| 2024-06-20 19:34:24,157:WARNING: | |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. | |
| 2024-06-20 19:34:24,157:WARNING: | |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. | |
| 2024-06-20 19:34:24,157:WARNING: | |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. | |
| 2024-06-20 19:34:24,157:WARNING: | |
| 'cuml' is a soft dependency and not included in the pycaret installation. Please run: `pip install cuml` to install. | |
| 2024-06-20 19:35:11,420:INFO:PyCaret RegressionExperiment | |
| 2024-06-20 19:35:11,420:INFO:Logging name: reg-default-name | |
| 2024-06-20 19:35:11,420:INFO:ML Usecase: MLUsecase.REGRESSION | |
| 2024-06-20 19:35:11,420:INFO:version 3.3.2 | |
| 2024-06-20 19:35:11,420:INFO:Initializing setup() | |
| 2024-06-20 19:35:11,421:INFO:self.USI: 9ad7 | |
| 2024-06-20 19:35:11,421:INFO:self._variable_keys: {'html_param', 'idx', '_ml_usecase', 'X', 'target_param', 'USI', 'memory', 'log_plots_param', 'exp_id', 'y_train', 'seed', 'gpu_param', 'fold_generator', 'fold_groups_param', 'X_test', 'transform_target_param', 'y_test', 'n_jobs_param', 'exp_name_log', '_available_plots', 'gpu_n_jobs_param', 'logging_param', 'y', 'X_train', 'fold_shuffle_param', 'data', 'pipeline'} | |
| 2024-06-20 19:35:11,421:INFO:Checking environment | |
| 2024-06-20 19:35:11,421:INFO:python_version: 3.11.9 | |
| 2024-06-20 19:35:11,421:INFO:python_build: ('tags/v3.11.9:de54cf5', 'Apr 2 2024 10:12:12') | |
| 2024-06-20 19:35:11,421:INFO:machine: AMD64 | |
| 2024-06-20 19:35:11,421:INFO:platform: Windows-10-10.0.22631-SP0 | |
| 2024-06-20 19:35:11,428:INFO:Memory: svmem(total=16948453376, available=2113404928, percent=87.5, used=14835048448, free=2113404928) | |
| 2024-06-20 19:35:11,428:INFO:Physical Core: 6 | |
| 2024-06-20 19:35:11,428:INFO:Logical Core: 12 | |
| 2024-06-20 19:35:11,428:INFO:Checking libraries | |
| 2024-06-20 19:35:11,428:INFO:System: | |
| 2024-06-20 19:35:11,428:INFO: python: 3.11.9 (tags/v3.11.9:de54cf5, Apr 2 2024, 10:12:12) [MSC v.1938 64 bit (AMD64)] | |
| 2024-06-20 19:35:11,428:INFO:executable: c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Scripts\python.exe | |
| 2024-06-20 19:35:11,428:INFO: machine: Windows-10-10.0.22631-SP0 | |
| 2024-06-20 19:35:11,429:INFO:PyCaret required dependencies: | |
| 2024-06-20 19:35:15,895:INFO: pip: 24.0 | |
| 2024-06-20 19:35:15,895:INFO: setuptools: 65.5.0 | |
| 2024-06-20 19:35:15,895:INFO: pycaret: 3.3.2 | |
| 2024-06-20 19:35:15,895:INFO: IPython: 8.25.0 | |
| 2024-06-20 19:35:15,895:INFO: ipywidgets: 8.1.3 | |
| 2024-06-20 19:35:15,895:INFO: tqdm: 4.66.4 | |
| 2024-06-20 19:35:15,895:INFO: numpy: 1.26.4 | |
| 2024-06-20 19:35:15,895:INFO: pandas: 2.1.4 | |
| 2024-06-20 19:35:15,896:INFO: jinja2: 3.1.4 | |
| 2024-06-20 19:35:15,896:INFO: scipy: 1.11.4 | |
| 2024-06-20 19:35:15,896:INFO: joblib: 1.3.2 | |
| 2024-06-20 19:35:15,896:INFO: sklearn: 1.4.2 | |
| 2024-06-20 19:35:15,896:INFO: pyod: 2.0.0 | |
| 2024-06-20 19:35:15,896:INFO: imblearn: 0.12.3 | |
| 2024-06-20 19:35:15,896:INFO: category_encoders: 2.6.3 | |
| 2024-06-20 19:35:15,896:INFO: lightgbm: 4.4.0 | |
| 2024-06-20 19:35:15,896:INFO: numba: 0.60.0 | |
| 2024-06-20 19:35:15,896:INFO: requests: 2.32.3 | |
| 2024-06-20 19:35:15,896:INFO: matplotlib: 3.7.5 | |
| 2024-06-20 19:35:15,896:INFO: scikitplot: 0.3.7 | |
| 2024-06-20 19:35:15,896:INFO: yellowbrick: 1.5 | |
| 2024-06-20 19:35:15,896:INFO: plotly: 5.22.0 | |
| 2024-06-20 19:35:15,896:INFO: plotly-resampler: Not installed | |
| 2024-06-20 19:35:15,896:INFO: kaleido: 0.2.1 | |
| 2024-06-20 19:35:15,896:INFO: schemdraw: 0.15 | |
| 2024-06-20 19:35:15,896:INFO: statsmodels: 0.14.2 | |
| 2024-06-20 19:35:15,896:INFO: sktime: 0.26.0 | |
| 2024-06-20 19:35:15,896:INFO: tbats: 1.1.3 | |
| 2024-06-20 19:35:15,896:INFO: pmdarima: 2.0.4 | |
| 2024-06-20 19:35:15,896:INFO: psutil: 5.9.8 | |
| 2024-06-20 19:35:15,896:INFO: markupsafe: 2.1.5 | |
| 2024-06-20 19:35:15,896:INFO: pickle5: Not installed | |
| 2024-06-20 19:35:15,896:INFO: cloudpickle: 3.0.0 | |
| 2024-06-20 19:35:15,896:INFO: deprecation: 2.1.0 | |
| 2024-06-20 19:35:15,896:INFO: xxhash: 3.4.1 | |
| 2024-06-20 19:35:15,896:INFO: wurlitzer: Not installed | |
| 2024-06-20 19:35:15,896:INFO:PyCaret optional dependencies: | |
| 2024-06-20 19:35:24,088:INFO: shap: 0.44.1 | |
| 2024-06-20 19:35:24,088:INFO: interpret: 0.6.1 | |
| 2024-06-20 19:35:24,088:INFO: umap: 0.5.6 | |
| 2024-06-20 19:35:24,088:INFO: ydata_profiling: 4.8.3 | |
| 2024-06-20 19:35:24,088:INFO: explainerdashboard: 0.4.7 | |
| 2024-06-20 19:35:24,088:INFO: autoviz: Not installed | |
| 2024-06-20 19:35:24,088:INFO: fairlearn: 0.7.0 | |
| 2024-06-20 19:35:24,088:INFO: deepchecks: Not installed | |
| 2024-06-20 19:35:24,088:INFO: xgboost: Not installed | |
| 2024-06-20 19:35:24,088:INFO: catboost: 1.2.5 | |
| 2024-06-20 19:35:24,088:INFO: kmodes: 0.12.2 | |
| 2024-06-20 19:35:24,088:INFO: mlxtend: 0.23.1 | |
| 2024-06-20 19:35:24,088:INFO: statsforecast: 1.5.0 | |
| 2024-06-20 19:35:24,088:INFO: tune_sklearn: Not installed | |
| 2024-06-20 19:35:24,088:INFO: ray: Not installed | |
| 2024-06-20 19:35:24,088:INFO: hyperopt: 0.2.7 | |
| 2024-06-20 19:35:24,088:INFO: optuna: 3.6.1 | |
| 2024-06-20 19:35:24,088:INFO: skopt: 0.10.2 | |
| 2024-06-20 19:35:24,088:INFO: mlflow: 2.14.0 | |
| 2024-06-20 19:35:24,088:INFO: gradio: 4.36.1 | |
| 2024-06-20 19:35:24,088:INFO: fastapi: 0.111.0 | |
| 2024-06-20 19:35:24,088:INFO: uvicorn: 0.30.1 | |
| 2024-06-20 19:35:24,088:INFO: m2cgen: 0.10.0 | |
| 2024-06-20 19:35:24,088:INFO: evidently: 0.4.27 | |
| 2024-06-20 19:35:24,088:INFO: fugue: 0.8.7 | |
| 2024-06-20 19:35:24,088:INFO: streamlit: Not installed | |
| 2024-06-20 19:35:24,088:INFO: prophet: Not installed | |
| 2024-06-20 19:35:24,088:INFO:None | |
| 2024-06-20 19:35:24,088:INFO:Set up data. | |
| 2024-06-20 19:35:24,099:INFO:Set up folding strategy. | |
| 2024-06-20 19:35:24,099:INFO:Set up train/test split. | |
| 2024-06-20 19:35:24,114:INFO:Set up index. | |
| 2024-06-20 19:35:24,119:INFO:Assigning column types. | |
| 2024-06-20 19:35:24,123:INFO:Engine successfully changes for model 'lr' to 'sklearn'. | |
| 2024-06-20 19:35:24,123:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:24,127:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:24,131:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:24,181:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:24,216:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:24,216:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:24,216:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,064:INFO:Engine for model 'lasso' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,069:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,074:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,118:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,153:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,153:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,153:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,154:INFO:Engine successfully changes for model 'lasso' to 'sklearn'. | |
| 2024-06-20 19:35:25,158:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,161:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,205:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,239:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,239:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,239:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,244:INFO:Engine for model 'ridge' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,247:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,310:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,345:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,346:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,346:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,346:INFO:Engine successfully changes for model 'ridge' to 'sklearn'. | |
| 2024-06-20 19:35:25,354:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,398:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,432:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,433:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,433:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,441:INFO:Engine for model 'en' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,484:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,518:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,518:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,518:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,519:INFO:Engine successfully changes for model 'en' to 'sklearn'. | |
| 2024-06-20 19:35:25,575:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,608:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,608:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,609:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,661:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,694:INFO:Engine for model 'knn' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,695:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,695:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,695:INFO:Engine successfully changes for model 'knn' to 'sklearn'. | |
| 2024-06-20 19:35:25,748:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,788:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,789:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,839:INFO:Engine for model 'svm' has not been set explicitly, hence returning None. | |
| 2024-06-20 19:35:25,874:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,874:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:25,874:INFO:Engine successfully changes for model 'svm' to 'sklearn'. | |
| 2024-06-20 19:35:25,960:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:25,960:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:26,046:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:26,046:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:26,048:INFO:Preparing preprocessing pipeline... | |
| 2024-06-20 19:35:26,048:INFO:Set up simple imputation. | |
| 2024-06-20 19:35:26,078:INFO:Finished creating preprocessing pipeline. | |
| 2024-06-20 19:35:26,083:INFO:Pipeline: Pipeline(memory=FastMemory(location=C:\Users\kowom\AppData\Local\Temp\joblib), | |
| steps=[('numerical_imputer', | |
| TransformerWrapper(include=['cement', 'slag', 'ash', 'water', | |
| 'superplastic', 'coarseagg', | |
| 'fineagg', 'age'], | |
| transformer=SimpleImputer())), | |
| ('categorical_imputer', | |
| TransformerWrapper(include=[], | |
| transformer=SimpleImputer(strategy='most_frequent')))]) | |
| 2024-06-20 19:35:26,083:INFO:Creating final display dataframe. | |
| 2024-06-20 19:35:26,124:INFO:Setup _display_container: Description Value | |
| 0 Session id 123 | |
| 1 Target strength | |
| 2 Target type Regression | |
| 3 Original data shape (1030, 9) | |
| 4 Transformed data shape (1030, 9) | |
| 5 Transformed train set shape (824, 9) | |
| 6 Transformed test set shape (206, 9) | |
| 7 Numeric features 8 | |
| 8 Preprocess True | |
| 9 Imputation type simple | |
| 10 Numeric imputation mean | |
| 11 Categorical imputation mode | |
| 12 Fold Generator KFold | |
| 13 Fold Number 10 | |
| 14 CPU Jobs -1 | |
| 15 Use GPU False | |
| 16 Log Experiment False | |
| 17 Experiment Name reg-default-name | |
| 18 USI 9ad7 | |
| 2024-06-20 19:35:26,236:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:26,236:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:26,331:WARNING: | |
| 'xgboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install xgboost` to install. | |
| Alternately, you can install this by running `pip install pycaret[models]` | |
| 2024-06-20 19:35:26,331:INFO:Soft dependency imported: catboost: 1.2.5 | |
| 2024-06-20 19:35:26,332:INFO:setup() successfully completed in 14.97s............... | |
| 2024-06-20 19:35:53,507:INFO:Initializing compare_models() | |
| 2024-06-20 19:35:53,507:INFO:compare_models(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, include=None, exclude=None, fold=None, round=4, cross_validation=True, sort=R2, n_select=1, budget_time=None, turbo=True, errors=ignore, fit_kwargs=None, groups=None, experiment_custom_tags=None, probability_threshold=None, verbose=True, parallel=None, caller_params={'self': <pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'R2', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'groups': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': <class 'pycaret.regression.oop.RegressionExperiment'>}) | |
| 2024-06-20 19:35:53,507:INFO:Checking exceptions | |
| 2024-06-20 19:35:53,508:INFO:Preparing display monitor | |
| 2024-06-20 19:35:53,531:INFO:Initializing Linear Regression | |
| 2024-06-20 19:35:53,531:INFO:Total runtime is 0.0 minutes | |
| 2024-06-20 19:35:53,535:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:35:53,536:INFO:Initializing create_model() | |
| 2024-06-20 19:35:53,536:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:35:53,536:INFO:Checking exceptions | |
| 2024-06-20 19:35:53,536:INFO:Importing libraries | |
| 2024-06-20 19:35:53,536:INFO:Copying training dataset | |
| 2024-06-20 19:35:53,542:INFO:Defining folds | |
| 2024-06-20 19:35:53,542:INFO:Declaring metric variables | |
| 2024-06-20 19:35:53,544:INFO:Importing untrained model | |
| 2024-06-20 19:35:53,549:INFO:Linear Regression Imported successfully | |
| 2024-06-20 19:35:53,555:INFO:Starting cross validation | |
| 2024-06-20 19:35:53,566:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:04,301:INFO:Calculating mean and std | |
| 2024-06-20 19:36:04,305:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:04,385:INFO:Uploading results into container | |
| 2024-06-20 19:36:04,387:INFO:Uploading model into container now | |
| 2024-06-20 19:36:04,388:INFO:_master_model_container: 1 | |
| 2024-06-20 19:36:04,388:INFO:_display_container: 2 | |
| 2024-06-20 19:36:04,389:INFO:LinearRegression(n_jobs=-1) | |
| 2024-06-20 19:36:04,389:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:04,555:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:04,555:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:04,563:INFO:Initializing Lasso Regression | |
| 2024-06-20 19:36:04,563:INFO:Total runtime is 0.18385961850484211 minutes | |
| 2024-06-20 19:36:04,565:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:04,566:INFO:Initializing create_model() | |
| 2024-06-20 19:36:04,566:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:04,566:INFO:Checking exceptions | |
| 2024-06-20 19:36:04,566:INFO:Importing libraries | |
| 2024-06-20 19:36:04,566:INFO:Copying training dataset | |
| 2024-06-20 19:36:04,571:INFO:Defining folds | |
| 2024-06-20 19:36:04,572:INFO:Declaring metric variables | |
| 2024-06-20 19:36:04,574:INFO:Importing untrained model | |
| 2024-06-20 19:36:04,578:INFO:Lasso Regression Imported successfully | |
| 2024-06-20 19:36:04,588:INFO:Starting cross validation | |
| 2024-06-20 19:36:04,591:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:07,100:INFO:Calculating mean and std | |
| 2024-06-20 19:36:07,101:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,104:INFO:Uploading results into container | |
| 2024-06-20 19:36:07,105:INFO:Uploading model into container now | |
| 2024-06-20 19:36:07,105:INFO:_master_model_container: 2 | |
| 2024-06-20 19:36:07,105:INFO:_display_container: 2 | |
| 2024-06-20 19:36:07,106:INFO:Lasso(random_state=123) | |
| 2024-06-20 19:36:07,106:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:07,235:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:07,235:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,254:INFO:Initializing Ridge Regression | |
| 2024-06-20 19:36:07,254:INFO:Total runtime is 0.22871678670247395 minutes | |
| 2024-06-20 19:36:07,256:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:07,257:INFO:Initializing create_model() | |
| 2024-06-20 19:36:07,257:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:07,257:INFO:Checking exceptions | |
| 2024-06-20 19:36:07,257:INFO:Importing libraries | |
| 2024-06-20 19:36:07,257:INFO:Copying training dataset | |
| 2024-06-20 19:36:07,260:INFO:Defining folds | |
| 2024-06-20 19:36:07,260:INFO:Declaring metric variables | |
| 2024-06-20 19:36:07,263:INFO:Importing untrained model | |
| 2024-06-20 19:36:07,266:INFO:Ridge Regression Imported successfully | |
| 2024-06-20 19:36:07,271:INFO:Starting cross validation | |
| 2024-06-20 19:36:07,271:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:07,370:INFO:Calculating mean and std | |
| 2024-06-20 19:36:07,370:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,372:INFO:Uploading results into container | |
| 2024-06-20 19:36:07,372:INFO:Uploading model into container now | |
| 2024-06-20 19:36:07,372:INFO:_master_model_container: 3 | |
| 2024-06-20 19:36:07,374:INFO:_display_container: 2 | |
| 2024-06-20 19:36:07,374:INFO:Ridge(random_state=123) | |
| 2024-06-20 19:36:07,374:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:07,495:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:07,496:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,503:INFO:Initializing Elastic Net | |
| 2024-06-20 19:36:07,503:INFO:Total runtime is 0.23286216656366981 minutes | |
| 2024-06-20 19:36:07,507:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:07,507:INFO:Initializing create_model() | |
| 2024-06-20 19:36:07,507:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:07,507:INFO:Checking exceptions | |
| 2024-06-20 19:36:07,507:INFO:Importing libraries | |
| 2024-06-20 19:36:07,508:INFO:Copying training dataset | |
| 2024-06-20 19:36:07,511:INFO:Defining folds | |
| 2024-06-20 19:36:07,511:INFO:Declaring metric variables | |
| 2024-06-20 19:36:07,515:INFO:Importing untrained model | |
| 2024-06-20 19:36:07,520:INFO:Elastic Net Imported successfully | |
| 2024-06-20 19:36:07,528:INFO:Starting cross validation | |
| 2024-06-20 19:36:07,529:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:07,636:INFO:Calculating mean and std | |
| 2024-06-20 19:36:07,637:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,639:INFO:Uploading results into container | |
| 2024-06-20 19:36:07,640:INFO:Uploading model into container now | |
| 2024-06-20 19:36:07,640:INFO:_master_model_container: 4 | |
| 2024-06-20 19:36:07,640:INFO:_display_container: 2 | |
| 2024-06-20 19:36:07,640:INFO:ElasticNet(random_state=123) | |
| 2024-06-20 19:36:07,640:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:07,749:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:07,749:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:07,755:INFO:Initializing Least Angle Regression | |
| 2024-06-20 19:36:07,755:INFO:Total runtime is 0.2370623429616292 minutes | |
| 2024-06-20 19:36:07,757:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:07,757:INFO:Initializing create_model() | |
| 2024-06-20 19:36:07,757:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:07,758:INFO:Checking exceptions | |
| 2024-06-20 19:36:07,758:INFO:Importing libraries | |
| 2024-06-20 19:36:07,758:INFO:Copying training dataset | |
| 2024-06-20 19:36:07,760:INFO:Defining folds | |
| 2024-06-20 19:36:07,760:INFO:Declaring metric variables | |
| 2024-06-20 19:36:07,763:INFO:Importing untrained model | |
| 2024-06-20 19:36:07,766:INFO:Least Angle Regression Imported successfully | |
| 2024-06-20 19:36:07,771:INFO:Starting cross validation | |
| 2024-06-20 19:36:07,772:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:08,278:INFO:Calculating mean and std | |
| 2024-06-20 19:36:08,278:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,280:INFO:Uploading results into container | |
| 2024-06-20 19:36:08,281:INFO:Uploading model into container now | |
| 2024-06-20 19:36:08,281:INFO:_master_model_container: 5 | |
| 2024-06-20 19:36:08,282:INFO:_display_container: 2 | |
| 2024-06-20 19:36:08,282:INFO:Lars(random_state=123) | |
| 2024-06-20 19:36:08,282:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:08,407:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:08,408:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,414:INFO:Initializing Lasso Least Angle Regression | |
| 2024-06-20 19:36:08,414:INFO:Total runtime is 0.2480380018552144 minutes | |
| 2024-06-20 19:36:08,418:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:08,418:INFO:Initializing create_model() | |
| 2024-06-20 19:36:08,418:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:08,418:INFO:Checking exceptions | |
| 2024-06-20 19:36:08,418:INFO:Importing libraries | |
| 2024-06-20 19:36:08,418:INFO:Copying training dataset | |
| 2024-06-20 19:36:08,422:INFO:Defining folds | |
| 2024-06-20 19:36:08,422:INFO:Declaring metric variables | |
| 2024-06-20 19:36:08,424:INFO:Importing untrained model | |
| 2024-06-20 19:36:08,427:INFO:Lasso Least Angle Regression Imported successfully | |
| 2024-06-20 19:36:08,433:INFO:Starting cross validation | |
| 2024-06-20 19:36:08,434:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:08,512:INFO:Calculating mean and std | |
| 2024-06-20 19:36:08,512:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,514:INFO:Uploading results into container | |
| 2024-06-20 19:36:08,515:INFO:Uploading model into container now | |
| 2024-06-20 19:36:08,515:INFO:_master_model_container: 6 | |
| 2024-06-20 19:36:08,515:INFO:_display_container: 2 | |
| 2024-06-20 19:36:08,515:INFO:LassoLars(random_state=123) | |
| 2024-06-20 19:36:08,515:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:08,643:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:08,643:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,649:INFO:Initializing Orthogonal Matching Pursuit | |
| 2024-06-20 19:36:08,649:INFO:Total runtime is 0.251967978477478 minutes | |
| 2024-06-20 19:36:08,652:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:08,652:INFO:Initializing create_model() | |
| 2024-06-20 19:36:08,652:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:08,652:INFO:Checking exceptions | |
| 2024-06-20 19:36:08,652:INFO:Importing libraries | |
| 2024-06-20 19:36:08,653:INFO:Copying training dataset | |
| 2024-06-20 19:36:08,656:INFO:Defining folds | |
| 2024-06-20 19:36:08,656:INFO:Declaring metric variables | |
| 2024-06-20 19:36:08,659:INFO:Importing untrained model | |
| 2024-06-20 19:36:08,662:INFO:Orthogonal Matching Pursuit Imported successfully | |
| 2024-06-20 19:36:08,668:INFO:Starting cross validation | |
| 2024-06-20 19:36:08,670:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:08,743:INFO:Calculating mean and std | |
| 2024-06-20 19:36:08,743:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,745:INFO:Uploading results into container | |
| 2024-06-20 19:36:08,745:INFO:Uploading model into container now | |
| 2024-06-20 19:36:08,745:INFO:_master_model_container: 7 | |
| 2024-06-20 19:36:08,746:INFO:_display_container: 2 | |
| 2024-06-20 19:36:08,746:INFO:OrthogonalMatchingPursuit() | |
| 2024-06-20 19:36:08,746:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:08,868:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:08,868:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,874:INFO:Initializing Bayesian Ridge | |
| 2024-06-20 19:36:08,874:INFO:Total runtime is 0.25572057167689 minutes | |
| 2024-06-20 19:36:08,878:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:08,878:INFO:Initializing create_model() | |
| 2024-06-20 19:36:08,878:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:08,878:INFO:Checking exceptions | |
| 2024-06-20 19:36:08,878:INFO:Importing libraries | |
| 2024-06-20 19:36:08,878:INFO:Copying training dataset | |
| 2024-06-20 19:36:08,882:INFO:Defining folds | |
| 2024-06-20 19:36:08,882:INFO:Declaring metric variables | |
| 2024-06-20 19:36:08,884:INFO:Importing untrained model | |
| 2024-06-20 19:36:08,889:INFO:Bayesian Ridge Imported successfully | |
| 2024-06-20 19:36:08,893:INFO:Starting cross validation | |
| 2024-06-20 19:36:08,895:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:08,973:INFO:Calculating mean and std | |
| 2024-06-20 19:36:08,973:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:08,975:INFO:Uploading results into container | |
| 2024-06-20 19:36:08,975:INFO:Uploading model into container now | |
| 2024-06-20 19:36:08,975:INFO:_master_model_container: 8 | |
| 2024-06-20 19:36:08,975:INFO:_display_container: 2 | |
| 2024-06-20 19:36:08,975:INFO:BayesianRidge() | |
| 2024-06-20 19:36:08,976:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:09,087:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:09,087:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,092:INFO:Initializing Passive Aggressive Regressor | |
| 2024-06-20 19:36:09,092:INFO:Total runtime is 0.25934991439183547 minutes | |
| 2024-06-20 19:36:09,094:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:09,094:INFO:Initializing create_model() | |
| 2024-06-20 19:36:09,094:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:09,094:INFO:Checking exceptions | |
| 2024-06-20 19:36:09,095:INFO:Importing libraries | |
| 2024-06-20 19:36:09,095:INFO:Copying training dataset | |
| 2024-06-20 19:36:09,099:INFO:Defining folds | |
| 2024-06-20 19:36:09,099:INFO:Declaring metric variables | |
| 2024-06-20 19:36:09,101:INFO:Importing untrained model | |
| 2024-06-20 19:36:09,105:INFO:Passive Aggressive Regressor Imported successfully | |
| 2024-06-20 19:36:09,110:INFO:Starting cross validation | |
| 2024-06-20 19:36:09,111:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:09,205:INFO:Calculating mean and std | |
| 2024-06-20 19:36:09,206:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,208:INFO:Uploading results into container | |
| 2024-06-20 19:36:09,208:INFO:Uploading model into container now | |
| 2024-06-20 19:36:09,210:INFO:_master_model_container: 9 | |
| 2024-06-20 19:36:09,210:INFO:_display_container: 2 | |
| 2024-06-20 19:36:09,210:INFO:PassiveAggressiveRegressor(random_state=123) | |
| 2024-06-20 19:36:09,210:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:09,338:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:09,338:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,344:INFO:Initializing Huber Regressor | |
| 2024-06-20 19:36:09,344:INFO:Total runtime is 0.26354595025380445 minutes | |
| 2024-06-20 19:36:09,346:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:09,347:INFO:Initializing create_model() | |
| 2024-06-20 19:36:09,347:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:09,347:INFO:Checking exceptions | |
| 2024-06-20 19:36:09,347:INFO:Importing libraries | |
| 2024-06-20 19:36:09,347:INFO:Copying training dataset | |
| 2024-06-20 19:36:09,351:INFO:Defining folds | |
| 2024-06-20 19:36:09,351:INFO:Declaring metric variables | |
| 2024-06-20 19:36:09,354:INFO:Importing untrained model | |
| 2024-06-20 19:36:09,358:INFO:Huber Regressor Imported successfully | |
| 2024-06-20 19:36:09,364:INFO:Starting cross validation | |
| 2024-06-20 19:36:09,365:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:09,426:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,427:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,437:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,437:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,440:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,443:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,445:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,461:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,467:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\linear_model\_huber.py:342: ConvergenceWarning: lbfgs failed to converge (status=1): | |
| STOP: TOTAL NO. of ITERATIONS REACHED LIMIT. | |
| Increase the number of iterations (max_iter) or scale the data as shown in: | |
| https://scikit-learn.org/stable/modules/preprocessing.html | |
| self.n_iter_ = _check_optimize_result("lbfgs", opt_res, self.max_iter) | |
| 2024-06-20 19:36:09,481:INFO:Calculating mean and std | |
| 2024-06-20 19:36:09,481:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,484:INFO:Uploading results into container | |
| 2024-06-20 19:36:09,484:INFO:Uploading model into container now | |
| 2024-06-20 19:36:09,484:INFO:_master_model_container: 10 | |
| 2024-06-20 19:36:09,484:INFO:_display_container: 2 | |
| 2024-06-20 19:36:09,485:INFO:HuberRegressor() | |
| 2024-06-20 19:36:09,485:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:09,594:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:09,595:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,602:INFO:Initializing K Neighbors Regressor | |
| 2024-06-20 19:36:09,602:INFO:Total runtime is 0.26784221331278474 minutes | |
| 2024-06-20 19:36:09,605:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:09,605:INFO:Initializing create_model() | |
| 2024-06-20 19:36:09,606:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:09,606:INFO:Checking exceptions | |
| 2024-06-20 19:36:09,606:INFO:Importing libraries | |
| 2024-06-20 19:36:09,606:INFO:Copying training dataset | |
| 2024-06-20 19:36:09,608:INFO:Defining folds | |
| 2024-06-20 19:36:09,608:INFO:Declaring metric variables | |
| 2024-06-20 19:36:09,610:INFO:Importing untrained model | |
| 2024-06-20 19:36:09,614:INFO:K Neighbors Regressor Imported successfully | |
| 2024-06-20 19:36:09,619:INFO:Starting cross validation | |
| 2024-06-20 19:36:09,620:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:09,722:INFO:Calculating mean and std | |
| 2024-06-20 19:36:09,723:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,725:INFO:Uploading results into container | |
| 2024-06-20 19:36:09,725:INFO:Uploading model into container now | |
| 2024-06-20 19:36:09,725:INFO:_master_model_container: 11 | |
| 2024-06-20 19:36:09,725:INFO:_display_container: 2 | |
| 2024-06-20 19:36:09,725:INFO:KNeighborsRegressor(n_jobs=-1) | |
| 2024-06-20 19:36:09,725:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:09,852:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:09,852:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,859:INFO:Initializing Decision Tree Regressor | |
| 2024-06-20 19:36:09,859:INFO:Total runtime is 0.27212407191594434 minutes | |
| 2024-06-20 19:36:09,862:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:09,863:INFO:Initializing create_model() | |
| 2024-06-20 19:36:09,863:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:09,863:INFO:Checking exceptions | |
| 2024-06-20 19:36:09,863:INFO:Importing libraries | |
| 2024-06-20 19:36:09,863:INFO:Copying training dataset | |
| 2024-06-20 19:36:09,867:INFO:Defining folds | |
| 2024-06-20 19:36:09,868:INFO:Declaring metric variables | |
| 2024-06-20 19:36:09,871:INFO:Importing untrained model | |
| 2024-06-20 19:36:09,874:INFO:Decision Tree Regressor Imported successfully | |
| 2024-06-20 19:36:09,879:INFO:Starting cross validation | |
| 2024-06-20 19:36:09,880:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:09,958:INFO:Calculating mean and std | |
| 2024-06-20 19:36:09,958:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:09,960:INFO:Uploading results into container | |
| 2024-06-20 19:36:09,960:INFO:Uploading model into container now | |
| 2024-06-20 19:36:09,960:INFO:_master_model_container: 12 | |
| 2024-06-20 19:36:09,960:INFO:_display_container: 2 | |
| 2024-06-20 19:36:09,961:INFO:DecisionTreeRegressor(random_state=123) | |
| 2024-06-20 19:36:09,961:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:10,077:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:10,077:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:10,084:INFO:Initializing Random Forest Regressor | |
| 2024-06-20 19:36:10,084:INFO:Total runtime is 0.2758734345436095 minutes | |
| 2024-06-20 19:36:10,086:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:10,086:INFO:Initializing create_model() | |
| 2024-06-20 19:36:10,086:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:10,086:INFO:Checking exceptions | |
| 2024-06-20 19:36:10,086:INFO:Importing libraries | |
| 2024-06-20 19:36:10,086:INFO:Copying training dataset | |
| 2024-06-20 19:36:10,089:INFO:Defining folds | |
| 2024-06-20 19:36:10,090:INFO:Declaring metric variables | |
| 2024-06-20 19:36:10,092:INFO:Importing untrained model | |
| 2024-06-20 19:36:10,095:INFO:Random Forest Regressor Imported successfully | |
| 2024-06-20 19:36:10,100:INFO:Starting cross validation | |
| 2024-06-20 19:36:10,101:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:10,714:INFO:Calculating mean and std | |
| 2024-06-20 19:36:10,716:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:10,717:INFO:Uploading results into container | |
| 2024-06-20 19:36:10,717:INFO:Uploading model into container now | |
| 2024-06-20 19:36:10,718:INFO:_master_model_container: 13 | |
| 2024-06-20 19:36:10,718:INFO:_display_container: 2 | |
| 2024-06-20 19:36:10,718:INFO:RandomForestRegressor(n_jobs=-1, random_state=123) | |
| 2024-06-20 19:36:10,718:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:10,829:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:10,829:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:10,836:INFO:Initializing Extra Trees Regressor | |
| 2024-06-20 19:36:10,836:INFO:Total runtime is 0.2884133060773213 minutes | |
| 2024-06-20 19:36:10,838:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:10,838:INFO:Initializing create_model() | |
| 2024-06-20 19:36:10,838:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:10,838:INFO:Checking exceptions | |
| 2024-06-20 19:36:10,840:INFO:Importing libraries | |
| 2024-06-20 19:36:10,840:INFO:Copying training dataset | |
| 2024-06-20 19:36:10,842:INFO:Defining folds | |
| 2024-06-20 19:36:10,842:INFO:Declaring metric variables | |
| 2024-06-20 19:36:10,844:INFO:Importing untrained model | |
| 2024-06-20 19:36:10,848:INFO:Extra Trees Regressor Imported successfully | |
| 2024-06-20 19:36:10,855:INFO:Starting cross validation | |
| 2024-06-20 19:36:10,855:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:11,284:INFO:Calculating mean and std | |
| 2024-06-20 19:36:11,285:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:11,286:INFO:Uploading results into container | |
| 2024-06-20 19:36:11,286:INFO:Uploading model into container now | |
| 2024-06-20 19:36:11,287:INFO:_master_model_container: 14 | |
| 2024-06-20 19:36:11,287:INFO:_display_container: 2 | |
| 2024-06-20 19:36:11,287:INFO:ExtraTreesRegressor(n_jobs=-1, random_state=123) | |
| 2024-06-20 19:36:11,287:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:11,396:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:11,396:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:11,402:INFO:Initializing AdaBoost Regressor | |
| 2024-06-20 19:36:11,402:INFO:Total runtime is 0.297850203514099 minutes | |
| 2024-06-20 19:36:11,404:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:11,404:INFO:Initializing create_model() | |
| 2024-06-20 19:36:11,404:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:11,406:INFO:Checking exceptions | |
| 2024-06-20 19:36:11,406:INFO:Importing libraries | |
| 2024-06-20 19:36:11,406:INFO:Copying training dataset | |
| 2024-06-20 19:36:11,408:INFO:Defining folds | |
| 2024-06-20 19:36:11,408:INFO:Declaring metric variables | |
| 2024-06-20 19:36:11,411:INFO:Importing untrained model | |
| 2024-06-20 19:36:11,413:INFO:AdaBoost Regressor Imported successfully | |
| 2024-06-20 19:36:11,418:INFO:Starting cross validation | |
| 2024-06-20 19:36:11,419:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:11,636:INFO:Calculating mean and std | |
| 2024-06-20 19:36:11,637:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:11,638:INFO:Uploading results into container | |
| 2024-06-20 19:36:11,638:INFO:Uploading model into container now | |
| 2024-06-20 19:36:11,639:INFO:_master_model_container: 15 | |
| 2024-06-20 19:36:11,639:INFO:_display_container: 2 | |
| 2024-06-20 19:36:11,639:INFO:AdaBoostRegressor(random_state=123) | |
| 2024-06-20 19:36:11,639:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:11,753:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:11,754:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:11,761:INFO:Initializing Gradient Boosting Regressor | |
| 2024-06-20 19:36:11,761:INFO:Total runtime is 0.30383289655049633 minutes | |
| 2024-06-20 19:36:11,764:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:11,765:INFO:Initializing create_model() | |
| 2024-06-20 19:36:11,765:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:11,765:INFO:Checking exceptions | |
| 2024-06-20 19:36:11,765:INFO:Importing libraries | |
| 2024-06-20 19:36:11,765:INFO:Copying training dataset | |
| 2024-06-20 19:36:11,769:INFO:Defining folds | |
| 2024-06-20 19:36:11,769:INFO:Declaring metric variables | |
| 2024-06-20 19:36:11,771:INFO:Importing untrained model | |
| 2024-06-20 19:36:11,774:INFO:Gradient Boosting Regressor Imported successfully | |
| 2024-06-20 19:36:11,780:INFO:Starting cross validation | |
| 2024-06-20 19:36:11,780:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:12,076:INFO:Calculating mean and std | |
| 2024-06-20 19:36:12,077:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:12,079:INFO:Uploading results into container | |
| 2024-06-20 19:36:12,079:INFO:Uploading model into container now | |
| 2024-06-20 19:36:12,079:INFO:_master_model_container: 16 | |
| 2024-06-20 19:36:12,079:INFO:_display_container: 2 | |
| 2024-06-20 19:36:12,080:INFO:GradientBoostingRegressor(random_state=123) | |
| 2024-06-20 19:36:12,080:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:12,197:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:12,197:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:12,206:INFO:Initializing Light Gradient Boosting Machine | |
| 2024-06-20 19:36:12,206:INFO:Total runtime is 0.31123881737391146 minutes | |
| 2024-06-20 19:36:12,209:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:12,210:INFO:Initializing create_model() | |
| 2024-06-20 19:36:12,210:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:12,210:INFO:Checking exceptions | |
| 2024-06-20 19:36:12,210:INFO:Importing libraries | |
| 2024-06-20 19:36:12,210:INFO:Copying training dataset | |
| 2024-06-20 19:36:12,214:INFO:Defining folds | |
| 2024-06-20 19:36:12,214:INFO:Declaring metric variables | |
| 2024-06-20 19:36:12,217:INFO:Importing untrained model | |
| 2024-06-20 19:36:12,220:INFO:Light Gradient Boosting Machine Imported successfully | |
| 2024-06-20 19:36:12,226:INFO:Starting cross validation | |
| 2024-06-20 19:36:12,227:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:13,201:INFO:Calculating mean and std | |
| 2024-06-20 19:36:13,202:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:13,204:INFO:Uploading results into container | |
| 2024-06-20 19:36:13,205:INFO:Uploading model into container now | |
| 2024-06-20 19:36:13,205:INFO:_master_model_container: 17 | |
| 2024-06-20 19:36:13,205:INFO:_display_container: 2 | |
| 2024-06-20 19:36:13,205:INFO:LGBMRegressor(n_jobs=-1, random_state=123) | |
| 2024-06-20 19:36:13,207:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:13,346:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:13,346:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:13,353:INFO:Initializing CatBoost Regressor | |
| 2024-06-20 19:36:13,353:INFO:Total runtime is 0.3303659796714782 minutes | |
| 2024-06-20 19:36:13,355:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:13,356:INFO:Initializing create_model() | |
| 2024-06-20 19:36:13,356:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:13,356:INFO:Checking exceptions | |
| 2024-06-20 19:36:13,356:INFO:Importing libraries | |
| 2024-06-20 19:36:13,356:INFO:Copying training dataset | |
| 2024-06-20 19:36:13,359:INFO:Defining folds | |
| 2024-06-20 19:36:13,359:INFO:Declaring metric variables | |
| 2024-06-20 19:36:13,361:INFO:Importing untrained model | |
| 2024-06-20 19:36:13,376:INFO:CatBoost Regressor Imported successfully | |
| 2024-06-20 19:36:13,382:INFO:Starting cross validation | |
| 2024-06-20 19:36:13,383:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:16,893:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\model_selection\_validation.py:547: FitFailedWarning: | |
| 9 fits failed out of a total of 10. | |
| The score on these train-test partitions for these parameters will be set to 0.0. | |
| If these failures are not expected, you can try to debug them by setting error_score='raise'. | |
| Below are more details about the failures: | |
| -------------------------------------------------------------------------------- | |
| 9 fits failed with the following error: | |
| Traceback (most recent call last): | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\sklearn\model_selection\_validation.py", line 895, in _fit_and_score | |
| estimator.fit(X_train, y_train, **fit_params) | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\pycaret\internal\pipeline.py", line 278, in fit | |
| fitted_estimator = self._memory_fit( | |
| ^^^^^^^^^^^^^^^^^ | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\joblib\memory.py", line 353, in __call__ | |
| return self.func(*args, **kwargs) | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\pycaret\internal\pipeline.py", line 69, in _fit_one | |
| transformer.fit(*args) | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\catboost\core.py", line 5827, in fit | |
| return self._fit(X, y, cat_features, text_features, embedding_features, None, sample_weight, None, None, None, None, baseline, | |
| ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\catboost\core.py", line 2400, in _fit | |
| self._train( | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\catboost\core.py", line 1780, in _train | |
| self._object._train(train_pool, test_pool, params, allow_clear_pool, init_model._object if init_model else None) | |
| File "_catboost.pyx", line 4833, in _catboost._CatBoost._train | |
| File "_catboost.pyx", line 4882, in _catboost._CatBoost._train | |
| _catboost.CatBoostError: C:/Go_Agent/pipelines/BuildMaster/catboost.git/catboost/libs/train_lib/dir_helper.cpp:20: Can't create train working dir: catboost_info | |
| warnings.warn(some_fits_failed_message, FitFailedWarning) | |
| 2024-06-20 19:36:16,893:INFO:Calculating mean and std | |
| 2024-06-20 19:36:16,895:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:16,897:INFO:Uploading results into container | |
| 2024-06-20 19:36:16,897:INFO:Uploading model into container now | |
| 2024-06-20 19:36:16,897:INFO:_master_model_container: 18 | |
| 2024-06-20 19:36:16,898:INFO:_display_container: 2 | |
| 2024-06-20 19:36:16,898:INFO:<catboost.core.CatBoostRegressor object at 0x000002BBE3872D10> | |
| 2024-06-20 19:36:16,898:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:17,022:WARNING:create_model() for <catboost.core.CatBoostRegressor object at 0x000002BBE3872D10> raised an exception or returned all 0.0, trying without fit_kwargs: | |
| 2024-06-20 19:36:17,046:WARNING:Traceback (most recent call last): | |
| File "c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\pycaret\internal\pycaret_experiment\supervised_experiment.py", line 797, in compare_models | |
| np.sum( | |
| AssertionError | |
| 2024-06-20 19:36:17,047:INFO:Initializing create_model() | |
| 2024-06-20 19:36:17,047:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:17,047:INFO:Checking exceptions | |
| 2024-06-20 19:36:17,047:INFO:Importing libraries | |
| 2024-06-20 19:36:17,047:INFO:Copying training dataset | |
| 2024-06-20 19:36:17,050:INFO:Defining folds | |
| 2024-06-20 19:36:17,050:INFO:Declaring metric variables | |
| 2024-06-20 19:36:17,053:INFO:Importing untrained model | |
| 2024-06-20 19:36:17,056:INFO:CatBoost Regressor Imported successfully | |
| 2024-06-20 19:36:17,064:INFO:Starting cross validation | |
| 2024-06-20 19:36:17,064:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:24,419:INFO:Calculating mean and std | |
| 2024-06-20 19:36:24,420:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:24,421:INFO:Uploading results into container | |
| 2024-06-20 19:36:24,422:INFO:Uploading model into container now | |
| 2024-06-20 19:36:24,423:INFO:_master_model_container: 19 | |
| 2024-06-20 19:36:24,423:INFO:_display_container: 2 | |
| 2024-06-20 19:36:24,423:INFO:<catboost.core.CatBoostRegressor object at 0x000002BBE48AE910> | |
| 2024-06-20 19:36:24,423:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:24,548:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:24,548:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:24,565:INFO:Initializing Dummy Regressor | |
| 2024-06-20 19:36:24,565:INFO:Total runtime is 0.5172213117281594 minutes | |
| 2024-06-20 19:36:24,568:INFO:SubProcess create_model() called ================================== | |
| 2024-06-20 19:36:24,570:INFO:Initializing create_model() | |
| 2024-06-20 19:36:24,570:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, 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, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=<pycaret.internal.display.display.CommonDisplay object at 0x000002BBD987F0D0>, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:24,570:INFO:Checking exceptions | |
| 2024-06-20 19:36:24,570:INFO:Importing libraries | |
| 2024-06-20 19:36:24,570:INFO:Copying training dataset | |
| 2024-06-20 19:36:24,573:INFO:Defining folds | |
| 2024-06-20 19:36:24,573:INFO:Declaring metric variables | |
| 2024-06-20 19:36:24,576:INFO:Importing untrained model | |
| 2024-06-20 19:36:24,579:INFO:Dummy Regressor Imported successfully | |
| 2024-06-20 19:36:24,585:INFO:Starting cross validation | |
| 2024-06-20 19:36:24,586:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:24,651:INFO:Calculating mean and std | |
| 2024-06-20 19:36:24,654:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:24,655:INFO:Uploading results into container | |
| 2024-06-20 19:36:24,655:INFO:Uploading model into container now | |
| 2024-06-20 19:36:24,656:INFO:_master_model_container: 20 | |
| 2024-06-20 19:36:24,656:INFO:_display_container: 2 | |
| 2024-06-20 19:36:24,656:INFO:DummyRegressor() | |
| 2024-06-20 19:36:24,656:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:24,777:INFO:SubProcess create_model() end ================================== | |
| 2024-06-20 19:36:24,777:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:24,784:WARNING:c:\Users\kowom\Desktop\SN Keyce\PycaretVenv\Lib\site-packages\pycaret\internal\pycaret_experiment\supervised_experiment.py:339: FutureWarning: Styler.applymap has been deprecated. Use Styler.map instead. | |
| .applymap(highlight_cols, subset=["TT (Sec)"]) | |
| 2024-06-20 19:36:24,791:INFO:Initializing create_model() | |
| 2024-06-20 19:36:24,791:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, estimator=<catboost.core.CatBoostRegressor object at 0x000002BBE48AE910>, fold=KFold(n_splits=10, random_state=None, shuffle=False), round=4, cross_validation=False, predict=False, fit_kwargs={}, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=False, system=False, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:24,791:INFO:Checking exceptions | |
| 2024-06-20 19:36:24,793:INFO:Importing libraries | |
| 2024-06-20 19:36:24,793:INFO:Copying training dataset | |
| 2024-06-20 19:36:24,796:INFO:Defining folds | |
| 2024-06-20 19:36:24,796:INFO:Declaring metric variables | |
| 2024-06-20 19:36:24,796:INFO:Importing untrained model | |
| 2024-06-20 19:36:24,796:INFO:Declaring custom model | |
| 2024-06-20 19:36:24,797:INFO:CatBoost Regressor Imported successfully | |
| 2024-06-20 19:36:24,797:INFO:Cross validation set to False | |
| 2024-06-20 19:36:24,798:INFO:Fitting Model | |
| 2024-06-20 19:36:26,176:INFO:<catboost.core.CatBoostRegressor object at 0x000002BBE4008B10> | |
| 2024-06-20 19:36:26,176:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:36:26,307:INFO:_master_model_container: 20 | |
| 2024-06-20 19:36:26,308:INFO:_display_container: 2 | |
| 2024-06-20 19:36:26,308:INFO:<catboost.core.CatBoostRegressor object at 0x000002BBE4008B10> | |
| 2024-06-20 19:36:26,308:INFO:compare_models() successfully completed...................................... | |
| 2024-06-20 19:36:51,865:INFO:Initializing create_model() | |
| 2024-06-20 19:36:51,865:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, estimator=catboost, fold=None, round=4, cross_validation=True, predict=True, fit_kwargs=None, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=True, system=True, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:36:51,865:INFO:Checking exceptions | |
| 2024-06-20 19:36:51,878:INFO:Importing libraries | |
| 2024-06-20 19:36:51,878:INFO:Copying training dataset | |
| 2024-06-20 19:36:51,883:INFO:Defining folds | |
| 2024-06-20 19:36:51,883:INFO:Declaring metric variables | |
| 2024-06-20 19:36:51,887:INFO:Importing untrained model | |
| 2024-06-20 19:36:51,891:INFO:CatBoost Regressor Imported successfully | |
| 2024-06-20 19:36:51,898:INFO:Starting cross validation | |
| 2024-06-20 19:36:51,900:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:36:58,006:INFO:Calculating mean and std | |
| 2024-06-20 19:36:58,007:INFO:Creating metrics dataframe | |
| 2024-06-20 19:36:58,011:INFO:Finalizing model | |
| 2024-06-20 19:36:59,345:INFO:Uploading results into container | |
| 2024-06-20 19:36:59,346:INFO:Uploading model into container now | |
| 2024-06-20 19:36:59,353:INFO:_master_model_container: 21 | |
| 2024-06-20 19:36:59,353:INFO:_display_container: 3 | |
| 2024-06-20 19:36:59,353:INFO:<catboost.core.CatBoostRegressor object at 0x000002BBE41ED510> | |
| 2024-06-20 19:36:59,353:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:37:12,970:INFO:Initializing plot_model() | |
| 2024-06-20 19:37:12,970:INFO:plot_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, estimator=<catboost.core.CatBoostRegressor object at 0x000002BBE41ED510>, plot=residuals, scale=1, save=False, fold=None, fit_kwargs=None, plot_kwargs=None, groups=None, feature_name=None, label=False, verbose=True, system=True, display=None, display_format=None) | |
| 2024-06-20 19:37:12,970:INFO:Checking exceptions | |
| 2024-06-20 19:37:12,973:INFO:Preloading libraries | |
| 2024-06-20 19:37:12,976:INFO:Copying training dataset | |
| 2024-06-20 19:37:12,976:INFO:Plot type: residuals | |
| 2024-06-20 19:37:13,092:INFO:Fitting Model | |
| 2024-06-20 19:37:13,178:INFO:Scoring test/hold-out set | |
| 2024-06-20 19:37:13,598:INFO:Visual Rendered Successfully | |
| 2024-06-20 19:37:13,738:INFO:plot_model() successfully completed...................................... | |
| 2024-06-20 19:59:19,422:INFO:Initializing create_model() | |
| 2024-06-20 19:59:19,422:INFO:create_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, estimator=lightgbm, fold=None, round=4, cross_validation=True, predict=True, fit_kwargs=None, groups=None, refit=True, probability_threshold=None, experiment_custom_tags=None, verbose=True, system=True, add_to_model_list=True, metrics=None, display=None, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) | |
| 2024-06-20 19:59:19,422:INFO:Checking exceptions | |
| 2024-06-20 19:59:19,435:INFO:Importing libraries | |
| 2024-06-20 19:59:19,436:INFO:Copying training dataset | |
| 2024-06-20 19:59:19,438:INFO:Defining folds | |
| 2024-06-20 19:59:19,438:INFO:Declaring metric variables | |
| 2024-06-20 19:59:19,440:INFO:Importing untrained model | |
| 2024-06-20 19:59:19,443:INFO:Light Gradient Boosting Machine Imported successfully | |
| 2024-06-20 19:59:19,451:INFO:Starting cross validation | |
| 2024-06-20 19:59:19,452:INFO:Cross validating with KFold(n_splits=10, random_state=None, shuffle=False), n_jobs=-1 | |
| 2024-06-20 19:59:35,670:INFO:Calculating mean and std | |
| 2024-06-20 19:59:35,674:INFO:Creating metrics dataframe | |
| 2024-06-20 19:59:35,681:INFO:Finalizing model | |
| 2024-06-20 19:59:35,778:INFO:[LightGBM] [Info] Auto-choosing col-wise multi-threading, the overhead of testing was 0.000231 seconds. | |
| 2024-06-20 19:59:35,778:INFO:You can set `force_col_wise=true` to remove the overhead. | |
| 2024-06-20 19:59:35,778:INFO:[LightGBM] [Info] Total Bins 1054 | |
| 2024-06-20 19:59:35,779:INFO:[LightGBM] [Info] Number of data points in the train set: 824, number of used features: 8 | |
| 2024-06-20 19:59:35,779:INFO:[LightGBM] [Info] Start training from score 35.658204 | |
| 2024-06-20 19:59:35,789:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,794:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,794:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,800:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,806:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,816:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,820:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,826:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,834:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,837:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,842:INFO:[LightGBM] [Warning] No further splits with positive gain, best gain: -inf | |
| 2024-06-20 19:59:35,864:INFO:Uploading results into container | |
| 2024-06-20 19:59:35,865:INFO:Uploading model into container now | |
| 2024-06-20 19:59:35,877:INFO:_master_model_container: 22 | |
| 2024-06-20 19:59:35,877:INFO:_display_container: 4 | |
| 2024-06-20 19:59:35,878:INFO:LGBMRegressor(n_jobs=-1, random_state=123) | |
| 2024-06-20 19:59:35,878:INFO:create_model() successfully completed...................................... | |
| 2024-06-20 19:59:36,071:INFO:Initializing plot_model() | |
| 2024-06-20 19:59:36,071:INFO:plot_model(self=<pycaret.regression.oop.RegressionExperiment object at 0x000002BBD987D6D0>, estimator=LGBMRegressor(n_jobs=-1, random_state=123), plot=residuals, scale=1, save=False, fold=None, fit_kwargs=None, plot_kwargs=None, groups=None, feature_name=None, label=False, verbose=True, system=True, display=None, display_format=None) | |
| 2024-06-20 19:59:36,071:INFO:Checking exceptions | |
| 2024-06-20 19:59:36,073:INFO:Preloading libraries | |
| 2024-06-20 19:59:36,080:INFO:Copying training dataset | |
| 2024-06-20 19:59:36,081:INFO:Plot type: residuals | |
| 2024-06-20 19:59:36,250:INFO:Fitting Model | |
| 2024-06-20 19:59:36,291:INFO:Scoring test/hold-out set | |
| 2024-06-20 19:59:36,580:INFO:Visual Rendered Successfully | |
| 2024-06-20 19:59:36,700:INFO:plot_model() successfully completed...................................... | |