:master_model_container: 19
2022-06-06 13:45:31,947:INFO:display_container: 2
2022-06-06 13:45:31,947:INFO:<catboost.core.CatBoostRegressor object at 0x000001A4906D2400>
2022-06-06 13:45:31,947:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:32,028:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:32,028:INFO:Creating metrics dataframe
2022-06-06 13:45:32,063:INFO:Initializing Dummy Regressor
2022-06-06 13:45:32,063:INFO:Total runtime is 0.5045655886332194 minutes
2022-06-06 13:45:32,073:INFO:SubProcess create_model() called ==================================
2022-06-06 13:45:32,073:INFO:Initializing create_model()
2022-06-06 13:45:32,073:INFO:create_model(estimator=dummy, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x000001A4906E29D0>, return_train_score=False, kwargs={})
2022-06-06 13:45:32,073:INFO:Checking exceptions
2022-06-06 13:45:32,073:INFO:Importing libraries
2022-06-06 13:45:32,073:INFO:Copying training dataset
2022-06-06 13:45:32,074:INFO:Defining folds
2022-06-06 13:45:32,074:INFO:Declaring metric variables
2022-06-06 13:45:32,083:INFO:Importing untrained model
2022-06-06 13:45:32,092:INFO:Dummy Regressor Imported succesfully
2022-06-06 13:45:32,114:INFO:Starting cross validation
2022-06-06 13:45:32,115:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:45:32,168:INFO:Calculating mean and std
2022-06-06 13:45:32,169:INFO:Creating metrics dataframe
2022-06-06 13:45:32,189:INFO:Uploading results into container
2022-06-06 13:45:32,190:INFO:Uploading model into container now
2022-06-06 13:45:32,190:INFO:create_model_container: 20
2022-06-06 13:45:32,190:INFO:master_model_container: 20
2022-06-06 13:45:32,190:INFO:display_container: 2
2022-06-06 13:45:32,190:INFO:DummyRegressor(constant=None, quantile=None, strategy='mean')
2022-06-06 13:45:32,190:INFO:create_model() succesfully completed......................................
2022-06-06 13:45:32,266:INFO:SubProcess create_model() end ==================================
2022-06-06 13:45:32,266:INFO:Creating metrics dataframe
2022-06-06 13:45:32,321:INFO:Initializing create_model()
2022-06-06 13:45:32,322:INFO:create_model(estimator=ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=-1, oob_score=False,
random_state=123, verbose=0, warm_start=False), fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=None, return_train_score=False, kwargs={})
2022-06-06 13:45:32,322:INFO:Checking exceptions
2022-06-06 13:45:32,322:INFO:Importing libraries
2022-06-06 13:45:32,322:INFO:Copying training dataset
2022-06-06 13:45:32,322:INFO:Defining folds
2022-06-06 13:45:32,322:INFO:Declaring metric variables
2022-06-06 13:45:32,322:INFO:Importing untrained model
2022-06-06 13:45:32,322:INFO:Declaring custom model
2022-06-06 13:45:32,323:INFO:Extra Trees Regressor Imported succesfully
2022-06-06 13:45:32,324:INFO:Cross validation set to False
2022-06-06 13:45:32,324:INFO:Fitting Model
2022-06-06 13:45:32,498:INFO:ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=-1, oob_score=False,
random_state=123, verbose=0, warm_start=False)
2022-06-06 13:45:32,498:INFO:create_models() succesfully completed......................................
2022-06-06 13:45:32,577:INFO:Initializing create_model()
2022-06-06 13:45:32,578:INFO:create_model(estimator=Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
normalize=False, random_state=123, solver='auto', tol=0.001), fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=None, return_train_score=False, kwargs={})
2022-06-06 13:45:32,578:INFO:Checking exceptions
2022-06-06 13:45:32,578:INFO:Importing libraries
2022-06-06 13:45:32,579:INFO:Copying training dataset
2022-06-06 13:45:32,579:INFO:Defining folds
2022-06-06 13:45:32,579:INFO:Declaring metric variables
2022-06-06 13:45:32,579:INFO:Importing untrained model
2022-06-06 13:45:32,579:INFO:Declaring custom model
2022-06-06 13:45:32,580:INFO:Ridge Regression Imported succesfully
2022-06-06 13:45:32,581:INFO:Cross validation set to False
2022-06-06 13:45:32,581:INFO:Fitting Model
2022-06-06 13:45:32,584:INFO:Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
normalize=False, random_state=123, solver='auto', tol=0.001)
2022-06-06 13:45:32,584:INFO:create_models() succesfully completed......................................
2022-06-06 13:45:32,669:INFO:Initializing create_model()
2022-06-06 13:45:32,669:INFO:create_model(estimator=Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,
jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',
random_state=123, verbose=False), fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=None, return_train_score=False, kwargs={})
2022-06-06 13:45:32,670:INFO:Checking exceptions
2022-06-06 13:45:32,670:INFO:Importing libraries
2022-06-06 13:45:32,670:INFO:Copying training dataset
2022-06-06 13:45:32,670:INFO:Defining folds
2022-06-06 13:45:32,670:INFO:Declaring metric variables
2022-06-06 13:45:32,670:INFO:Importing untrained model
2022-06-06 13:45:32,670:INFO:Declaring custom model
2022-06-06 13:45:32,671:INFO:Least Angle Regression Imported succesfully
2022-06-06 13:45:32,671:INFO:Cross validation set to False
2022-06-06 13:45:32,671:INFO:Fitting Model
2022-06-06 13:45:32,676:INFO:Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,
jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',
random_state=123, verbose=False)
2022-06-06 13:45:32,676:INFO:create_models() succesfully completed......................................
2022-06-06 13:45:32,789:INFO:create_model_container: 20
2022-06-06 13:45:32,789:INFO:master_model_container: 20
2022-06-06 13:45:32,789:INFO:display_container: 2
2022-06-06 13:45:32,790:INFO:[ExtraTreesRegressor(bootstrap=False, ccp_alpha=0.0, criterion='mse',
max_depth=None, max_features='auto', max_leaf_nodes=None,
max_samples=None, min_impurity_decrease=0.0,
min_impurity_split=None, min_samples_leaf=1,
min_samples_split=2, min_weight_fraction_leaf=0.0,
n_estimators=100, n_jobs=-1, oob_score=False,
random_state=123, verbose=0, warm_start=False), Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
normalize=False, random_state=123, solver='auto', tol=0.001), Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,
jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',
random_state=123, verbose=False)]
2022-06-06 13:45:32,790:INFO:compare_models() succesfully completed......................................
2022-06-06 13:55:51,954:INFO:PyCaret Supervised Module
2022-06-06 13:55:51,955:INFO:ML Usecase: regression
2022-06-06 13:55:51,955:INFO:version 2.3.10
2022-06-06 13:55:51,955:INFO:Initializing setup()
2022-06-06 13:55:51,955:INFO:setup(target=Close, ml_usecase=regression, available_plots={'parameter': 'Hyperparameters', 'residuals': 'Residuals', 'error': 'Prediction Error', 'cooks': 'Cooks Distance', 'rfe': 'Feature Selection', 'learning': 'Learning Curve', 'manifold': 'Manifold Learning', 'vc': 'Validation Curve', 'feature': 'Feature Importance', 'feature_all': 'Feature Importance (All)', 'tree': 'Decision Tree', 'residuals_interactive': 'Interactive Residuals'}, train_size=0.7, test_data=None, preprocess=True, imputation_type=simple, iterative_imputation_iters=5, categorical_features=None, categorical_imputation=constant, categorical_iterative_imputer=lightgbm, ordinal_features=None, high_cardinality_features=None, high_cardinality_method=frequency, numeric_features=None, numeric_imputation=mean, numeric_iterative_imputer=lightgbm, date_features=None, ignore_features=None, normalize=False, normalize_method=zscore, transformation=False, transformation_method=yeo-johnson, handle_unknown_categorical=True, unknown_categorical_method=least_frequent, pca=False, pca_method=linear, pca_components=None, ignore_low_variance=False, combine_rare_levels=False, rare_level_threshold=0.1, bin_numeric_features=None, remove_outliers=False, outliers_threshold=0.05, remove_multicollinearity=False, multicollinearity_threshold=0.9, remove_perfect_collinearity=True, create_clusters=False, cluster_iter=20, polynomial_features=False, polynomial_degree=2, trigonometry_features=False, polynomial_threshold=0.1, group_features=None, group_names=None, feature_selection=False, feature_selection_threshold=0.8, feature_selection_method=classic, feature_interaction=False, feature_ratio=False, interaction_threshold=0.01, fix_imbalance=False, fix_imbalance_method=None, transform_target=False, transform_target_method=box-cox, data_split_shuffle=True, data_split_stratify=False, fold_strategy=kfold, fold=10, fold_shuffle=False, fold_groups=None, n_jobs=-1, use_gpu=False, custom_pipeline=None, html=True, session_id=123, log_experiment=False, experiment_name=None, experiment_custom_tags=None, log_plots=False, log_profile=False, log_data=False, silent=False, verbose=True, profile=False, profile_kwargs=None, display=None)
2022-06-06 13:55:51,955:INFO:Checking environment
2022-06-06 13:55:51,955:INFO:python_version: 3.9.7
2022-06-06 13:55:51,955:INFO:python_build: ('default', 'Sep 16 2021 16:59:28')
2022-06-06 13:55:51,955:INFO:machine: AMD64
2022-06-06 13:55:51,955:INFO:platform: Windows-10-10.0.22000-SP0
2022-06-06 13:55:51,955:INFO:Memory: svmem(total=8412778496, available=3895607296, percent=53.7, used=4517171200, free=3895607296)
2022-06-06 13:55:51,955:INFO:Physical Core: 4
2022-06-06 13:55:51,955:INFO:Logical Core: 8
2022-06-06 13:55:51,955:INFO:Checking libraries
2022-06-06 13:55:51,956:INFO:pd==1.4.2
2022-06-06 13:55:51,956:INFO:numpy==1.19.5
2022-06-06 13:55:51,956:INFO:sklearn==0.23.2
2022-06-06 13:55:51,956:INFO:lightgbm==3.3.2
2022-06-06 13:55:52,207:INFO:catboost==1.0.6
2022-06-06 13:55:52,207:INFO:xgboost==1.6.1
2022-06-06 13:55:52,207:INFO:mlflow==1.26.1
2022-06-06 13:55:52,207:INFO:Checking Exceptions
2022-06-06 13:55:52,207:INFO:Declaring global variables
2022-06-06 13:55:52,207:INFO:USI: 39cc
2022-06-06 13:55:52,207:INFO:pycaret_globals: {'pycaret_globals', 'fold_shuffle_param', 'USI', 'fold_param', 'transform_target_param', 'experiment__', 'create_model_container', 'imputation_classifier', 'X_test', 'n_jobs_param', 'logging_param', '_ml_usecase', '_all_metrics', 'target_param', 'imputation_regressor', 'dashboard_logger', 'stratify_param', 'master_model_container', '_all_models_internal', 'iterative_imputation_iters_param', 'display_container', 'y', 'X_train', 'X', 'fold_generator', 'log_plots_param', 'seed', 'y_test', 'transform_target_method_param', '_available_plots', 'html_param', 'fold_groups_param_full', 'gpu_param', '_internal_pipeline', 'fix_imbalance_method_param', '_all_models', 'fix_imbalance_param', 'prep_pipe', 'data_before_preprocess', '_gpu_n_jobs_param', 'fold_groups_param', 'y_train', 'exp_name_log'}
2022-06-06 13:55:52,207:INFO:Preparing display monitor
2022-06-06 13:55:52,207:INFO:Preparing display monitor
2022-06-06 13:55:52,218:INFO:Importing libraries
2022-06-06 13:55:52,218:INFO:Copying data for preprocessing
2022-06-06 13:55:52,224:INFO:Declaring preprocessing parameters
2022-06-06 13:55:52,225:INFO:Creating preprocessing pipeline
2022-06-06 13:55:52,232:INFO:Preprocessing pipeline created successfully
2022-06-06 13:55:52,232:ERROR:(Process Exit): setup has been interupted with user command 'quit'. setup must rerun.
2022-06-06 13:55:52,232:INFO:Creating global containers
2022-06-06 13:55:52,233:INFO:Internal pipeline: Pipeline(memory=None, steps=[('empty_step', 'passthrough')], verbose=False)
2022-06-06 13:55:55,089:INFO:Creating grid variables
2022-06-06 13:55:55,104:INFO:create_model_container: 0
2022-06-06 13:55:55,105:INFO:master_model_container: 0
2022-06-06 13:55:55,105:INFO:display_container: 1
2022-06-06 13:55:55,111:INFO:Pipeline(memory=None,
steps=[('dtypes',
DataTypes_Auto_infer(categorical_features=[],
display_types=True, features_todrop=[],
id_columns=[], ml_usecase='regression',
numerical_features=[], target='Close',
time_features=[])),
('imputer',
Simple_Imputer(categorical_strategy='not_available',
fill_value_categorical=None,
fill_value_numerical=None,
numeric_strategy='...
('scaling', 'passthrough'), ('P_transform', 'passthrough'),
('binn', 'passthrough'), ('rem_outliers', 'passthrough'),
('cluster_all', 'passthrough'),
('dummy', Dummify(target='Close')),
('fix_perfect', Remove_100(target='Close')),
('clean_names', Clean_Colum_Names()),
('feature_select', 'passthrough'), ('fix_multi', 'passthrough'),
('dfs', 'passthrough'), ('pca', 'passthrough')],
verbose=False)
2022-06-06 13:55:55,111:INFO:setup() succesfully completed......................................
2022-06-06 13:55:55,247:INFO:Initializing compare_models()
2022-06-06 13:55:55,247:INFO:compare_models(include=None, fold=None, round=4, cross_validation=True, sort=R2, n_select=3, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, display=None, exclude=None)
2022-06-06 13:55:55,247:INFO:Checking exceptions
2022-06-06 13:55:55,248:INFO:Preparing display monitor
2022-06-06 13:55:55,248:INFO:Preparing display monitor
2022-06-06 13:55:55,280:INFO:Initializing Linear Regression
2022-06-06 13:55:55,280:INFO:Total runtime is 1.6617774963378907e-05 minutes
2022-06-06 13:55:55,289:INFO:SubProcess create_model() called ==================================
2022-06-06 13:55:55,290:INFO:Initializing create_model()
2022-06-06 13:55:55,290:INFO:create_model(estimator=lr, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:55:55,290:INFO:Checking exceptions
2022-06-06 13:55:55,291:INFO:Importing libraries
2022-06-06 13:55:55,291:INFO:Copying training dataset
2022-06-06 13:55:55,293:INFO:Defining folds
2022-06-06 13:55:55,293:INFO:Declaring metric variables
2022-06-06 13:55:55,302:INFO:Importing untrained model
2022-06-06 13:55:55,312:INFO:Linear Regression Imported succesfully
2022-06-06 13:55:55,328:INFO:Starting cross validation
2022-06-06 13:55:55,336:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:02,156:INFO:Calculating mean and std
2022-06-06 13:56:02,157:INFO:Creating metrics dataframe
2022-06-06 13:56:02,195:INFO:Uploading results into container
2022-06-06 13:56:02,196:INFO:Uploading model into container now
2022-06-06 13:56:02,196:INFO:create_model_container: 1
2022-06-06 13:56:02,196:INFO:master_model_container: 1
2022-06-06 13:56:02,196:INFO:display_container: 2
2022-06-06 13:56:02,197:INFO:LinearRegression(copy_X=True, fit_intercept=True, n_jobs=-1, normalize=False)
2022-06-06 13:56:02,197:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:02,289:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:02,289:INFO:Creating metrics dataframe
2022-06-06 13:56:02,319:INFO:Initializing Lasso Regression
2022-06-06 13:56:02,319:INFO:Total runtime is 0.11733707586924236 minutes
2022-06-06 13:56:02,330:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:02,331:INFO:Initializing create_model()
2022-06-06 13:56:02,331:INFO:create_model(estimator=lasso, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:02,331:INFO:Checking exceptions
2022-06-06 13:56:02,331:INFO:Importing libraries
2022-06-06 13:56:02,331:INFO:Copying training dataset
2022-06-06 13:56:02,333:INFO:Defining folds
2022-06-06 13:56:02,333:INFO:Declaring metric variables
2022-06-06 13:56:02,342:INFO:Importing untrained model
2022-06-06 13:56:02,353:INFO:Lasso Regression Imported succesfully
2022-06-06 13:56:02,378:INFO:Starting cross validation
2022-06-06 13:56:02,379:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:02,456:INFO:Calculating mean and std
2022-06-06 13:56:02,457:INFO:Creating metrics dataframe
2022-06-06 13:56:02,480:INFO:Uploading results into container
2022-06-06 13:56:02,480:INFO:Uploading model into container now
2022-06-06 13:56:02,481:INFO:create_model_container: 2
2022-06-06 13:56:02,481:INFO:master_model_container: 2
2022-06-06 13:56:02,481:INFO:display_container: 2
2022-06-06 13:56:02,481:INFO:Lasso(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=1000,
normalize=False, positive=False, precompute=False, random_state=123,
selection='cyclic', tol=0.0001, warm_start=False)
2022-06-06 13:56:02,482:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:02,558:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:02,558:INFO:Creating metrics dataframe
2022-06-06 13:56:02,589:INFO:Initializing Ridge Regression
2022-06-06 13:56:02,589:INFO:Total runtime is 0.12184224923451742 minutes
2022-06-06 13:56:02,599:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:02,599:INFO:Initializing create_model()
2022-06-06 13:56:02,600:INFO:create_model(estimator=ridge, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:02,600:INFO:Checking exceptions
2022-06-06 13:56:02,600:INFO:Importing libraries
2022-06-06 13:56:02,600:INFO:Copying training dataset
2022-06-06 13:56:02,602:INFO:Defining folds
2022-06-06 13:56:02,602:INFO:Declaring metric variables
2022-06-06 13:56:02,610:INFO:Importing untrained model
2022-06-06 13:56:02,621:INFO:Ridge Regression Imported succesfully
2022-06-06 13:56:02,645:INFO:Starting cross validation
2022-06-06 13:56:02,646:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:02,703:INFO:Calculating mean and std
2022-06-06 13:56:02,704:INFO:Creating metrics dataframe
2022-06-06 13:56:02,724:INFO:Uploading results into container
2022-06-06 13:56:02,724:INFO:Uploading model into container now
2022-06-06 13:56:02,724:INFO:create_model_container: 3
2022-06-06 13:56:02,724:INFO:master_model_container: 3
2022-06-06 13:56:02,724:INFO:display_container: 2
2022-06-06 13:56:02,725:INFO:Ridge(alpha=1.0, copy_X=True, fit_intercept=True, max_iter=None,
normalize=False, random_state=123, solver='auto', tol=0.001)
2022-06-06 13:56:02,725:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:02,802:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:02,802:INFO:Creating metrics dataframe
2022-06-06 13:56:02,833:INFO:Initializing Elastic Net
2022-06-06 13:56:02,833:INFO:Total runtime is 0.1258993188540141 minutes
2022-06-06 13:56:02,843:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:02,843:INFO:Initializing create_model()
2022-06-06 13:56:02,843:INFO:create_model(estimator=en, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:02,844:INFO:Checking exceptions
2022-06-06 13:56:02,844:INFO:Importing libraries
2022-06-06 13:56:02,844:INFO:Copying training dataset
2022-06-06 13:56:02,845:INFO:Defining folds
2022-06-06 13:56:02,845:INFO:Declaring metric variables
2022-06-06 13:56:02,853:INFO:Importing untrained model
2022-06-06 13:56:02,864:INFO:Elastic Net Imported succesfully
2022-06-06 13:56:02,884:INFO:Starting cross validation
2022-06-06 13:56:02,885:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:02,943:INFO:Calculating mean and std
2022-06-06 13:56:02,945:INFO:Creating metrics dataframe
2022-06-06 13:56:02,967:INFO:Uploading results into container
2022-06-06 13:56:02,968:INFO:Uploading model into container now
2022-06-06 13:56:02,968:INFO:create_model_container: 4
2022-06-06 13:56:02,968:INFO:master_model_container: 4
2022-06-06 13:56:02,968:INFO:display_container: 2
2022-06-06 13:56:02,968:INFO:ElasticNet(alpha=1.0, copy_X=True, fit_intercept=True, l1_ratio=0.5,
max_iter=1000, normalize=False, positive=False, precompute=False,
random_state=123, selection='cyclic', tol=0.0001, warm_start=False)
2022-06-06 13:56:02,968:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:03,042:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:03,042:INFO:Creating metrics dataframe
2022-06-06 13:56:03,073:INFO:Initializing Least Angle Regression
2022-06-06 13:56:03,073:INFO:Total runtime is 0.12990411520004275 minutes
2022-06-06 13:56:03,082:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:03,083:INFO:Initializing create_model()
2022-06-06 13:56:03,083:INFO:create_model(estimator=lar, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:03,083:INFO:Checking exceptions
2022-06-06 13:56:03,083:INFO:Importing libraries
2022-06-06 13:56:03,083:INFO:Copying training dataset
2022-06-06 13:56:03,084:INFO:Defining folds
2022-06-06 13:56:03,084:INFO:Declaring metric variables
2022-06-06 13:56:03,093:INFO:Importing untrained model
2022-06-06 13:56:03,104:INFO:Least Angle Regression Imported succesfully
2022-06-06 13:56:03,124:INFO:Starting cross validation
2022-06-06 13:56:03,124:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:03,176:INFO:Calculating mean and std
2022-06-06 13:56:03,177:INFO:Creating metrics dataframe
2022-06-06 13:56:03,198:INFO:Uploading results into container
2022-06-06 13:56:03,198:INFO:Uploading model into container now
2022-06-06 13:56:03,198:INFO:create_model_container: 5
2022-06-06 13:56:03,198:INFO:master_model_container: 5
2022-06-06 13:56:03,198:INFO:display_container: 2
2022-06-06 13:56:03,199:INFO:Lars(copy_X=True, eps=2.220446049250313e-16, fit_intercept=True, fit_path=True,
jitter=None, n_nonzero_coefs=500, normalize=True, precompute='auto',
random_state=123, verbose=False)
2022-06-06 13:56:03,199:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:03,271:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:03,271:INFO:Creating metrics dataframe
2022-06-06 13:56:03,296:INFO:Initializing Lasso Least Angle Regression
2022-06-06 13:56:03,296:INFO:Total runtime is 0.13362827698389693 minutes
2022-06-06 13:56:03,304:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:03,305:INFO:Initializing create_model()
2022-06-06 13:56:03,305:INFO:create_model(estimator=llar, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:03,305:INFO:Checking exceptions
2022-06-06 13:56:03,305:INFO:Importing libraries
2022-06-06 13:56:03,305:INFO:Copying training dataset
2022-06-06 13:56:03,306:INFO:Defining folds
2022-06-06 13:56:03,307:INFO:Declaring metric variables
2022-06-06 13:56:03,314:INFO:Importing untrained model
2022-06-06 13:56:03,322:INFO:Lasso Least Angle Regression Imported succesfully
2022-06-06 13:56:03,341:INFO:Starting cross validation
2022-06-06 13:56:03,341:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:03,391:INFO:Calculating mean and std
2022-06-06 13:56:03,391:INFO:Creating metrics dataframe
2022-06-06 13:56:03,410:INFO:Uploading results into container
2022-06-06 13:56:03,411:INFO:Uploading model into container now
2022-06-06 13:56:03,411:INFO:create_model_container: 6
2022-06-06 13:56:03,411:INFO:master_model_container: 6
2022-06-06 13:56:03,411:INFO:display_container: 2
2022-06-06 13:56:03,411:INFO:LassoLars(alpha=1.0, copy_X=True, eps=2.220446049250313e-16, fit_intercept=True,
fit_path=True, jitter=None, max_iter=500, normalize=True,
positive=False, precompute='auto', random_state=123, verbose=False)
2022-06-06 13:56:03,411:INFO:create_model() succesfully completed......................................
2022-06-06 13:56:03,487:INFO:SubProcess create_model() end ==================================
2022-06-06 13:56:03,487:INFO:Creating metrics dataframe
2022-06-06 13:56:03,513:INFO:Initializing Orthogonal Matching Pursuit
2022-06-06 13:56:03,513:INFO:Total runtime is 0.13723605076471967 minutes
2022-06-06 13:56:03,522:INFO:SubProcess create_model() called ==================================
2022-06-06 13:56:03,523:INFO:Initializing create_model()
2022-06-06 13:56:03,523:INFO:create_model(estimator=omp, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=True, predict=True, fit_kwargs={}, groups=None, refit=False, verbose=False, system=False, metrics=None, experiment_custom_tags=None, add_to_model_list=True, probability_threshold=None, display=<pycaret.internal.Display.Display object at 0x00000214CC26CE80>, return_train_score=False, kwargs={})
2022-06-06 13:56:03,523:INFO:Checking exceptions
2022-06-06 13:56:03,523:INFO:Importing libraries
2022-06-06 13:56:03,523:INFO:Copying training dataset
2022-06-06 13:56:03,524:INFO:Defining folds
2022-06-06 13:56:03,524:INFO:Declaring metric variables
2022-06-06 13:56:03,533:INFO:Importing untrained model
2022-06-06 13:56:03,542:INFO:Orthogonal Matching Pursuit Imported succesfully
2022-06-06 13:56:03,561:INFO:Starting cross validation
2022-06-06 13:56:03,562:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1
2022-06-06 13:56:03,621:INFO:Calculating mean and std
2022-06-06 13:56:03,622:INFO:Creating metrics dataframe
2022-06-06 13:56:03,641:INFO:Uploading results into container
2022-06-06 13:56:03,641:INFO:Uploading model into container now
2022-06-06 13:56:03,641:INFO:create_model_container: 7
2022-06-06 13:56:03,641:INFO:master_model_container: 7
2022-06-06 13:56:03,641:INFO:display_container: 2
2022-06-06 13:56:03,641:INFO:OrthogonalMatchingPursuit(fit_intercept=True, n_nonzero_coefs=None,