2024-11-25 13:56:54,832:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:11,977:INFO:PyCaret TSForecastingExperiment 2024-11-25 13:57:11,977:INFO:Logging name: ts-default-name 2024-11-25 13:57:11,977:INFO:ML Usecase: MLUsecase.TIME_SERIES 2024-11-25 13:57:11,977:INFO:version 3.3.2 2024-11-25 13:57:11,977:INFO:Initializing setup() 2024-11-25 13:57:11,977:INFO:self.USI: 8607 2024-11-25 13:57:11,977:INFO:self._variable_keys: {'exogenous_present', 'fh', 'memory', 'model_engines', '_ml_usecase', 'pipeline', 'index_type', 'exp_name_log', 'data', 'primary_sp_to_use', 'enforce_pi', 'significant_sps', 'candidate_sps', 'X_test', 'log_plots_param', 'gpu_param', 'y_test', 'enforce_exogenous', 'html_param', 'X_test_transformed', 'n_jobs_param', 'y_train', 'X', 'X_train', 'fold_generator', 'X_train_transformed', 'idx', 'y_train_transformed', 'y', 'fold_param', 'seasonality_present', 'gpu_n_jobs_param', 'approach_type', 'X_transformed', 'significant_sps_no_harmonics', 'exp_id', 'logging_param', 'y_test_transformed', 'USI', 'strictly_positive', 'y_transformed', 'seed', 'all_sps_to_use', '_available_plots'} 2024-11-25 13:57:11,977:INFO:Checking environment 2024-11-25 13:57:11,978:INFO:python_version: 3.11.6 2024-11-25 13:57:11,978:INFO:python_build: ('v3.11.6:8b6ee5ba3b', 'Oct 2 2023 11:18:21') 2024-11-25 13:57:11,978:INFO:machine: arm64 2024-11-25 13:57:11,978:INFO:platform: macOS-14.6.1-arm64-arm-64bit 2024-11-25 13:57:11,978:INFO:Memory: svmem(total=17179869184, available=6329368576, percent=63.2, used=7994540032, free=138870784, active=6180175872, inactive=6127566848, wired=1814364160) 2024-11-25 13:57:11,978:INFO:Physical Core: 8 2024-11-25 13:57:11,978:INFO:Logical Core: 8 2024-11-25 13:57:11,978:INFO:Checking libraries 2024-11-25 13:57:11,978:INFO:System: 2024-11-25 13:57:11,978:INFO: python: 3.11.6 (v3.11.6:8b6ee5ba3b, Oct 2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] 2024-11-25 13:57:11,978:INFO:executable: /usr/local/bin/python3 2024-11-25 13:57:11,978:INFO: machine: macOS-14.6.1-arm64-arm-64bit 2024-11-25 13:57:11,978:INFO:PyCaret required dependencies: 2024-11-25 13:57:12,152:INFO: pip: 24.3.1 2024-11-25 13:57:12,152:INFO: setuptools: 75.5.0 2024-11-25 13:57:12,152:INFO: pycaret: 3.3.2 2024-11-25 13:57:12,152:INFO: IPython: 8.29.0 2024-11-25 13:57:12,152:INFO: ipywidgets: 8.1.5 2024-11-25 13:57:12,152:INFO: tqdm: 4.67.0 2024-11-25 13:57:12,152:INFO: numpy: 1.26.4 2024-11-25 13:57:12,152:INFO: pandas: 2.1.4 2024-11-25 13:57:12,152:INFO: jinja2: 3.1.4 2024-11-25 13:57:12,152:INFO: scipy: 1.11.4 2024-11-25 13:57:12,152:INFO: joblib: 1.3.2 2024-11-25 13:57:12,152:INFO: sklearn: 1.4.2 2024-11-25 13:57:12,153:INFO: pyod: 2.0.2 2024-11-25 13:57:12,153:INFO: imblearn: 0.12.4 2024-11-25 13:57:12,153:INFO: category_encoders: 2.6.4 2024-11-25 13:57:12,153:INFO: lightgbm: 4.5.0 2024-11-25 13:57:12,153:INFO: numba: 0.60.0 2024-11-25 13:57:12,153:INFO: requests: 2.32.3 2024-11-25 13:57:12,153:INFO: matplotlib: 3.7.5 2024-11-25 13:57:12,153:INFO: scikitplot: 0.3.7 2024-11-25 13:57:12,153:INFO: yellowbrick: 1.5 2024-11-25 13:57:12,153:INFO: plotly: 5.24.1 2024-11-25 13:57:12,153:INFO: plotly-resampler: Not installed 2024-11-25 13:57:12,153:INFO: kaleido: 0.2.1 2024-11-25 13:57:12,153:INFO: schemdraw: 0.15 2024-11-25 13:57:12,153:INFO: statsmodels: 0.14.4 2024-11-25 13:57:12,153:INFO: sktime: 0.26.0 2024-11-25 13:57:12,153:INFO: tbats: 1.1.3 2024-11-25 13:57:12,153:INFO: pmdarima: 2.0.4 2024-11-25 13:57:12,153:INFO: psutil: 6.1.0 2024-11-25 13:57:12,153:INFO: markupsafe: 2.1.5 2024-11-25 13:57:12,153:INFO: pickle5: Not installed 2024-11-25 13:57:12,153:INFO: cloudpickle: 3.1.0 2024-11-25 13:57:12,153:INFO: deprecation: 2.1.0 2024-11-25 13:57:12,153:INFO: xxhash: 3.5.0 2024-11-25 13:57:12,153:INFO: wurlitzer: 3.1.1 2024-11-25 13:57:12,153:INFO:PyCaret optional dependencies: 2024-11-25 13:57:13,584:INFO: shap: Not installed 2024-11-25 13:57:13,584:INFO: interpret: Not installed 2024-11-25 13:57:13,584:INFO: umap: 0.5.7 2024-11-25 13:57:13,584:INFO: ydata_profiling: Not installed 2024-11-25 13:57:13,584:INFO: explainerdashboard: Not installed 2024-11-25 13:57:13,584:INFO: autoviz: Not installed 2024-11-25 13:57:13,584:INFO: fairlearn: Not installed 2024-11-25 13:57:13,584:INFO: deepchecks: Not installed 2024-11-25 13:57:13,584:INFO: xgboost: Not installed 2024-11-25 13:57:13,584:INFO: catboost: Not installed 2024-11-25 13:57:13,584:INFO: kmodes: Not installed 2024-11-25 13:57:13,584:INFO: mlxtend: Not installed 2024-11-25 13:57:13,584:INFO: statsforecast: Not installed 2024-11-25 13:57:13,584:INFO: tune_sklearn: Not installed 2024-11-25 13:57:13,584:INFO: ray: Not installed 2024-11-25 13:57:13,584:INFO: hyperopt: Not installed 2024-11-25 13:57:13,584:INFO: optuna: 4.1.0 2024-11-25 13:57:13,584:INFO: skopt: Not installed 2024-11-25 13:57:13,584:INFO: mlflow: Not installed 2024-11-25 13:57:13,584:INFO: gradio: 5.6.0 2024-11-25 13:57:13,584:INFO: fastapi: 0.115.5 2024-11-25 13:57:13,584:INFO: uvicorn: 0.32.0 2024-11-25 13:57:13,584:INFO: m2cgen: Not installed 2024-11-25 13:57:13,584:INFO: evidently: Not installed 2024-11-25 13:57:13,584:INFO: fugue: Not installed 2024-11-25 13:57:13,584:INFO: streamlit: Not installed 2024-11-25 13:57:13,584:INFO: prophet: 1.1.6 2024-11-25 13:57:13,584:INFO:None 2024-11-25 13:57:13,585:INFO:Set Forecast Horizon. 2024-11-25 13:57:13,585:INFO:Set up Train-Test Splits. 2024-11-25 13:57:13,612:INFO:Finished creating preprocessing pipeline. 2024-11-25 13:57:13,613:INFO:Pipeline: ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', DummyForecaster())]))]) 2024-11-25 13:57:13,613:INFO:Set up Seasonal Period. 2024-11-25 13:57:13,613:INFO:Setting the seasonal component type - 'add' or 'mul'. 2024-11-25 13:57:13,613:INFO:Checking if data is strictly positive. 2024-11-25 13:57:13,622:INFO:Creating final display dataframe. 2024-11-25 13:57:13,626:INFO:Setup Display Container: Description Value 0 session_id 42 1 Target target 2 Approach Univariate 3 Exogenous Variables Not Present 4 Original data shape (206, 1) 5 Transformed data shape (206, 1) 6 Transformed train set shape (182, 1) 7 Transformed test set shape (24, 1) 8 Rows with missing values 0.0% 9 Fold Generator ExpandingWindowSplitter 10 Fold Number 5 11 Enforce Prediction Interval False 12 Splits used for hyperparameters all 13 User Defined Seasonal Period(s) 12 14 Ignore Seasonality Test False 15 Seasonality Detection Algo user_defined 16 Max Period to Consider 60 17 Seasonal Period(s) Tested [12] 18 Significant Seasonal Period(s) [12] 19 Significant Seasonal Period(s) without Harmonics [12] 20 Remove Harmonics False 21 Harmonics Order Method harmonic_max 22 Num Seasonalities to Use 1 23 All Seasonalities to Use [12] 24 Primary Seasonality 12 25 Seasonality Present True 26 Seasonality Type mul 27 Target Strictly Positive True 28 Target White Noise No 29 Recommended d 1 30 Recommended Seasonal D 0 31 Preprocess False 32 CPU Jobs -1 33 Use GPU False 34 Log Experiment False 35 Experiment Name ts-default-name 36 USI 8607 2024-11-25 13:57:13,640:INFO:Engine successfully changes for model 'auto_arima' to 'pmdarima'. 2024-11-25 13:57:13,670:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,691:INFO:Engine for model 'lr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,691:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,691:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,691:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,691:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,692:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,692:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,692:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693: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]` 2024-11-25 13:57:13,693: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]` 2024-11-25 13:57:13,693:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,693:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,693:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,695:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,695:INFO:Engine for model 'lr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,695:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,697:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,697:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,697:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,697:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,698:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,699:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,699:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,700:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,700:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,701:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,701:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,701:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,702:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,702: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]` 2024-11-25 13:57:13,702: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]` 2024-11-25 13:57:13,702:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,702:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,702:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,702:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,702:INFO:Engine successfully changes for model 'lr_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,705:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,706:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,706:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,707:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,707:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,707:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,707:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,707:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,708: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]` 2024-11-25 13:57:13,708: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]` 2024-11-25 13:57:13,708:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,709:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,709:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,709:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,710:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,710:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,710:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,710:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,710:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,710:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,710:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,711:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,711:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,711:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,711:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,712:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,712:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,712:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,712:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,712: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]` 2024-11-25 13:57:13,712: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]` 2024-11-25 13:57:13,713:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,713:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,713:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,713:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,713:INFO:Engine successfully changes for model 'en_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,716:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,716:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,716:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,717:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,717:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,717:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,718:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,719:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,719:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,720:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,720:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,720:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,721:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,721:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,721: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]` 2024-11-25 13:57:13,722: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]` 2024-11-25 13:57:13,722:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,722:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,722:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,722:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,724:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,724:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,724:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,724:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,725:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,725:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,725:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726: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]` 2024-11-25 13:57:13,726: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]` 2024-11-25 13:57:13,726:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,726:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,726:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,727:INFO:Engine successfully changes for model 'ridge_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,728:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,728:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,728:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,728:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,729:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,730:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,730:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,731:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,731:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,731:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,732:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,732:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,732:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,732: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]` 2024-11-25 13:57:13,732: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]` 2024-11-25 13:57:13,732:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,733:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,733:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,733:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,736:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,737:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,737:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,738:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,738:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,739:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,740:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,741:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,741:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,741:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,741:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,742:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,742:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,742: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]` 2024-11-25 13:57:13,742: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]` 2024-11-25 13:57:13,742:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,742:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,742:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,742:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,743:INFO:Engine successfully changes for model 'lasso_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,745:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,746:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,746:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,746:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,747:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,747:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,747:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,748: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]` 2024-11-25 13:57:13,748: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]` 2024-11-25 13:57:13,748:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,749:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,749:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,749:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,750:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,750:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,750:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,750:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,751:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,752:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,752:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,752: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]` 2024-11-25 13:57:13,752: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]` 2024-11-25 13:57:13,752:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,752:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,752:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,752:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,752:INFO:Engine successfully changes for model 'lar_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,753:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,753:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,753:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,754:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,754:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,754:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,754:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,754:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755: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]` 2024-11-25 13:57:13,755: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]` 2024-11-25 13:57:13,755:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,755:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,755:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,756:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,758:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,758:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,758:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,759:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,760:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,760:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,761:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,761:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,761:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,761:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,762:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,762: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]` 2024-11-25 13:57:13,762: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]` 2024-11-25 13:57:13,762:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,762:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,762:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,762:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,762:INFO:Engine successfully changes for model 'llar_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,764:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,764:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,764:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,765:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,766:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,766:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,766: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]` 2024-11-25 13:57:13,766: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]` 2024-11-25 13:57:13,766:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,766:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,766:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,766:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,768:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,769:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,769:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,769:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770: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]` 2024-11-25 13:57:13,770: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]` 2024-11-25 13:57:13,770:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,770:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,770:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,770:INFO:Engine successfully changes for model 'br_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,771:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,772:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,772:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,773: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]` 2024-11-25 13:57:13,773: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]` 2024-11-25 13:57:13,773:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,774:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,774:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,774:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,775:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,775:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,775:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,776:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,777:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,777:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,777:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,778:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,778:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,778:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,778: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]` 2024-11-25 13:57:13,778: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]` 2024-11-25 13:57:13,778:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,779:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,779:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,779:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,779:INFO:Engine successfully changes for model 'huber_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,780:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,781:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,781:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,782:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,782: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]` 2024-11-25 13:57:13,782: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]` 2024-11-25 13:57:13,782:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,782:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,782:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,782:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,785:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,786:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787: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]` 2024-11-25 13:57:13,787: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]` 2024-11-25 13:57:13,787:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,787:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,787:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,787:INFO:Engine successfully changes for model 'par_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,788:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,789:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,790:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,790:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,790:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,790:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,791:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,791:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,791:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,791: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]` 2024-11-25 13:57:13,791: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]` 2024-11-25 13:57:13,791:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,792:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,792:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,792:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,794:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,797:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,798:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,798:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,798:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,799:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,799:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,799:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,799:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,799: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]` 2024-11-25 13:57:13,799: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]` 2024-11-25 13:57:13,799:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,800:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,800:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,800:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,800:INFO:Engine successfully changes for model 'omp_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,803:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,806:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,807:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,807:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,807:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,808:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,808:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,808:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,808: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]` 2024-11-25 13:57:13,808: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]` 2024-11-25 13:57:13,808:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,809:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,809:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,809:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,811:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,813:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,813: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]` 2024-11-25 13:57:13,813: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]` 2024-11-25 13:57:13,813:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,814:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,814:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,814:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,814:INFO:Engine successfully changes for model 'knn_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,815:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,816:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,816:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,816:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817: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]` 2024-11-25 13:57:13,817: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]` 2024-11-25 13:57:13,817:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,817:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,817:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,818:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,819:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,819:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,819:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,819:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,820:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,820:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,820: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]` 2024-11-25 13:57:13,820: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]` 2024-11-25 13:57:13,820:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,820:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,820:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,820:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,820:INFO:Engine successfully changes for model 'dt_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,821:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,822:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,822:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,823:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,823:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,823:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,823: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]` 2024-11-25 13:57:13,823: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]` 2024-11-25 13:57:13,823:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,823:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,824:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,824:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,826:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,829:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829: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]` 2024-11-25 13:57:13,829: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]` 2024-11-25 13:57:13,829:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,829:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,829:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,829:INFO:Engine successfully changes for model 'rf_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,831:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,835:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,835:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,835:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,835:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,836: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]` 2024-11-25 13:57:13,836: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]` 2024-11-25 13:57:13,836:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,836:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,836:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,836:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,839:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,842:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843: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]` 2024-11-25 13:57:13,843: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]` 2024-11-25 13:57:13,843:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,843:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,843:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,843:INFO:Engine successfully changes for model 'et_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,844:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,846:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,846:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,846:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,846: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]` 2024-11-25 13:57:13,846: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]` 2024-11-25 13:57:13,846:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,846:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,846:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,846:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,847:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,849:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,849:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,849:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,849: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]` 2024-11-25 13:57:13,849: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]` 2024-11-25 13:57:13,849:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,849:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,849:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,849:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,849:INFO:Engine successfully changes for model 'gbr_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,850:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,852:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,852:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,852: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]` 2024-11-25 13:57:13,852: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]` 2024-11-25 13:57:13,852:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,852:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,852:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,852:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,854:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,861:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,861:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,861: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]` 2024-11-25 13:57:13,861: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]` 2024-11-25 13:57:13,861:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,862:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,862:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,862:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,862:INFO:Engine successfully changes for model 'ada_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,864:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,869:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,869: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]` 2024-11-25 13:57:13,869: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]` 2024-11-25 13:57:13,869:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,869:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,869:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,869:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,870:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,872:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,872: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]` 2024-11-25 13:57:13,872: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]` 2024-11-25 13:57:13,872:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,872:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,872:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,872:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,872:INFO:Engine successfully changes for model 'xgboost_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,873:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,877: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]` 2024-11-25 13:57:13,878: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]` 2024-11-25 13:57:13,878:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,878:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,878:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,878:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,881:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,885: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]` 2024-11-25 13:57:13,885: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]` 2024-11-25 13:57:13,885:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,886:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,886:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,886:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,886:INFO:Engine successfully changes for model 'lightgbm_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,888:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,890: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]` 2024-11-25 13:57:13,890: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]` 2024-11-25 13:57:13,890:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,890:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,890:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,891:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,893: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]` 2024-11-25 13:57:13,893: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]` 2024-11-25 13:57:13,893:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 13:57:13,893:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,893:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,893:INFO:Engine successfully changes for model 'catboost_cds_dt' to 'sklearn'. 2024-11-25 13:57:13,894:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,896: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]` 2024-11-25 13:57:13,896: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]` 2024-11-25 13:57:13,896:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,896:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,897:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,899: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]` 2024-11-25 13:57:13,899: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]` 2024-11-25 13:57:13,900:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,900:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,901:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,902: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]` 2024-11-25 13:57:13,902: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]` 2024-11-25 13:57:13,902:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,902:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,903:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:13,905: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]` 2024-11-25 13:57:13,905: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]` 2024-11-25 13:57:13,905:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,905:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 13:57:13,906:INFO:setup() successfully completed in 1.93s............... 2024-11-25 13:57:13,906:INFO:Initializing compare_models() 2024-11-25 13:57:13,906:INFO:compare_models(self=, include=None, exclude=None, fold=None, round=4, cross_validation=True, sort=MASE, 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': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MASE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }) 2024-11-25 13:57:13,906:INFO:Checking exceptions 2024-11-25 13:57:13,906:INFO:Preparing display monitor 2024-11-25 13:57:13,954:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/internal/pycaret_experiment/supervised_experiment.py:713: UserWarning: Unsupported estimator `ensemble_forecaster` for method `compare_models()`, removing from model_library warnings.warn( 2024-11-25 13:57:13,954:INFO:Initializing Naive Forecaster 2024-11-25 13:57:13,954:INFO:Total runtime is 1.0530153910319011e-06 minutes 2024-11-25 13:57:13,955:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:13,956:INFO:Initializing create_model() 2024-11-25 13:57:13,956:INFO:create_model(self=, estimator=naive, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:13,956:INFO:Checking exceptions 2024-11-25 13:57:13,956:INFO:Importing libraries 2024-11-25 13:57:13,956:INFO:Copying training dataset 2024-11-25 13:57:13,957:INFO:Defining folds 2024-11-25 13:57:13,957:INFO:Declaring metric variables 2024-11-25 13:57:13,958:INFO:Importing untrained model 2024-11-25 13:57:13,959:INFO:Naive Forecaster Imported successfully 2024-11-25 13:57:13,971:INFO:Starting cross validation 2024-11-25 13:57:13,990:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:16,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,613:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,613:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,663:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,663:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,676:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,676:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,687:INFO:Calculating mean and std 2024-11-25 13:57:16,690:INFO:Creating metrics dataframe 2024-11-25 13:57:16,697:INFO:Uploading results into container 2024-11-25 13:57:16,697:INFO:Uploading model into container now 2024-11-25 13:57:16,698:INFO:_master_model_container: 1 2024-11-25 13:57:16,698:INFO:_display_container: 2 2024-11-25 13:57:16,699:INFO:NaiveForecaster() 2024-11-25 13:57:16,699:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:16,815:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:16,815:INFO:Creating metrics dataframe 2024-11-25 13:57:16,818:INFO:Initializing Grand Means Forecaster 2024-11-25 13:57:16,818:INFO:Total runtime is 0.047730700174967444 minutes 2024-11-25 13:57:16,819:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:16,819:INFO:Initializing create_model() 2024-11-25 13:57:16,819:INFO:create_model(self=, estimator=grand_means, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:16,819:INFO:Checking exceptions 2024-11-25 13:57:16,819:INFO:Importing libraries 2024-11-25 13:57:16,820:INFO:Copying training dataset 2024-11-25 13:57:16,821:INFO:Defining folds 2024-11-25 13:57:16,821:INFO:Declaring metric variables 2024-11-25 13:57:16,822:INFO:Importing untrained model 2024-11-25 13:57:16,824:INFO:Grand Means Forecaster Imported successfully 2024-11-25 13:57:16,826:INFO:Starting cross validation 2024-11-25 13:57:16,827:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:16,848:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,848:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,857:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,857:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,857:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,857:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,858:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:16,859:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,658:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,658:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,660:INFO:Calculating mean and std 2024-11-25 13:57:17,661:INFO:Creating metrics dataframe 2024-11-25 13:57:17,663:INFO:Uploading results into container 2024-11-25 13:57:17,663:INFO:Uploading model into container now 2024-11-25 13:57:17,663:INFO:_master_model_container: 2 2024-11-25 13:57:17,663:INFO:_display_container: 2 2024-11-25 13:57:17,663:INFO:NaiveForecaster(strategy='mean') 2024-11-25 13:57:17,663:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:17,734:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:17,734:INFO:Creating metrics dataframe 2024-11-25 13:57:17,738:INFO:Initializing Seasonal Naive Forecaster 2024-11-25 13:57:17,738:INFO:Total runtime is 0.06305650075276692 minutes 2024-11-25 13:57:17,739:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:17,739:INFO:Initializing create_model() 2024-11-25 13:57:17,739:INFO:create_model(self=, estimator=snaive, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:17,739:INFO:Checking exceptions 2024-11-25 13:57:17,739:INFO:Importing libraries 2024-11-25 13:57:17,739:INFO:Copying training dataset 2024-11-25 13:57:17,740:INFO:Defining folds 2024-11-25 13:57:17,740:INFO:Declaring metric variables 2024-11-25 13:57:17,741:INFO:Importing untrained model 2024-11-25 13:57:17,742:INFO:Seasonal Naive Forecaster Imported successfully 2024-11-25 13:57:17,745:INFO:Starting cross validation 2024-11-25 13:57:17,746:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:17,776:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,776:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,787:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,796:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:17,796:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,570:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,570:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,578:INFO:Calculating mean and std 2024-11-25 13:57:18,578:INFO:Creating metrics dataframe 2024-11-25 13:57:18,580:INFO:Uploading results into container 2024-11-25 13:57:18,580:INFO:Uploading model into container now 2024-11-25 13:57:18,580:INFO:_master_model_container: 3 2024-11-25 13:57:18,580:INFO:_display_container: 2 2024-11-25 13:57:18,580:INFO:NaiveForecaster(sp=12) 2024-11-25 13:57:18,580:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:18,650:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:18,650:INFO:Creating metrics dataframe 2024-11-25 13:57:18,654:INFO:Initializing Polynomial Trend Forecaster 2024-11-25 13:57:18,654:INFO:Total runtime is 0.07832766771316528 minutes 2024-11-25 13:57:18,655:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:18,655:INFO:Initializing create_model() 2024-11-25 13:57:18,655:INFO:create_model(self=, estimator=polytrend, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:18,656:INFO:Checking exceptions 2024-11-25 13:57:18,656:INFO:Importing libraries 2024-11-25 13:57:18,656:INFO:Copying training dataset 2024-11-25 13:57:18,657:INFO:Defining folds 2024-11-25 13:57:18,657:INFO:Declaring metric variables 2024-11-25 13:57:18,658:INFO:Importing untrained model 2024-11-25 13:57:18,659:INFO:Polynomial Trend Forecaster Imported successfully 2024-11-25 13:57:18,662:INFO:Starting cross validation 2024-11-25 13:57:18,662:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:18,681:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,681:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,687:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,687:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,688:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,688:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,694:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:18,694:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,450:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,450:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,453:INFO:Calculating mean and std 2024-11-25 13:57:19,453:INFO:Creating metrics dataframe 2024-11-25 13:57:19,454:INFO:Uploading results into container 2024-11-25 13:57:19,455:INFO:Uploading model into container now 2024-11-25 13:57:19,455:INFO:_master_model_container: 4 2024-11-25 13:57:19,455:INFO:_display_container: 2 2024-11-25 13:57:19,455:INFO:PolynomialTrendForecaster() 2024-11-25 13:57:19,455:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:19,527:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:19,527:INFO:Creating metrics dataframe 2024-11-25 13:57:19,530:INFO:Initializing ARIMA 2024-11-25 13:57:19,530:INFO:Total runtime is 0.0929239312807719 minutes 2024-11-25 13:57:19,531:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:19,531:INFO:Initializing create_model() 2024-11-25 13:57:19,531:INFO:create_model(self=, estimator=arima, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:19,531:INFO:Checking exceptions 2024-11-25 13:57:19,531:INFO:Importing libraries 2024-11-25 13:57:19,531:INFO:Copying training dataset 2024-11-25 13:57:19,532:INFO:Defining folds 2024-11-25 13:57:19,533:INFO:Declaring metric variables 2024-11-25 13:57:19,534:INFO:Importing untrained model 2024-11-25 13:57:19,535:INFO:ARIMA Imported successfully 2024-11-25 13:57:19,538:INFO:Starting cross validation 2024-11-25 13:57:19,538:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:19,585:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,585:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,585:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,586:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,598:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,599:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,603:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,603:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,604:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,604:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:19,606:INFO:Calculating mean and std 2024-11-25 13:57:19,606:INFO:Creating metrics dataframe 2024-11-25 13:57:19,608:INFO:Uploading results into container 2024-11-25 13:57:19,608:INFO:Uploading model into container now 2024-11-25 13:57:19,608:INFO:_master_model_container: 5 2024-11-25 13:57:19,608:INFO:_display_container: 2 2024-11-25 13:57:19,609:INFO:ARIMA(seasonal_order=(0, 1, 0, 12)) 2024-11-25 13:57:19,609:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:19,674:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:19,674:INFO:Creating metrics dataframe 2024-11-25 13:57:19,677:INFO:Initializing Auto ARIMA 2024-11-25 13:57:19,677:INFO:Total runtime is 0.09537796576817831 minutes 2024-11-25 13:57:19,679:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:19,679:INFO:Initializing create_model() 2024-11-25 13:57:19,679:INFO:create_model(self=, estimator=auto_arima, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:19,679:INFO:Checking exceptions 2024-11-25 13:57:19,679:INFO:Importing libraries 2024-11-25 13:57:19,679:INFO:Copying training dataset 2024-11-25 13:57:19,680:INFO:Defining folds 2024-11-25 13:57:19,680:INFO:Declaring metric variables 2024-11-25 13:57:19,681:INFO:Importing untrained model 2024-11-25 13:57:19,683:INFO:Auto ARIMA Imported successfully 2024-11-25 13:57:19,685:INFO:Starting cross validation 2024-11-25 13:57:19,686:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:21,494:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:21,494:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:21,575:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:21,576:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:22,493:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:22,493:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:24,249:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:24,249:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,047:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,047:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,057:INFO:Calculating mean and std 2024-11-25 13:57:26,058:INFO:Creating metrics dataframe 2024-11-25 13:57:26,059:INFO:Uploading results into container 2024-11-25 13:57:26,059:INFO:Uploading model into container now 2024-11-25 13:57:26,060:INFO:_master_model_container: 6 2024-11-25 13:57:26,060:INFO:_display_container: 2 2024-11-25 13:57:26,061:INFO:AutoARIMA(random_state=42, sp=12, suppress_warnings=True) 2024-11-25 13:57:26,061:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,126:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,126:INFO:Creating metrics dataframe 2024-11-25 13:57:26,129:INFO:Initializing Exponential Smoothing 2024-11-25 13:57:26,129:INFO:Total runtime is 0.20291503270467123 minutes 2024-11-25 13:57:26,130:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,130:INFO:Initializing create_model() 2024-11-25 13:57:26,130:INFO:create_model(self=, estimator=exp_smooth, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,131:INFO:Checking exceptions 2024-11-25 13:57:26,131:INFO:Importing libraries 2024-11-25 13:57:26,131:INFO:Copying training dataset 2024-11-25 13:57:26,132:INFO:Defining folds 2024-11-25 13:57:26,132:INFO:Declaring metric variables 2024-11-25 13:57:26,133:INFO:Importing untrained model 2024-11-25 13:57:26,134:INFO:Exponential Smoothing Imported successfully 2024-11-25 13:57:26,137:INFO:Starting cross validation 2024-11-25 13:57:26,138:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:26,183:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,183:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,186:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,186:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,192:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,192:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,199:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,200:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,209:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,209:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,219:INFO:Calculating mean and std 2024-11-25 13:57:26,219:INFO:Creating metrics dataframe 2024-11-25 13:57:26,221:INFO:Uploading results into container 2024-11-25 13:57:26,221:INFO:Uploading model into container now 2024-11-25 13:57:26,221:INFO:_master_model_container: 7 2024-11-25 13:57:26,221:INFO:_display_container: 2 2024-11-25 13:57:26,222:INFO:ExponentialSmoothing(seasonal='mul', sp=12, trend='add') 2024-11-25 13:57:26,222:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,293:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,293:INFO:Creating metrics dataframe 2024-11-25 13:57:26,297:INFO:Initializing ETS 2024-11-25 13:57:26,297:INFO:Total runtime is 0.2057072162628174 minutes 2024-11-25 13:57:26,298:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,298:INFO:Initializing create_model() 2024-11-25 13:57:26,298:INFO:create_model(self=, estimator=ets, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,298:INFO:Checking exceptions 2024-11-25 13:57:26,298:INFO:Importing libraries 2024-11-25 13:57:26,298:INFO:Copying training dataset 2024-11-25 13:57:26,299:INFO:Defining folds 2024-11-25 13:57:26,299:INFO:Declaring metric variables 2024-11-25 13:57:26,300:INFO:Importing untrained model 2024-11-25 13:57:26,302:INFO:ETS Imported successfully 2024-11-25 13:57:26,304:INFO:Starting cross validation 2024-11-25 13:57:26,305:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:26,352:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,353:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,363:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,364:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,370:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,370:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,372:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,372:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,375:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,375:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,387:INFO:Calculating mean and std 2024-11-25 13:57:26,388:INFO:Creating metrics dataframe 2024-11-25 13:57:26,389:INFO:Uploading results into container 2024-11-25 13:57:26,389:INFO:Uploading model into container now 2024-11-25 13:57:26,389:INFO:_master_model_container: 8 2024-11-25 13:57:26,389:INFO:_display_container: 2 2024-11-25 13:57:26,389:INFO:AutoETS(seasonal='mul', sp=12, trend='add') 2024-11-25 13:57:26,389:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,455:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,455:INFO:Creating metrics dataframe 2024-11-25 13:57:26,459:INFO:Initializing Theta Forecaster 2024-11-25 13:57:26,459:INFO:Total runtime is 0.20841036637624108 minutes 2024-11-25 13:57:26,460:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,460:INFO:Initializing create_model() 2024-11-25 13:57:26,460:INFO:create_model(self=, estimator=theta, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,460:INFO:Checking exceptions 2024-11-25 13:57:26,461:INFO:Importing libraries 2024-11-25 13:57:26,461:INFO:Copying training dataset 2024-11-25 13:57:26,462:INFO:Defining folds 2024-11-25 13:57:26,462:INFO:Declaring metric variables 2024-11-25 13:57:26,463:INFO:Importing untrained model 2024-11-25 13:57:26,464:INFO:Theta Forecaster Imported successfully 2024-11-25 13:57:26,467:INFO:Starting cross validation 2024-11-25 13:57:26,467:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:26,490:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,490:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,491:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,491:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,494:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,494:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,498:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,498:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,504:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,504:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,509:INFO:Calculating mean and std 2024-11-25 13:57:26,510:INFO:Creating metrics dataframe 2024-11-25 13:57:26,511:INFO:Uploading results into container 2024-11-25 13:57:26,511:INFO:Uploading model into container now 2024-11-25 13:57:26,512:INFO:_master_model_container: 9 2024-11-25 13:57:26,512:INFO:_display_container: 2 2024-11-25 13:57:26,512:INFO:ThetaForecaster(sp=12) 2024-11-25 13:57:26,512:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,578:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,578:INFO:Creating metrics dataframe 2024-11-25 13:57:26,582:INFO:Initializing STLF 2024-11-25 13:57:26,582:INFO:Total runtime is 0.21045573552449548 minutes 2024-11-25 13:57:26,583:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,583:INFO:Initializing create_model() 2024-11-25 13:57:26,583:INFO:create_model(self=, estimator=stlf, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,583:INFO:Checking exceptions 2024-11-25 13:57:26,583:INFO:Importing libraries 2024-11-25 13:57:26,583:INFO:Copying training dataset 2024-11-25 13:57:26,584:INFO:Defining folds 2024-11-25 13:57:26,584:INFO:Declaring metric variables 2024-11-25 13:57:26,585:INFO:Importing untrained model 2024-11-25 13:57:26,587:INFO:STLF Imported successfully 2024-11-25 13:57:26,589:INFO:Starting cross validation 2024-11-25 13:57:26,590:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:26,617:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,617:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,618:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,618:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,620:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,620:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,621:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,621:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,626:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,626:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,632:INFO:Calculating mean and std 2024-11-25 13:57:26,632:INFO:Creating metrics dataframe 2024-11-25 13:57:26,634:INFO:Uploading results into container 2024-11-25 13:57:26,634:INFO:Uploading model into container now 2024-11-25 13:57:26,634:INFO:_master_model_container: 10 2024-11-25 13:57:26,634:INFO:_display_container: 2 2024-11-25 13:57:26,634:INFO:STLForecaster(sp=12) 2024-11-25 13:57:26,634:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,700:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,700:INFO:Creating metrics dataframe 2024-11-25 13:57:26,704:INFO:Initializing Croston 2024-11-25 13:57:26,704:INFO:Total runtime is 0.21250266631444298 minutes 2024-11-25 13:57:26,706:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,706:INFO:Initializing create_model() 2024-11-25 13:57:26,706:INFO:create_model(self=, estimator=croston, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,706:INFO:Checking exceptions 2024-11-25 13:57:26,706:INFO:Importing libraries 2024-11-25 13:57:26,706:INFO:Copying training dataset 2024-11-25 13:57:26,707:INFO:Defining folds 2024-11-25 13:57:26,707:INFO:Declaring metric variables 2024-11-25 13:57:26,708:INFO:Importing untrained model 2024-11-25 13:57:26,709:INFO:Croston Imported successfully 2024-11-25 13:57:26,712:INFO:Starting cross validation 2024-11-25 13:57:26,713:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:26,724:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,725:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,727:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,727:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,734:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,734:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:26,742:INFO:Calculating mean and std 2024-11-25 13:57:26,742:INFO:Creating metrics dataframe 2024-11-25 13:57:26,744:INFO:Uploading results into container 2024-11-25 13:57:26,744:INFO:Uploading model into container now 2024-11-25 13:57:26,744:INFO:_master_model_container: 11 2024-11-25 13:57:26,744:INFO:_display_container: 2 2024-11-25 13:57:26,744:INFO:Croston() 2024-11-25 13:57:26,744:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:26,810:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:26,810:INFO:Creating metrics dataframe 2024-11-25 13:57:26,814:INFO:Initializing Linear w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:26,815:INFO:Total runtime is 0.21433846950531008 minutes 2024-11-25 13:57:26,816:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:26,816:INFO:Initializing create_model() 2024-11-25 13:57:26,816:INFO:create_model(self=, estimator=lr_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:26,816:INFO:Checking exceptions 2024-11-25 13:57:26,816:INFO:Importing libraries 2024-11-25 13:57:26,816:INFO:Copying training dataset 2024-11-25 13:57:26,817:INFO:Defining folds 2024-11-25 13:57:26,817:INFO:Declaring metric variables 2024-11-25 13:57:26,818:INFO:Importing untrained model 2024-11-25 13:57:26,819:INFO:Linear w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:26,822:INFO:Starting cross validation 2024-11-25 13:57:26,823:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:27,056:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,056:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,056:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,056:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,056:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,250:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,250:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,263:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,263:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,270:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,270:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,276:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,276:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,289:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,289:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,303:INFO:Calculating mean and std 2024-11-25 13:57:27,303:INFO:Creating metrics dataframe 2024-11-25 13:57:27,305:INFO:Uploading results into container 2024-11-25 13:57:27,305:INFO:Uploading model into container now 2024-11-25 13:57:27,305:INFO:_master_model_container: 12 2024-11-25 13:57:27,305:INFO:_display_container: 2 2024-11-25 13:57:27,307:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LinearRegression(n_jobs=-1), sp=12, window_length=12) 2024-11-25 13:57:27,307:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:27,374:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:27,374:INFO:Creating metrics dataframe 2024-11-25 13:57:27,377:INFO:Initializing Elastic Net w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:27,377:INFO:Total runtime is 0.22371761798858644 minutes 2024-11-25 13:57:27,379:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:27,379:INFO:Initializing create_model() 2024-11-25 13:57:27,379:INFO:create_model(self=, estimator=en_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:27,379:INFO:Checking exceptions 2024-11-25 13:57:27,379:INFO:Importing libraries 2024-11-25 13:57:27,379:INFO:Copying training dataset 2024-11-25 13:57:27,380:INFO:Defining folds 2024-11-25 13:57:27,380:INFO:Declaring metric variables 2024-11-25 13:57:27,381:INFO:Importing untrained model 2024-11-25 13:57:27,382:INFO:Elastic Net w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:27,385:INFO:Starting cross validation 2024-11-25 13:57:27,385:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:27,495:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,600:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,600:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,609:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,609:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,620:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,620:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,647:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,648:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,704:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,704:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:27,715:INFO:Calculating mean and std 2024-11-25 13:57:27,715:INFO:Creating metrics dataframe 2024-11-25 13:57:27,717:INFO:Uploading results into container 2024-11-25 13:57:27,717:INFO:Uploading model into container now 2024-11-25 13:57:27,717:INFO:_master_model_container: 13 2024-11-25 13:57:27,717:INFO:_display_container: 2 2024-11-25 13:57:27,718:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=ElasticNet(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:27,718:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:27,784:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:27,784:INFO:Creating metrics dataframe 2024-11-25 13:57:27,788:INFO:Initializing Ridge w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:27,788:INFO:Total runtime is 0.23056913216908775 minutes 2024-11-25 13:57:27,790:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:27,790:INFO:Initializing create_model() 2024-11-25 13:57:27,790:INFO:create_model(self=, estimator=ridge_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:27,790:INFO:Checking exceptions 2024-11-25 13:57:27,790:INFO:Importing libraries 2024-11-25 13:57:27,790:INFO:Copying training dataset 2024-11-25 13:57:27,791:INFO:Defining folds 2024-11-25 13:57:27,791:INFO:Declaring metric variables 2024-11-25 13:57:27,792:INFO:Importing untrained model 2024-11-25 13:57:27,793:INFO:Ridge w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:27,796:INFO:Starting cross validation 2024-11-25 13:57:27,797:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:27,924:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:27,958:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:28,030:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,030:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,033:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,033:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,047:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,048:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,120:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,120:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,154:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,155:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,166:INFO:Calculating mean and std 2024-11-25 13:57:28,166:INFO:Creating metrics dataframe 2024-11-25 13:57:28,167:INFO:Uploading results into container 2024-11-25 13:57:28,167:INFO:Uploading model into container now 2024-11-25 13:57:28,168:INFO:_master_model_container: 14 2024-11-25 13:57:28,168:INFO:_display_container: 2 2024-11-25 13:57:28,169:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=Ridge(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:28,169:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:28,234:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:28,234:INFO:Creating metrics dataframe 2024-11-25 13:57:28,239:INFO:Initializing Lasso w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:28,239:INFO:Total runtime is 0.2380847533543905 minutes 2024-11-25 13:57:28,240:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:28,241:INFO:Initializing create_model() 2024-11-25 13:57:28,241:INFO:create_model(self=, estimator=lasso_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:28,241:INFO:Checking exceptions 2024-11-25 13:57:28,241:INFO:Importing libraries 2024-11-25 13:57:28,241:INFO:Copying training dataset 2024-11-25 13:57:28,242:INFO:Defining folds 2024-11-25 13:57:28,242:INFO:Declaring metric variables 2024-11-25 13:57:28,243:INFO:Importing untrained model 2024-11-25 13:57:28,245:INFO:Lasso w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:28,247:INFO:Starting cross validation 2024-11-25 13:57:28,248:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:28,483:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,483:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,489:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,490:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,499:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,500:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,501:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,501:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,516:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,516:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,519:INFO:Calculating mean and std 2024-11-25 13:57:28,519:INFO:Creating metrics dataframe 2024-11-25 13:57:28,521:INFO:Uploading results into container 2024-11-25 13:57:28,521:INFO:Uploading model into container now 2024-11-25 13:57:28,521:INFO:_master_model_container: 15 2024-11-25 13:57:28,521:INFO:_display_container: 2 2024-11-25 13:57:28,523:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=Lasso(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:28,523:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:28,589:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:28,589:INFO:Creating metrics dataframe 2024-11-25 13:57:28,593:INFO:Initializing Lasso Least Angular Regressor w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:28,593:INFO:Total runtime is 0.24398570060729985 minutes 2024-11-25 13:57:28,595:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:28,595:INFO:Initializing create_model() 2024-11-25 13:57:28,595:INFO:create_model(self=, estimator=llar_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:28,595:INFO:Checking exceptions 2024-11-25 13:57:28,595:INFO:Importing libraries 2024-11-25 13:57:28,596:INFO:Copying training dataset 2024-11-25 13:57:28,596:INFO:Defining folds 2024-11-25 13:57:28,596:INFO:Declaring metric variables 2024-11-25 13:57:28,597:INFO:Importing untrained model 2024-11-25 13:57:28,599:INFO:Lasso Least Angular Regressor w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:28,601:INFO:Starting cross validation 2024-11-25 13:57:28,602:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:28,818:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,818:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,828:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,828:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,838:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,838:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,838:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,838:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:28,843:INFO:Calculating mean and std 2024-11-25 13:57:28,843:INFO:Creating metrics dataframe 2024-11-25 13:57:28,845:INFO:Uploading results into container 2024-11-25 13:57:28,845:INFO:Uploading model into container now 2024-11-25 13:57:28,845:INFO:_master_model_container: 16 2024-11-25 13:57:28,845:INFO:_display_container: 2 2024-11-25 13:57:28,847:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LassoLars(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:28,847:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:28,913:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:28,913:INFO:Creating metrics dataframe 2024-11-25 13:57:28,918:INFO:Initializing Bayesian Ridge w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:28,918:INFO:Total runtime is 0.2493886510531108 minutes 2024-11-25 13:57:28,919:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:28,919:INFO:Initializing create_model() 2024-11-25 13:57:28,919:INFO:create_model(self=, estimator=br_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:28,919:INFO:Checking exceptions 2024-11-25 13:57:28,919:INFO:Importing libraries 2024-11-25 13:57:28,919:INFO:Copying training dataset 2024-11-25 13:57:28,920:INFO:Defining folds 2024-11-25 13:57:28,920:INFO:Declaring metric variables 2024-11-25 13:57:28,921:INFO:Importing untrained model 2024-11-25 13:57:28,923:INFO:Bayesian Ridge w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:28,925:INFO:Starting cross validation 2024-11-25 13:57:28,926:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:29,138:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,139:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,152:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,152:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,154:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,154:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,158:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,158:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,177:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,177:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,183:INFO:Calculating mean and std 2024-11-25 13:57:29,183:INFO:Creating metrics dataframe 2024-11-25 13:57:29,185:INFO:Uploading results into container 2024-11-25 13:57:29,185:INFO:Uploading model into container now 2024-11-25 13:57:29,185:INFO:_master_model_container: 17 2024-11-25 13:57:29,185:INFO:_display_container: 2 2024-11-25 13:57:29,186:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=BayesianRidge(), sp=12, window_length=12) 2024-11-25 13:57:29,186:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:29,252:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:29,252:INFO:Creating metrics dataframe 2024-11-25 13:57:29,256:INFO:Initializing Huber w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:29,256:INFO:Total runtime is 0.25503636598587043 minutes 2024-11-25 13:57:29,258:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:29,258:INFO:Initializing create_model() 2024-11-25 13:57:29,258:INFO:create_model(self=, estimator=huber_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:29,258:INFO:Checking exceptions 2024-11-25 13:57:29,258:INFO:Importing libraries 2024-11-25 13:57:29,258:INFO:Copying training dataset 2024-11-25 13:57:29,259:INFO:Defining folds 2024-11-25 13:57:29,259:INFO:Declaring metric variables 2024-11-25 13:57:29,260:INFO:Importing untrained model 2024-11-25 13:57:29,261:INFO:Huber w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:29,264:INFO:Starting cross validation 2024-11-25 13:57:29,265:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:29,489:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,489:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,502:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,502:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,506:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,506:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,507:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,507:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,510:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,510:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,521:INFO:Calculating mean and std 2024-11-25 13:57:29,522:INFO:Creating metrics dataframe 2024-11-25 13:57:29,523:INFO:Uploading results into container 2024-11-25 13:57:29,523:INFO:Uploading model into container now 2024-11-25 13:57:29,523:INFO:_master_model_container: 18 2024-11-25 13:57:29,523:INFO:_display_container: 2 2024-11-25 13:57:29,525:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=HuberRegressor(), sp=12, window_length=12) 2024-11-25 13:57:29,525:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:29,591:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:29,591:INFO:Creating metrics dataframe 2024-11-25 13:57:29,595:INFO:Initializing Orthogonal Matching Pursuit w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:29,595:INFO:Total runtime is 0.26068516572316497 minutes 2024-11-25 13:57:29,597:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:29,597:INFO:Initializing create_model() 2024-11-25 13:57:29,597:INFO:create_model(self=, estimator=omp_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:29,597:INFO:Checking exceptions 2024-11-25 13:57:29,597:INFO:Importing libraries 2024-11-25 13:57:29,597:INFO:Copying training dataset 2024-11-25 13:57:29,598:INFO:Defining folds 2024-11-25 13:57:29,598:INFO:Declaring metric variables 2024-11-25 13:57:29,599:INFO:Importing untrained model 2024-11-25 13:57:29,601:INFO:Orthogonal Matching Pursuit w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:29,604:INFO:Starting cross validation 2024-11-25 13:57:29,604:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:29,823:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,823:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,829:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,829:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,847:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,848:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,850:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,851:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:29,863:INFO:Calculating mean and std 2024-11-25 13:57:29,863:INFO:Creating metrics dataframe 2024-11-25 13:57:29,865:INFO:Uploading results into container 2024-11-25 13:57:29,865:INFO:Uploading model into container now 2024-11-25 13:57:29,865:INFO:_master_model_container: 19 2024-11-25 13:57:29,865:INFO:_display_container: 2 2024-11-25 13:57:29,866:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=OrthogonalMatchingPursuit(), sp=12, window_length=12) 2024-11-25 13:57:29,866:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:29,932:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:29,932:INFO:Creating metrics dataframe 2024-11-25 13:57:29,937:INFO:Initializing K Neighbors w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:29,937:INFO:Total runtime is 0.26637374957402554 minutes 2024-11-25 13:57:29,938:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:29,938:INFO:Initializing create_model() 2024-11-25 13:57:29,938:INFO:create_model(self=, estimator=knn_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:29,938:INFO:Checking exceptions 2024-11-25 13:57:29,938:INFO:Importing libraries 2024-11-25 13:57:29,938:INFO:Copying training dataset 2024-11-25 13:57:29,939:INFO:Defining folds 2024-11-25 13:57:29,939:INFO:Declaring metric variables 2024-11-25 13:57:29,940:INFO:Importing untrained model 2024-11-25 13:57:29,941:INFO:K Neighbors w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:29,944:INFO:Starting cross validation 2024-11-25 13:57:29,945:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:30,482:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,482:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,483:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,483:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,489:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,489:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,503:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,503:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,503:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,504:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,514:INFO:Calculating mean and std 2024-11-25 13:57:30,515:INFO:Creating metrics dataframe 2024-11-25 13:57:30,516:INFO:Uploading results into container 2024-11-25 13:57:30,516:INFO:Uploading model into container now 2024-11-25 13:57:30,516:INFO:_master_model_container: 20 2024-11-25 13:57:30,516:INFO:_display_container: 2 2024-11-25 13:57:30,517:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=KNeighborsRegressor(n_jobs=-1), sp=12, window_length=12) 2024-11-25 13:57:30,517:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:30,582:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:30,582:INFO:Creating metrics dataframe 2024-11-25 13:57:30,587:INFO:Initializing Decision Tree w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:30,587:INFO:Total runtime is 0.2772200703620911 minutes 2024-11-25 13:57:30,589:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:30,589:INFO:Initializing create_model() 2024-11-25 13:57:30,589:INFO:create_model(self=, estimator=dt_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:30,589:INFO:Checking exceptions 2024-11-25 13:57:30,589:INFO:Importing libraries 2024-11-25 13:57:30,589:INFO:Copying training dataset 2024-11-25 13:57:30,590:INFO:Defining folds 2024-11-25 13:57:30,590:INFO:Declaring metric variables 2024-11-25 13:57:30,591:INFO:Importing untrained model 2024-11-25 13:57:30,592:INFO:Decision Tree w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:30,595:INFO:Starting cross validation 2024-11-25 13:57:30,596:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:30,806:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,806:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,828:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,828:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,834:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,834:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,841:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,842:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:30,853:INFO:Calculating mean and std 2024-11-25 13:57:30,853:INFO:Creating metrics dataframe 2024-11-25 13:57:30,855:INFO:Uploading results into container 2024-11-25 13:57:30,855:INFO:Uploading model into container now 2024-11-25 13:57:30,855:INFO:_master_model_container: 21 2024-11-25 13:57:30,855:INFO:_display_container: 2 2024-11-25 13:57:30,856:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=DecisionTreeRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:30,856:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:30,922:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:30,922:INFO:Creating metrics dataframe 2024-11-25 13:57:30,928:INFO:Initializing Random Forest w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:30,928:INFO:Total runtime is 0.2828956842422486 minutes 2024-11-25 13:57:30,929:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:30,930:INFO:Initializing create_model() 2024-11-25 13:57:30,930:INFO:create_model(self=, estimator=rf_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:30,930:INFO:Checking exceptions 2024-11-25 13:57:30,930:INFO:Importing libraries 2024-11-25 13:57:30,930:INFO:Copying training dataset 2024-11-25 13:57:30,931:INFO:Defining folds 2024-11-25 13:57:30,931:INFO:Declaring metric variables 2024-11-25 13:57:30,932:INFO:Importing untrained model 2024-11-25 13:57:30,933:INFO:Random Forest w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:30,936:INFO:Starting cross validation 2024-11-25 13:57:30,936:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:31,562:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,562:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,567:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,568:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,573:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,574:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,575:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,575:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:31,591:INFO:Calculating mean and std 2024-11-25 13:57:31,591:INFO:Creating metrics dataframe 2024-11-25 13:57:31,593:INFO:Uploading results into container 2024-11-25 13:57:31,593:INFO:Uploading model into container now 2024-11-25 13:57:31,593:INFO:_master_model_container: 22 2024-11-25 13:57:31,593:INFO:_display_container: 2 2024-11-25 13:57:31,594:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=RandomForestRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 13:57:31,594:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:31,659:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:31,659:INFO:Creating metrics dataframe 2024-11-25 13:57:31,665:INFO:Initializing Extra Trees w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:31,665:INFO:Total runtime is 0.2951762517293295 minutes 2024-11-25 13:57:31,666:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:31,666:INFO:Initializing create_model() 2024-11-25 13:57:31,666:INFO:create_model(self=, estimator=et_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:31,666:INFO:Checking exceptions 2024-11-25 13:57:31,666:INFO:Importing libraries 2024-11-25 13:57:31,666:INFO:Copying training dataset 2024-11-25 13:57:31,667:INFO:Defining folds 2024-11-25 13:57:31,667:INFO:Declaring metric variables 2024-11-25 13:57:31,669:INFO:Importing untrained model 2024-11-25 13:57:31,670:INFO:Extra Trees w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:31,673:INFO:Starting cross validation 2024-11-25 13:57:31,674:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:32,290:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,290:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,290:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,291:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,296:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,296:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,309:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,309:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,345:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,345:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,351:INFO:Calculating mean and std 2024-11-25 13:57:32,351:INFO:Creating metrics dataframe 2024-11-25 13:57:32,352:INFO:Uploading results into container 2024-11-25 13:57:32,353:INFO:Uploading model into container now 2024-11-25 13:57:32,353:INFO:_master_model_container: 23 2024-11-25 13:57:32,353:INFO:_display_container: 2 2024-11-25 13:57:32,354:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=ExtraTreesRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 13:57:32,354:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:32,426:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:32,426:INFO:Creating metrics dataframe 2024-11-25 13:57:32,433:INFO:Initializing Gradient Boosting w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:32,433:INFO:Total runtime is 0.30797541936238615 minutes 2024-11-25 13:57:32,434:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:32,434:INFO:Initializing create_model() 2024-11-25 13:57:32,434:INFO:create_model(self=, estimator=gbr_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:32,434:INFO:Checking exceptions 2024-11-25 13:57:32,434:INFO:Importing libraries 2024-11-25 13:57:32,434:INFO:Copying training dataset 2024-11-25 13:57:32,435:INFO:Defining folds 2024-11-25 13:57:32,435:INFO:Declaring metric variables 2024-11-25 13:57:32,436:INFO:Importing untrained model 2024-11-25 13:57:32,438:INFO:Gradient Boosting w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:32,441:INFO:Starting cross validation 2024-11-25 13:57:32,442:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:32,839:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,839:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,888:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,888:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,895:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,895:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,901:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,901:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,901:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,901:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:32,916:INFO:Calculating mean and std 2024-11-25 13:57:32,917:INFO:Creating metrics dataframe 2024-11-25 13:57:32,920:INFO:Uploading results into container 2024-11-25 13:57:32,920:INFO:Uploading model into container now 2024-11-25 13:57:32,921:INFO:_master_model_container: 24 2024-11-25 13:57:32,921:INFO:_display_container: 2 2024-11-25 13:57:32,922:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=GradientBoostingRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:32,922:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:33,006:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:33,006:INFO:Creating metrics dataframe 2024-11-25 13:57:33,012:INFO:Initializing AdaBoost w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:33,012:INFO:Total runtime is 0.3176307837168377 minutes 2024-11-25 13:57:33,013:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:33,013:INFO:Initializing create_model() 2024-11-25 13:57:33,014:INFO:create_model(self=, estimator=ada_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:33,014:INFO:Checking exceptions 2024-11-25 13:57:33,014:INFO:Importing libraries 2024-11-25 13:57:33,014:INFO:Copying training dataset 2024-11-25 13:57:33,015:INFO:Defining folds 2024-11-25 13:57:33,015:INFO:Declaring metric variables 2024-11-25 13:57:33,016:INFO:Importing untrained model 2024-11-25 13:57:33,017:INFO:AdaBoost w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:33,021:INFO:Starting cross validation 2024-11-25 13:57:33,022:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:33,365:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,365:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,374:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,374:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,390:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,390:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,392:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,393:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,403:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,403:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,413:INFO:Calculating mean and std 2024-11-25 13:57:33,413:INFO:Creating metrics dataframe 2024-11-25 13:57:33,415:INFO:Uploading results into container 2024-11-25 13:57:33,415:INFO:Uploading model into container now 2024-11-25 13:57:33,415:INFO:_master_model_container: 25 2024-11-25 13:57:33,415:INFO:_display_container: 2 2024-11-25 13:57:33,416:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=AdaBoostRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 13:57:33,416:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:33,483:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:33,483:INFO:Creating metrics dataframe 2024-11-25 13:57:33,489:INFO:Initializing Light Gradient Boosting w/ Cond. Deseasonalize & Detrending 2024-11-25 13:57:33,489:INFO:Total runtime is 0.3255805532137554 minutes 2024-11-25 13:57:33,490:INFO:SubProcess create_model() called ================================== 2024-11-25 13:57:33,491:INFO:Initializing create_model() 2024-11-25 13:57:33,491:INFO:create_model(self=, estimator=lightgbm_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:33,491:INFO:Checking exceptions 2024-11-25 13:57:33,491:INFO:Importing libraries 2024-11-25 13:57:33,491:INFO:Copying training dataset 2024-11-25 13:57:33,491:INFO:Defining folds 2024-11-25 13:57:33,491:INFO:Declaring metric variables 2024-11-25 13:57:33,493:INFO:Importing untrained model 2024-11-25 13:57:33,494:INFO:Light Gradient Boosting w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 13:57:33,497:INFO:Starting cross validation 2024-11-25 13:57:33,497:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 13:57:33,644:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,666:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,671:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,674:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,683:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,684:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,685:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,691:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,694:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,694:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,699:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,702:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,705:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,707:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,709:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,710:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,712:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,716:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,718:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,721:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,722:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,724:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,727:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,731:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,731:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,735:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,737:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,739:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,739:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,743:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,748:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,749:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,749:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,752:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,757:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,757:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,761:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,763:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,765:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,766:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,769:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,773:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,775:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,776:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,777:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,781:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,785:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,789:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,793:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,794:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,797:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,801:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,801:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,802:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,805:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,809:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,810:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,814:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,814:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,817:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,819:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,823:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,824:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,825:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,827:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,832:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,833:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,835:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,837:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,840:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,842:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,848:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,852:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,853:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,858:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,861:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,864:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,866:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,866:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,868:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,873:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,876:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,881:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,881:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,883:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,888:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,890:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,896:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,897:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,903:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,904:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,910:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,912:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,917:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,919:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,922:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,922:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,924:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,931:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,938:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:33,941:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:33,941:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:34,717:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 13:57:34,847:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,854:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,860:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,867:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,873:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,880:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,886:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,893:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,899:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,905:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,912:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,918:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,924:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,930:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,936:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,942:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,949:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,955:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,961:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,967:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,974:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,980:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,986:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,992:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 13:57:34,997:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:34,997:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 13:57:35,008:INFO:Calculating mean and std 2024-11-25 13:57:35,008:INFO:Creating metrics dataframe 2024-11-25 13:57:35,010:INFO:Uploading results into container 2024-11-25 13:57:35,010:INFO:Uploading model into container now 2024-11-25 13:57:35,010:INFO:_master_model_container: 26 2024-11-25 13:57:35,010:INFO:_display_container: 2 2024-11-25 13:57:35,012:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LGBMRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 13:57:35,012:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:35,081:INFO:SubProcess create_model() end ================================== 2024-11-25 13:57:35,081:INFO:Creating metrics dataframe 2024-11-25 13:57:35,087:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/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)"]) 2024-11-25 13:57:35,090:INFO:Initializing create_model() 2024-11-25 13:57:35,090:INFO:create_model(self=, estimator=NaiveForecaster(), fold=None, 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={}) 2024-11-25 13:57:35,090:INFO:Checking exceptions 2024-11-25 13:57:35,091:INFO:Importing libraries 2024-11-25 13:57:35,091:INFO:Copying training dataset 2024-11-25 13:57:35,092:INFO:Defining folds 2024-11-25 13:57:35,092:INFO:Declaring metric variables 2024-11-25 13:57:35,092:INFO:Importing untrained model 2024-11-25 13:57:35,092:INFO:Declaring custom model 2024-11-25 13:57:35,093:INFO:Naive Forecaster Imported successfully 2024-11-25 13:57:35,093:INFO:Cross validation set to False 2024-11-25 13:57:35,093:INFO:Fitting Model 2024-11-25 13:57:35,096:INFO:NaiveForecaster() 2024-11-25 13:57:35,096:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:35,177:INFO:_master_model_container: 26 2024-11-25 13:57:35,177:INFO:_display_container: 2 2024-11-25 13:57:35,178:INFO:NaiveForecaster() 2024-11-25 13:57:35,178:INFO:compare_models() successfully completed...................................... 2024-11-25 13:57:35,178:INFO:Initializing finalize_model() 2024-11-25 13:57:35,178:INFO:finalize_model(self=, estimator=NaiveForecaster(), fit_kwargs=None, groups=None, model_only=False, experiment_custom_tags=None) 2024-11-25 13:57:35,178:INFO:Finalizing NaiveForecaster() 2024-11-25 13:57:35,179:INFO:Initializing create_model() 2024-11-25 13:57:35,179:INFO:create_model(self=, estimator=NaiveForecaster(), fold=None, 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=False, metrics=None, display=None, model_only=False, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 13:57:35,179:INFO:Checking exceptions 2024-11-25 13:57:35,179:INFO:Importing libraries 2024-11-25 13:57:35,179:INFO:Copying training dataset 2024-11-25 13:57:35,180:INFO:Defining folds 2024-11-25 13:57:35,180:INFO:Declaring metric variables 2024-11-25 13:57:35,180:INFO:Importing untrained model 2024-11-25 13:57:35,181:INFO:Declaring custom model 2024-11-25 13:57:35,181:INFO:Naive Forecaster Imported successfully 2024-11-25 13:57:35,181:INFO:Cross validation set to False 2024-11-25 13:57:35,181:INFO:Fitting Model 2024-11-25 13:57:35,188:INFO:ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', NaiveForecaster())]))]) 2024-11-25 13:57:35,188:INFO:create_model() successfully completed...................................... 2024-11-25 13:57:35,285:INFO:_master_model_container: 26 2024-11-25 13:57:35,286:INFO:_display_container: 2 2024-11-25 13:57:35,286:INFO:ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', NaiveForecaster())]))]) 2024-11-25 13:57:35,286:INFO:finalize_model() successfully completed...................................... 2024-11-25 13:57:35,357:WARNING:predict_model >> Prediction Indices do not match test indices. Metrics will not be displayed. 2024-11-25 14:01:43,673:INFO:PyCaret TSForecastingExperiment 2024-11-25 14:01:43,673:INFO:Logging name: ts-default-name 2024-11-25 14:01:43,673:INFO:ML Usecase: MLUsecase.TIME_SERIES 2024-11-25 14:01:43,673:INFO:version 3.3.2 2024-11-25 14:01:43,673:INFO:Initializing setup() 2024-11-25 14:01:43,673:INFO:self.USI: a6f0 2024-11-25 14:01:43,673:INFO:self._variable_keys: {'exogenous_present', 'fh', 'memory', 'model_engines', '_ml_usecase', 'pipeline', 'index_type', 'exp_name_log', 'data', 'primary_sp_to_use', 'enforce_pi', 'significant_sps', 'candidate_sps', 'X_test', 'log_plots_param', 'gpu_param', 'y_test', 'enforce_exogenous', 'html_param', 'X_test_transformed', 'n_jobs_param', 'y_train', 'X', 'X_train', 'fold_generator', 'X_train_transformed', 'idx', 'y_train_transformed', 'y', 'fold_param', 'seasonality_present', 'gpu_n_jobs_param', 'approach_type', 'X_transformed', 'significant_sps_no_harmonics', 'exp_id', 'logging_param', 'y_test_transformed', 'USI', 'strictly_positive', 'y_transformed', 'seed', 'all_sps_to_use', '_available_plots'} 2024-11-25 14:01:43,673:INFO:Checking environment 2024-11-25 14:01:43,673:INFO:python_version: 3.11.6 2024-11-25 14:01:43,673:INFO:python_build: ('v3.11.6:8b6ee5ba3b', 'Oct 2 2023 11:18:21') 2024-11-25 14:01:43,673:INFO:machine: arm64 2024-11-25 14:01:43,673:INFO:platform: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:01:43,673:INFO:Memory: svmem(total=17179869184, available=5403525120, percent=68.5, used=7415808000, free=35979264, active=5407916032, inactive=5366398976, wired=2007891968) 2024-11-25 14:01:43,673:INFO:Physical Core: 8 2024-11-25 14:01:43,673:INFO:Logical Core: 8 2024-11-25 14:01:43,673:INFO:Checking libraries 2024-11-25 14:01:43,673:INFO:System: 2024-11-25 14:01:43,674:INFO: python: 3.11.6 (v3.11.6:8b6ee5ba3b, Oct 2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] 2024-11-25 14:01:43,674:INFO:executable: /usr/local/bin/python3 2024-11-25 14:01:43,674:INFO: machine: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:01:43,674:INFO:PyCaret required dependencies: 2024-11-25 14:01:43,674:INFO: pip: 24.3.1 2024-11-25 14:01:43,674:INFO: setuptools: 75.5.0 2024-11-25 14:01:43,674:INFO: pycaret: 3.3.2 2024-11-25 14:01:43,674:INFO: IPython: 8.29.0 2024-11-25 14:01:43,674:INFO: ipywidgets: 8.1.5 2024-11-25 14:01:43,674:INFO: tqdm: 4.67.0 2024-11-25 14:01:43,674:INFO: numpy: 1.26.4 2024-11-25 14:01:43,674:INFO: pandas: 2.1.4 2024-11-25 14:01:43,674:INFO: jinja2: 3.1.4 2024-11-25 14:01:43,674:INFO: scipy: 1.11.4 2024-11-25 14:01:43,674:INFO: joblib: 1.3.2 2024-11-25 14:01:43,674:INFO: sklearn: 1.4.2 2024-11-25 14:01:43,674:INFO: pyod: 2.0.2 2024-11-25 14:01:43,674:INFO: imblearn: 0.12.4 2024-11-25 14:01:43,674:INFO: category_encoders: 2.6.4 2024-11-25 14:01:43,674:INFO: lightgbm: 4.5.0 2024-11-25 14:01:43,674:INFO: numba: 0.60.0 2024-11-25 14:01:43,674:INFO: requests: 2.32.3 2024-11-25 14:01:43,674:INFO: matplotlib: 3.7.5 2024-11-25 14:01:43,674:INFO: scikitplot: 0.3.7 2024-11-25 14:01:43,674:INFO: yellowbrick: 1.5 2024-11-25 14:01:43,674:INFO: plotly: 5.24.1 2024-11-25 14:01:43,674:INFO: plotly-resampler: Not installed 2024-11-25 14:01:43,674:INFO: kaleido: 0.2.1 2024-11-25 14:01:43,674:INFO: schemdraw: 0.15 2024-11-25 14:01:43,674:INFO: statsmodels: 0.14.4 2024-11-25 14:01:43,674:INFO: sktime: 0.26.0 2024-11-25 14:01:43,674:INFO: tbats: 1.1.3 2024-11-25 14:01:43,674:INFO: pmdarima: 2.0.4 2024-11-25 14:01:43,674:INFO: psutil: 6.1.0 2024-11-25 14:01:43,674:INFO: markupsafe: 2.1.5 2024-11-25 14:01:43,674:INFO: pickle5: Not installed 2024-11-25 14:01:43,674:INFO: cloudpickle: 3.1.0 2024-11-25 14:01:43,674:INFO: deprecation: 2.1.0 2024-11-25 14:01:43,674:INFO: xxhash: 3.5.0 2024-11-25 14:01:43,674:INFO: wurlitzer: 3.1.1 2024-11-25 14:01:43,674:INFO:PyCaret optional dependencies: 2024-11-25 14:01:43,674:INFO: shap: Not installed 2024-11-25 14:01:43,674:INFO: interpret: Not installed 2024-11-25 14:01:43,674:INFO: umap: 0.5.7 2024-11-25 14:01:43,674:INFO: ydata_profiling: Not installed 2024-11-25 14:01:43,674:INFO: explainerdashboard: Not installed 2024-11-25 14:01:43,674:INFO: autoviz: Not installed 2024-11-25 14:01:43,674:INFO: fairlearn: Not installed 2024-11-25 14:01:43,674:INFO: deepchecks: Not installed 2024-11-25 14:01:43,674:INFO: xgboost: Not installed 2024-11-25 14:01:43,674:INFO: catboost: Not installed 2024-11-25 14:01:43,674:INFO: kmodes: Not installed 2024-11-25 14:01:43,674:INFO: mlxtend: Not installed 2024-11-25 14:01:43,674:INFO: statsforecast: Not installed 2024-11-25 14:01:43,674:INFO: tune_sklearn: Not installed 2024-11-25 14:01:43,675:INFO: ray: Not installed 2024-11-25 14:01:43,675:INFO: hyperopt: Not installed 2024-11-25 14:01:43,675:INFO: optuna: 4.1.0 2024-11-25 14:01:43,675:INFO: skopt: Not installed 2024-11-25 14:01:43,675:INFO: mlflow: Not installed 2024-11-25 14:01:43,675:INFO: gradio: 5.6.0 2024-11-25 14:01:43,675:INFO: fastapi: 0.115.5 2024-11-25 14:01:43,675:INFO: uvicorn: 0.32.0 2024-11-25 14:01:43,675:INFO: m2cgen: Not installed 2024-11-25 14:01:43,675:INFO: evidently: Not installed 2024-11-25 14:01:43,675:INFO: fugue: Not installed 2024-11-25 14:01:43,675:INFO: streamlit: Not installed 2024-11-25 14:01:43,675:INFO: prophet: 1.1.6 2024-11-25 14:01:43,675:INFO:None 2024-11-25 14:01:43,677:INFO:Set Forecast Horizon. 2024-11-25 14:01:43,677:INFO:Set up Train-Test Splits. 2024-11-25 14:01:43,691:INFO:Finished creating preprocessing pipeline. 2024-11-25 14:01:43,691:INFO:Pipeline: ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', DummyForecaster())]))]) 2024-11-25 14:01:43,691:INFO:Set up Seasonal Period. 2024-11-25 14:01:43,692:INFO:Setting the seasonal component type - 'add' or 'mul'. 2024-11-25 14:01:43,692:INFO:Checking if data is strictly positive. 2024-11-25 14:01:43,705:INFO:Creating final display dataframe. 2024-11-25 14:01:43,712:INFO:Setup Display Container: Description Value 0 session_id 42 1 Target target 2 Approach Univariate 3 Exogenous Variables Not Present 4 Original data shape (206, 1) 5 Transformed data shape (206, 1) 6 Transformed train set shape (182, 1) 7 Transformed test set shape (24, 1) 8 Rows with missing values 0.0% 9 Fold Generator ExpandingWindowSplitter 10 Fold Number 5 11 Enforce Prediction Interval False 12 Splits used for hyperparameters all 13 User Defined Seasonal Period(s) 12 14 Ignore Seasonality Test False 15 Seasonality Detection Algo user_defined 16 Max Period to Consider 60 17 Seasonal Period(s) Tested [12] 18 Significant Seasonal Period(s) [12] 19 Significant Seasonal Period(s) without Harmonics [12] 20 Remove Harmonics False 21 Harmonics Order Method harmonic_max 22 Num Seasonalities to Use 1 23 All Seasonalities to Use [12] 24 Primary Seasonality 12 25 Seasonality Present True 26 Seasonality Type mul 27 Target Strictly Positive True 28 Target White Noise No 29 Recommended d 1 30 Recommended Seasonal D 0 31 Preprocess False 32 CPU Jobs -1 33 Use GPU False 34 Log Experiment False 35 Experiment Name ts-default-name 36 USI a6f0 2024-11-25 14:01:43,720:INFO:Engine successfully changes for model 'auto_arima' to 'pmdarima'. 2024-11-25 14:01:43,723:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,723:INFO:Engine for model 'lr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,724:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,724:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,724:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,725:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,725:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,725:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,726:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,728:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,729:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,729:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,729:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,730:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,730:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,730:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,730: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]` 2024-11-25 14:01:43,730: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]` 2024-11-25 14:01:43,730:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,731:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,731:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,731:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,732:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,733:INFO:Engine for model 'lr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,733:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,734:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,734:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,734:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,734:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,734:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735: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]` 2024-11-25 14:01:43,735: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]` 2024-11-25 14:01:43,735:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,735:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,735:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,735:INFO:Engine successfully changes for model 'lr_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,736:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,737:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,737:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,738:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,738:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,738:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,739:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,740:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,740:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,741:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,741:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,741:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,742:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,742:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,742:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,742: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]` 2024-11-25 14:01:43,742: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]` 2024-11-25 14:01:43,742:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,743:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,743:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,743:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,747:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,747:INFO:Engine for model 'en_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,748:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,748:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,748:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,748:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,749:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,750:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,751:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,751:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,751:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,752:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,752:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,752:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,752:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,752: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]` 2024-11-25 14:01:43,753: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]` 2024-11-25 14:01:43,753:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,753:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,753:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,753:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,753:INFO:Engine successfully changes for model 'en_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,756:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,756:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,757:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,757:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,757:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,758:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,759:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,760:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,760:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,760:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761: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]` 2024-11-25 14:01:43,761: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]` 2024-11-25 14:01:43,761:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,761:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,761:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,765:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,766:INFO:Engine for model 'ridge_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,766:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,767:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,767:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,767:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,768:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,769:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,769:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,770: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]` 2024-11-25 14:01:43,770: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]` 2024-11-25 14:01:43,770:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,771:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,771:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,771:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,771:INFO:Engine successfully changes for model 'ridge_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,772:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,772:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,772:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,772:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,772:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,773:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,773:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,773:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,773:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774: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]` 2024-11-25 14:01:43,774: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]` 2024-11-25 14:01:43,774:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,774:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,774:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,775:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,776:INFO:Engine for model 'lasso_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,776:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,776:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,776:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,776:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,777: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]` 2024-11-25 14:01:43,777: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]` 2024-11-25 14:01:43,777:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,778:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,778:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,778:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,778:INFO:Engine successfully changes for model 'lasso_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,779:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,779:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,779:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,779:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,780:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,781:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,781:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,781:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,782:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,782:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,782:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,782:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,782: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]` 2024-11-25 14:01:43,783: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]` 2024-11-25 14:01:43,783:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,783:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,783:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,783:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,786:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,787:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,787:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,787:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,788:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,789:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,790: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]` 2024-11-25 14:01:43,790: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]` 2024-11-25 14:01:43,791:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,791:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,791:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,791:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,791:INFO:Engine successfully changes for model 'lar_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,792:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,792:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,792:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,792:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,793:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,793:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,793:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794: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]` 2024-11-25 14:01:43,794: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]` 2024-11-25 14:01:43,794:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,794:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,794:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,795:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,796:INFO:Engine for model 'llar_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,796:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,796:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,796:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,797: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]` 2024-11-25 14:01:43,797: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]` 2024-11-25 14:01:43,797:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,798:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,798:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,798:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,798:INFO:Engine successfully changes for model 'llar_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,799:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,799:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,799:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,800:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,800:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,800:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,800:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,801:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,801:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,801:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,801:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,801: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]` 2024-11-25 14:01:43,802: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]` 2024-11-25 14:01:43,802:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,802:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,802:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,802:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,808:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,808:INFO:Engine for model 'br_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,808:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,809:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,810:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,810:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,810: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]` 2024-11-25 14:01:43,810: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]` 2024-11-25 14:01:43,810:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,810:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,810:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,810:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,810:INFO:Engine successfully changes for model 'br_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,811:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,812:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,812:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,812:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,812:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813: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]` 2024-11-25 14:01:43,813: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]` 2024-11-25 14:01:43,813:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,813:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,813:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,814:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,815:INFO:Engine for model 'huber_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,815:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,816: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]` 2024-11-25 14:01:43,816: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]` 2024-11-25 14:01:43,816:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,817:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,817:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,817:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,817:INFO:Engine successfully changes for model 'huber_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,818:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,818:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,819: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]` 2024-11-25 14:01:43,819: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]` 2024-11-25 14:01:43,819:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,820:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,820:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,820:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,821:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,822:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,822:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,823:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,823: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]` 2024-11-25 14:01:43,823: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]` 2024-11-25 14:01:43,823:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,823:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,823:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,823:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,823:INFO:Engine successfully changes for model 'par_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,824:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,825:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,825:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,825:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,825:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,825:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,825:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,826:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,826:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,826: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]` 2024-11-25 14:01:43,826: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]` 2024-11-25 14:01:43,826:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,826:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,826:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,826:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,827:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,828:INFO:Engine for model 'omp_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,829: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]` 2024-11-25 14:01:43,829: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]` 2024-11-25 14:01:43,829:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,830:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,830:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,830:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,830:INFO:Engine successfully changes for model 'omp_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,831:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,832:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,832:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,832:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,832:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,832:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,833:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,833:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,833: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]` 2024-11-25 14:01:43,833: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]` 2024-11-25 14:01:43,833:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,833:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,833:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,833:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,834:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,835:INFO:Engine for model 'knn_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,835:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,835:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,835:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836: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]` 2024-11-25 14:01:43,836: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]` 2024-11-25 14:01:43,836:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,836:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,836:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,836:INFO:Engine successfully changes for model 'knn_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,837:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,838:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,838:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,838:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839: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]` 2024-11-25 14:01:43,839: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]` 2024-11-25 14:01:43,839:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,839:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,839:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,840:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,841:INFO:Engine for model 'dt_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,841:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842: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]` 2024-11-25 14:01:43,842: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]` 2024-11-25 14:01:43,842:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,842:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,842:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,842:INFO:Engine successfully changes for model 'dt_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,843:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,844:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845: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]` 2024-11-25 14:01:43,845: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]` 2024-11-25 14:01:43,845:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,845:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,845:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,846:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,848:INFO:Engine for model 'rf_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848: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]` 2024-11-25 14:01:43,848: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]` 2024-11-25 14:01:43,848:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,848:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,848:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,848:INFO:Engine successfully changes for model 'rf_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,849:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,851:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851: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]` 2024-11-25 14:01:43,851: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]` 2024-11-25 14:01:43,851:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,851:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,851:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,852:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,854:INFO:Engine for model 'et_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854: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]` 2024-11-25 14:01:43,854: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]` 2024-11-25 14:01:43,854:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,854:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,854:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,854:INFO:Engine successfully changes for model 'et_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,855:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,857:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,857:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,857:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,857: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]` 2024-11-25 14:01:43,857: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]` 2024-11-25 14:01:43,857:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,857:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,857:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,857:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,858:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,860:INFO:Engine for model 'gbr_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,860:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,860:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,860: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]` 2024-11-25 14:01:43,860: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]` 2024-11-25 14:01:43,860:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,860:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,860:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,860:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,860:INFO:Engine successfully changes for model 'gbr_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,862:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,863:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,863:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,863: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]` 2024-11-25 14:01:43,863: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]` 2024-11-25 14:01:43,863:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,864:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,864:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,864:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,866:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,872:INFO:Engine for model 'ada_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,873:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,873: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]` 2024-11-25 14:01:43,873: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]` 2024-11-25 14:01:43,873:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,874:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,874:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,874:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,874:INFO:Engine successfully changes for model 'ada_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,875:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,877:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,878: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]` 2024-11-25 14:01:43,878: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]` 2024-11-25 14:01:43,878:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,878:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,878:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,878:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,879:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,881:INFO:Engine for model 'xgboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,881: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]` 2024-11-25 14:01:43,881: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]` 2024-11-25 14:01:43,881:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,881:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,881:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,881:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,881:INFO:Engine successfully changes for model 'xgboost_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,882:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,884: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]` 2024-11-25 14:01:43,884: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]` 2024-11-25 14:01:43,884:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,884:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,884:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,884:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,885:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,887: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]` 2024-11-25 14:01:43,887: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]` 2024-11-25 14:01:43,887:INFO:Engine for model 'lightgbm_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,887:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,887:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,887:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,887:INFO:Engine successfully changes for model 'lightgbm_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,888:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,890: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]` 2024-11-25 14:01:43,890: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]` 2024-11-25 14:01:43,890:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,891:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,891:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,893:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,898: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]` 2024-11-25 14:01:43,898: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]` 2024-11-25 14:01:43,898:INFO:Engine for model 'catboost_cds_dt' has not been set explicitly, hence returning None. 2024-11-25 14:01:43,898:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,898:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,899:INFO:Engine successfully changes for model 'catboost_cds_dt' to 'sklearn'. 2024-11-25 14:01:43,901:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,903: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]` 2024-11-25 14:01:43,903: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]` 2024-11-25 14:01:43,903:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,903:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,904:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,906: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]` 2024-11-25 14:01:43,906: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]` 2024-11-25 14:01:43,906:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,906:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,907:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,911: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]` 2024-11-25 14:01:43,911: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]` 2024-11-25 14:01:43,911:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,911:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,912:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:43,914: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]` 2024-11-25 14:01:43,914: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]` 2024-11-25 14:01:43,914:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,914:WARNING: 'catboost' is a soft dependency and not included in the pycaret installation. Please run: `pip install catboost` to install. Alternately, you can install this by running `pip install pycaret[models]` 2024-11-25 14:01:43,915:INFO:setup() successfully completed in 0.24s............... 2024-11-25 14:01:43,915:INFO:Initializing compare_models() 2024-11-25 14:01:43,915:INFO:compare_models(self=, include=None, exclude=None, fold=None, round=4, cross_validation=True, sort=MASE, 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': , 'include': None, 'exclude': None, 'fold': None, 'round': 4, 'cross_validation': True, 'sort': 'MASE', 'n_select': 1, 'budget_time': None, 'turbo': True, 'errors': 'ignore', 'fit_kwargs': None, 'experiment_custom_tags': None, 'engine': None, 'verbose': True, 'parallel': None, '__class__': }) 2024-11-25 14:01:43,916:INFO:Checking exceptions 2024-11-25 14:01:43,916:INFO:Preparing display monitor 2024-11-25 14:01:43,946:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/internal/pycaret_experiment/supervised_experiment.py:713: UserWarning: Unsupported estimator `ensemble_forecaster` for method `compare_models()`, removing from model_library warnings.warn( 2024-11-25 14:01:43,946:INFO:Initializing Naive Forecaster 2024-11-25 14:01:43,946:INFO:Total runtime is 5.841255187988282e-07 minutes 2024-11-25 14:01:43,947:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:43,948:INFO:Initializing create_model() 2024-11-25 14:01:43,948:INFO:create_model(self=, estimator=naive, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:43,948:INFO:Checking exceptions 2024-11-25 14:01:43,948:INFO:Importing libraries 2024-11-25 14:01:43,948:INFO:Copying training dataset 2024-11-25 14:01:43,950:INFO:Defining folds 2024-11-25 14:01:43,950:INFO:Declaring metric variables 2024-11-25 14:01:43,958:INFO:Importing untrained model 2024-11-25 14:01:43,963:INFO:Naive Forecaster Imported successfully 2024-11-25 14:01:43,969:INFO:Starting cross validation 2024-11-25 14:01:43,979:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:44,018:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,018:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,020:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,020:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,024:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,024:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,027:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,028:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,029:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,030:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,039:INFO:Calculating mean and std 2024-11-25 14:01:44,039:INFO:Creating metrics dataframe 2024-11-25 14:01:44,041:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:44,041:INFO:Uploading results into container 2024-11-25 14:01:44,041:INFO:Uploading model into container now 2024-11-25 14:01:44,042:INFO:_master_model_container: 1 2024-11-25 14:01:44,042:INFO:_display_container: 2 2024-11-25 14:01:44,042:INFO:NaiveForecaster() 2024-11-25 14:01:44,042:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:44,113:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:44,113:INFO:Creating metrics dataframe 2024-11-25 14:01:44,116:INFO:Initializing Grand Means Forecaster 2024-11-25 14:01:44,116:INFO:Total runtime is 0.002834169069925944 minutes 2024-11-25 14:01:44,117:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:44,117:INFO:Initializing create_model() 2024-11-25 14:01:44,117:INFO:create_model(self=, estimator=grand_means, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:44,117:INFO:Checking exceptions 2024-11-25 14:01:44,117:INFO:Importing libraries 2024-11-25 14:01:44,117:INFO:Copying training dataset 2024-11-25 14:01:44,118:INFO:Defining folds 2024-11-25 14:01:44,118:INFO:Declaring metric variables 2024-11-25 14:01:44,119:INFO:Importing untrained model 2024-11-25 14:01:44,120:INFO:Grand Means Forecaster Imported successfully 2024-11-25 14:01:44,124:INFO:Starting cross validation 2024-11-25 14:01:44,124:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:44,141:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,141:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,146:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,146:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,149:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,149:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,150:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,150:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,153:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,153:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,167:INFO:Calculating mean and std 2024-11-25 14:01:44,167:INFO:Creating metrics dataframe 2024-11-25 14:01:44,168:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:44,168:INFO:Uploading results into container 2024-11-25 14:01:44,169:INFO:Uploading model into container now 2024-11-25 14:01:44,169:INFO:_master_model_container: 2 2024-11-25 14:01:44,169:INFO:_display_container: 2 2024-11-25 14:01:44,169:INFO:NaiveForecaster(strategy='mean') 2024-11-25 14:01:44,169:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:44,241:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:44,241:INFO:Creating metrics dataframe 2024-11-25 14:01:44,245:INFO:Initializing Seasonal Naive Forecaster 2024-11-25 14:01:44,245:INFO:Total runtime is 0.004981815814971924 minutes 2024-11-25 14:01:44,247:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:44,247:INFO:Initializing create_model() 2024-11-25 14:01:44,247:INFO:create_model(self=, estimator=snaive, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:44,247:INFO:Checking exceptions 2024-11-25 14:01:44,247:INFO:Importing libraries 2024-11-25 14:01:44,247:INFO:Copying training dataset 2024-11-25 14:01:44,248:INFO:Defining folds 2024-11-25 14:01:44,248:INFO:Declaring metric variables 2024-11-25 14:01:44,249:INFO:Importing untrained model 2024-11-25 14:01:44,250:INFO:Seasonal Naive Forecaster Imported successfully 2024-11-25 14:01:44,253:INFO:Starting cross validation 2024-11-25 14:01:44,254:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:44,287:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,287:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,291:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,291:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,298:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,299:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,304:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,305:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,311:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,311:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,324:INFO:Calculating mean and std 2024-11-25 14:01:44,324:INFO:Creating metrics dataframe 2024-11-25 14:01:44,325:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:44,325:INFO:Uploading results into container 2024-11-25 14:01:44,325:INFO:Uploading model into container now 2024-11-25 14:01:44,325:INFO:_master_model_container: 3 2024-11-25 14:01:44,325:INFO:_display_container: 2 2024-11-25 14:01:44,326:INFO:NaiveForecaster(sp=12) 2024-11-25 14:01:44,326:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:44,396:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:44,396:INFO:Creating metrics dataframe 2024-11-25 14:01:44,399:INFO:Initializing Polynomial Trend Forecaster 2024-11-25 14:01:44,399:INFO:Total runtime is 0.00756001869837443 minutes 2024-11-25 14:01:44,401:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:44,401:INFO:Initializing create_model() 2024-11-25 14:01:44,401:INFO:create_model(self=, estimator=polytrend, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:44,401:INFO:Checking exceptions 2024-11-25 14:01:44,401:INFO:Importing libraries 2024-11-25 14:01:44,401:INFO:Copying training dataset 2024-11-25 14:01:44,402:INFO:Defining folds 2024-11-25 14:01:44,402:INFO:Declaring metric variables 2024-11-25 14:01:44,403:INFO:Importing untrained model 2024-11-25 14:01:44,404:INFO:Polynomial Trend Forecaster Imported successfully 2024-11-25 14:01:44,407:INFO:Starting cross validation 2024-11-25 14:01:44,408:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:44,421:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,421:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,421:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,421:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,429:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,429:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,429:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,430:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,430:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,430:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,439:INFO:Calculating mean and std 2024-11-25 14:01:44,439:INFO:Creating metrics dataframe 2024-11-25 14:01:44,440:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:44,440:INFO:Uploading results into container 2024-11-25 14:01:44,440:INFO:Uploading model into container now 2024-11-25 14:01:44,440:INFO:_master_model_container: 4 2024-11-25 14:01:44,440:INFO:_display_container: 2 2024-11-25 14:01:44,440:INFO:PolynomialTrendForecaster() 2024-11-25 14:01:44,440:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:44,512:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:44,513:INFO:Creating metrics dataframe 2024-11-25 14:01:44,516:INFO:Initializing ARIMA 2024-11-25 14:01:44,516:INFO:Total runtime is 0.009497765700022379 minutes 2024-11-25 14:01:44,517:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:44,517:INFO:Initializing create_model() 2024-11-25 14:01:44,517:INFO:create_model(self=, estimator=arima, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:44,517:INFO:Checking exceptions 2024-11-25 14:01:44,517:INFO:Importing libraries 2024-11-25 14:01:44,517:INFO:Copying training dataset 2024-11-25 14:01:44,518:INFO:Defining folds 2024-11-25 14:01:44,518:INFO:Declaring metric variables 2024-11-25 14:01:44,519:INFO:Importing untrained model 2024-11-25 14:01:44,520:INFO:ARIMA Imported successfully 2024-11-25 14:01:44,523:INFO:Starting cross validation 2024-11-25 14:01:44,524:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:44,574:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,574:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,582:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,588:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,588:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,600:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,600:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,622:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,622:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:44,628:INFO:Calculating mean and std 2024-11-25 14:01:44,628:INFO:Creating metrics dataframe 2024-11-25 14:01:44,629:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:44,630:INFO:Uploading results into container 2024-11-25 14:01:44,630:INFO:Uploading model into container now 2024-11-25 14:01:44,631:INFO:_master_model_container: 5 2024-11-25 14:01:44,631:INFO:_display_container: 2 2024-11-25 14:01:44,631:INFO:ARIMA(seasonal_order=(0, 1, 0, 12)) 2024-11-25 14:01:44,631:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:44,702:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:44,702:INFO:Creating metrics dataframe 2024-11-25 14:01:44,705:INFO:Initializing Auto ARIMA 2024-11-25 14:01:44,705:INFO:Total runtime is 0.012654284636179606 minutes 2024-11-25 14:01:44,706:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:44,706:INFO:Initializing create_model() 2024-11-25 14:01:44,706:INFO:create_model(self=, estimator=auto_arima, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:44,706:INFO:Checking exceptions 2024-11-25 14:01:44,706:INFO:Importing libraries 2024-11-25 14:01:44,706:INFO:Copying training dataset 2024-11-25 14:01:44,708:INFO:Defining folds 2024-11-25 14:01:44,708:INFO:Declaring metric variables 2024-11-25 14:01:44,709:INFO:Importing untrained model 2024-11-25 14:01:44,710:INFO:Auto ARIMA Imported successfully 2024-11-25 14:01:44,714:INFO:Starting cross validation 2024-11-25 14:01:44,714:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:46,519:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:46,519:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:46,579:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:46,579:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:47,495:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:47,496:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:49,203:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:49,203:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:50,969:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:50,969:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:50,977:INFO:Calculating mean and std 2024-11-25 14:01:50,977:INFO:Creating metrics dataframe 2024-11-25 14:01:50,978:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:50,979:INFO:Uploading results into container 2024-11-25 14:01:50,979:INFO:Uploading model into container now 2024-11-25 14:01:50,980:INFO:_master_model_container: 6 2024-11-25 14:01:50,980:INFO:_display_container: 2 2024-11-25 14:01:50,980:INFO:AutoARIMA(random_state=42, sp=12, suppress_warnings=True) 2024-11-25 14:01:50,980:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,054:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,054:INFO:Creating metrics dataframe 2024-11-25 14:01:51,057:INFO:Initializing Exponential Smoothing 2024-11-25 14:01:51,058:INFO:Total runtime is 0.11853036880493165 minutes 2024-11-25 14:01:51,059:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,059:INFO:Initializing create_model() 2024-11-25 14:01:51,059:INFO:create_model(self=, estimator=exp_smooth, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,059:INFO:Checking exceptions 2024-11-25 14:01:51,060:INFO:Importing libraries 2024-11-25 14:01:51,060:INFO:Copying training dataset 2024-11-25 14:01:51,061:INFO:Defining folds 2024-11-25 14:01:51,061:INFO:Declaring metric variables 2024-11-25 14:01:51,062:INFO:Importing untrained model 2024-11-25 14:01:51,063:INFO:Exponential Smoothing Imported successfully 2024-11-25 14:01:51,066:INFO:Starting cross validation 2024-11-25 14:01:51,066:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:51,259:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,259:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,266:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,267:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,278:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,278:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,287:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,288:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,288:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,289:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,293:INFO:Calculating mean and std 2024-11-25 14:01:51,294:INFO:Creating metrics dataframe 2024-11-25 14:01:51,296:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:51,298:INFO:Uploading results into container 2024-11-25 14:01:51,298:INFO:Uploading model into container now 2024-11-25 14:01:51,298:INFO:_master_model_container: 7 2024-11-25 14:01:51,298:INFO:_display_container: 2 2024-11-25 14:01:51,298:INFO:ExponentialSmoothing(seasonal='mul', sp=12, trend='add') 2024-11-25 14:01:51,298:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,382:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,382:INFO:Creating metrics dataframe 2024-11-25 14:01:51,387:INFO:Initializing ETS 2024-11-25 14:01:51,387:INFO:Total runtime is 0.12402888536453248 minutes 2024-11-25 14:01:51,389:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,389:INFO:Initializing create_model() 2024-11-25 14:01:51,389:INFO:create_model(self=, estimator=ets, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,389:INFO:Checking exceptions 2024-11-25 14:01:51,389:INFO:Importing libraries 2024-11-25 14:01:51,389:INFO:Copying training dataset 2024-11-25 14:01:51,390:INFO:Defining folds 2024-11-25 14:01:51,390:INFO:Declaring metric variables 2024-11-25 14:01:51,391:INFO:Importing untrained model 2024-11-25 14:01:51,393:INFO:ETS Imported successfully 2024-11-25 14:01:51,397:INFO:Starting cross validation 2024-11-25 14:01:51,398:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:51,453:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,453:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,460:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,460:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,466:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,466:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,470:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,470:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,479:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,479:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,491:INFO:Calculating mean and std 2024-11-25 14:01:51,491:INFO:Creating metrics dataframe 2024-11-25 14:01:51,492:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:51,492:INFO:Uploading results into container 2024-11-25 14:01:51,492:INFO:Uploading model into container now 2024-11-25 14:01:51,493:INFO:_master_model_container: 8 2024-11-25 14:01:51,493:INFO:_display_container: 2 2024-11-25 14:01:51,493:INFO:AutoETS(seasonal='mul', sp=12, trend='add') 2024-11-25 14:01:51,493:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,559:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,559:INFO:Creating metrics dataframe 2024-11-25 14:01:51,563:INFO:Initializing Theta Forecaster 2024-11-25 14:01:51,563:INFO:Total runtime is 0.12695138057072958 minutes 2024-11-25 14:01:51,564:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,564:INFO:Initializing create_model() 2024-11-25 14:01:51,564:INFO:create_model(self=, estimator=theta, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,564:INFO:Checking exceptions 2024-11-25 14:01:51,564:INFO:Importing libraries 2024-11-25 14:01:51,565:INFO:Copying training dataset 2024-11-25 14:01:51,566:INFO:Defining folds 2024-11-25 14:01:51,566:INFO:Declaring metric variables 2024-11-25 14:01:51,567:INFO:Importing untrained model 2024-11-25 14:01:51,569:INFO:Theta Forecaster Imported successfully 2024-11-25 14:01:51,571:INFO:Starting cross validation 2024-11-25 14:01:51,572:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:51,593:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,593:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,595:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,595:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,601:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,601:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,604:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,604:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,606:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,607:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,618:INFO:Calculating mean and std 2024-11-25 14:01:51,618:INFO:Creating metrics dataframe 2024-11-25 14:01:51,618:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:51,619:INFO:Uploading results into container 2024-11-25 14:01:51,619:INFO:Uploading model into container now 2024-11-25 14:01:51,619:INFO:_master_model_container: 9 2024-11-25 14:01:51,619:INFO:_display_container: 2 2024-11-25 14:01:51,619:INFO:ThetaForecaster(sp=12) 2024-11-25 14:01:51,619:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,685:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,685:INFO:Creating metrics dataframe 2024-11-25 14:01:51,689:INFO:Initializing STLF 2024-11-25 14:01:51,689:INFO:Total runtime is 0.12905483643213908 minutes 2024-11-25 14:01:51,690:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,691:INFO:Initializing create_model() 2024-11-25 14:01:51,691:INFO:create_model(self=, estimator=stlf, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,691:INFO:Checking exceptions 2024-11-25 14:01:51,691:INFO:Importing libraries 2024-11-25 14:01:51,691:INFO:Copying training dataset 2024-11-25 14:01:51,692:INFO:Defining folds 2024-11-25 14:01:51,692:INFO:Declaring metric variables 2024-11-25 14:01:51,694:INFO:Importing untrained model 2024-11-25 14:01:51,696:INFO:STLF Imported successfully 2024-11-25 14:01:51,698:INFO:Starting cross validation 2024-11-25 14:01:51,699:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:51,730:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,730:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,733:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,734:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,734:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,735:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,736:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,744:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,744:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,755:INFO:Calculating mean and std 2024-11-25 14:01:51,755:INFO:Creating metrics dataframe 2024-11-25 14:01:51,756:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:51,757:INFO:Uploading results into container 2024-11-25 14:01:51,757:INFO:Uploading model into container now 2024-11-25 14:01:51,757:INFO:_master_model_container: 10 2024-11-25 14:01:51,757:INFO:_display_container: 2 2024-11-25 14:01:51,757:INFO:STLForecaster(sp=12) 2024-11-25 14:01:51,757:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,852:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,852:INFO:Creating metrics dataframe 2024-11-25 14:01:51,856:INFO:Initializing Croston 2024-11-25 14:01:51,856:INFO:Total runtime is 0.13183693091074625 minutes 2024-11-25 14:01:51,857:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,857:INFO:Initializing create_model() 2024-11-25 14:01:51,857:INFO:create_model(self=, estimator=croston, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,858:INFO:Checking exceptions 2024-11-25 14:01:51,858:INFO:Importing libraries 2024-11-25 14:01:51,858:INFO:Copying training dataset 2024-11-25 14:01:51,859:INFO:Defining folds 2024-11-25 14:01:51,859:INFO:Declaring metric variables 2024-11-25 14:01:51,860:INFO:Importing untrained model 2024-11-25 14:01:51,862:INFO:Croston Imported successfully 2024-11-25 14:01:51,865:INFO:Starting cross validation 2024-11-25 14:01:51,866:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:51,879:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,879:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,884:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,885:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,885:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,885:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,885:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,885:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,887:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,887:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:51,897:INFO:Calculating mean and std 2024-11-25 14:01:51,897:INFO:Creating metrics dataframe 2024-11-25 14:01:51,898:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:51,899:INFO:Uploading results into container 2024-11-25 14:01:51,899:INFO:Uploading model into container now 2024-11-25 14:01:51,899:INFO:_master_model_container: 11 2024-11-25 14:01:51,899:INFO:_display_container: 2 2024-11-25 14:01:51,899:INFO:Croston() 2024-11-25 14:01:51,899:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:51,966:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:51,966:INFO:Creating metrics dataframe 2024-11-25 14:01:51,970:INFO:Initializing Linear w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:51,970:INFO:Total runtime is 0.13373719851175944 minutes 2024-11-25 14:01:51,971:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:51,971:INFO:Initializing create_model() 2024-11-25 14:01:51,971:INFO:create_model(self=, estimator=lr_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:51,971:INFO:Checking exceptions 2024-11-25 14:01:51,972:INFO:Importing libraries 2024-11-25 14:01:51,972:INFO:Copying training dataset 2024-11-25 14:01:51,973:INFO:Defining folds 2024-11-25 14:01:51,973:INFO:Declaring metric variables 2024-11-25 14:01:51,974:INFO:Importing untrained model 2024-11-25 14:01:51,975:INFO:Linear w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:51,978:INFO:Starting cross validation 2024-11-25 14:01:51,979:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:52,247:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,248:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,261:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,261:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,269:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,269:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,275:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:52,275:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,268:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:01:53,481:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,481:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,492:INFO:Calculating mean and std 2024-11-25 14:01:53,492:INFO:Creating metrics dataframe 2024-11-25 14:01:53,493:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:53,494:INFO:Uploading results into container 2024-11-25 14:01:53,495:INFO:Uploading model into container now 2024-11-25 14:01:53,495:INFO:_master_model_container: 12 2024-11-25 14:01:53,495:INFO:_display_container: 2 2024-11-25 14:01:53,496:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LinearRegression(n_jobs=-1), sp=12, window_length=12) 2024-11-25 14:01:53,497:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:53,566:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:53,566:INFO:Creating metrics dataframe 2024-11-25 14:01:53,570:INFO:Initializing Elastic Net w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:53,570:INFO:Total runtime is 0.16040323575337728 minutes 2024-11-25 14:01:53,571:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:53,571:INFO:Initializing create_model() 2024-11-25 14:01:53,571:INFO:create_model(self=, estimator=en_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:53,571:INFO:Checking exceptions 2024-11-25 14:01:53,571:INFO:Importing libraries 2024-11-25 14:01:53,571:INFO:Copying training dataset 2024-11-25 14:01:53,572:INFO:Defining folds 2024-11-25 14:01:53,572:INFO:Declaring metric variables 2024-11-25 14:01:53,573:INFO:Importing untrained model 2024-11-25 14:01:53,575:INFO:Elastic Net w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:53,578:INFO:Starting cross validation 2024-11-25 14:01:53,579:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:53,802:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,802:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,809:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,809:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,811:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,811:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,829:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,829:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,844:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,844:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:53,850:INFO:Calculating mean and std 2024-11-25 14:01:53,850:INFO:Creating metrics dataframe 2024-11-25 14:01:53,851:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:53,852:INFO:Uploading results into container 2024-11-25 14:01:53,852:INFO:Uploading model into container now 2024-11-25 14:01:53,852:INFO:_master_model_container: 13 2024-11-25 14:01:53,852:INFO:_display_container: 2 2024-11-25 14:01:53,854:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=ElasticNet(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:53,854:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:53,920:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:53,920:INFO:Creating metrics dataframe 2024-11-25 14:01:53,924:INFO:Initializing Ridge w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:53,924:INFO:Total runtime is 0.1663059671719869 minutes 2024-11-25 14:01:53,925:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:53,925:INFO:Initializing create_model() 2024-11-25 14:01:53,925:INFO:create_model(self=, estimator=ridge_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:53,925:INFO:Checking exceptions 2024-11-25 14:01:53,925:INFO:Importing libraries 2024-11-25 14:01:53,925:INFO:Copying training dataset 2024-11-25 14:01:53,927:INFO:Defining folds 2024-11-25 14:01:53,927:INFO:Declaring metric variables 2024-11-25 14:01:53,928:INFO:Importing untrained model 2024-11-25 14:01:53,930:INFO:Ridge w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:53,932:INFO:Starting cross validation 2024-11-25 14:01:53,933:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:54,165:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,165:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,167:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,168:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,177:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,177:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,180:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,180:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,186:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,186:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,194:INFO:Calculating mean and std 2024-11-25 14:01:54,195:INFO:Creating metrics dataframe 2024-11-25 14:01:54,195:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:54,196:INFO:Uploading results into container 2024-11-25 14:01:54,196:INFO:Uploading model into container now 2024-11-25 14:01:54,196:INFO:_master_model_container: 14 2024-11-25 14:01:54,196:INFO:_display_container: 2 2024-11-25 14:01:54,198:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=Ridge(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:54,198:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:54,264:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:54,264:INFO:Creating metrics dataframe 2024-11-25 14:01:54,269:INFO:Initializing Lasso w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:54,269:INFO:Total runtime is 0.1720544179280599 minutes 2024-11-25 14:01:54,270:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:54,270:INFO:Initializing create_model() 2024-11-25 14:01:54,270:INFO:create_model(self=, estimator=lasso_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:54,271:INFO:Checking exceptions 2024-11-25 14:01:54,271:INFO:Importing libraries 2024-11-25 14:01:54,271:INFO:Copying training dataset 2024-11-25 14:01:54,272:INFO:Defining folds 2024-11-25 14:01:54,272:INFO:Declaring metric variables 2024-11-25 14:01:54,273:INFO:Importing untrained model 2024-11-25 14:01:54,274:INFO:Lasso w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:54,277:INFO:Starting cross validation 2024-11-25 14:01:54,277:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:54,502:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,502:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,507:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,507:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,508:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,508:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,529:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,530:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,533:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,533:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,542:INFO:Calculating mean and std 2024-11-25 14:01:54,543:INFO:Creating metrics dataframe 2024-11-25 14:01:54,544:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:54,545:INFO:Uploading results into container 2024-11-25 14:01:54,545:INFO:Uploading model into container now 2024-11-25 14:01:54,545:INFO:_master_model_container: 15 2024-11-25 14:01:54,545:INFO:_display_container: 2 2024-11-25 14:01:54,546:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=Lasso(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:54,546:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:54,613:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:54,613:INFO:Creating metrics dataframe 2024-11-25 14:01:54,618:INFO:Initializing Lasso Least Angular Regressor w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:54,618:INFO:Total runtime is 0.17787543535232545 minutes 2024-11-25 14:01:54,620:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:54,620:INFO:Initializing create_model() 2024-11-25 14:01:54,620:INFO:create_model(self=, estimator=llar_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:54,620:INFO:Checking exceptions 2024-11-25 14:01:54,620:INFO:Importing libraries 2024-11-25 14:01:54,620:INFO:Copying training dataset 2024-11-25 14:01:54,621:INFO:Defining folds 2024-11-25 14:01:54,621:INFO:Declaring metric variables 2024-11-25 14:01:54,622:INFO:Importing untrained model 2024-11-25 14:01:54,623:INFO:Lasso Least Angular Regressor w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:54,626:INFO:Starting cross validation 2024-11-25 14:01:54,627:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:54,847:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,847:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,852:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,853:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,872:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,872:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,880:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,881:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,886:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,886:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:54,899:INFO:Calculating mean and std 2024-11-25 14:01:54,899:INFO:Creating metrics dataframe 2024-11-25 14:01:54,900:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:54,900:INFO:Uploading results into container 2024-11-25 14:01:54,900:INFO:Uploading model into container now 2024-11-25 14:01:54,901:INFO:_master_model_container: 16 2024-11-25 14:01:54,901:INFO:_display_container: 2 2024-11-25 14:01:54,901:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LassoLars(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:54,901:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:54,967:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:54,967:INFO:Creating metrics dataframe 2024-11-25 14:01:54,972:INFO:Initializing Bayesian Ridge w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:54,972:INFO:Total runtime is 0.1837718645731608 minutes 2024-11-25 14:01:54,973:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:54,973:INFO:Initializing create_model() 2024-11-25 14:01:54,973:INFO:create_model(self=, estimator=br_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:54,974:INFO:Checking exceptions 2024-11-25 14:01:54,974:INFO:Importing libraries 2024-11-25 14:01:54,974:INFO:Copying training dataset 2024-11-25 14:01:54,975:INFO:Defining folds 2024-11-25 14:01:54,975:INFO:Declaring metric variables 2024-11-25 14:01:54,976:INFO:Importing untrained model 2024-11-25 14:01:54,977:INFO:Bayesian Ridge w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:54,980:INFO:Starting cross validation 2024-11-25 14:01:54,981:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:55,228:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,228:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,232:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,232:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,238:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,238:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,240:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,240:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,243:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,243:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,257:INFO:Calculating mean and std 2024-11-25 14:01:55,257:INFO:Creating metrics dataframe 2024-11-25 14:01:55,258:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:55,259:INFO:Uploading results into container 2024-11-25 14:01:55,259:INFO:Uploading model into container now 2024-11-25 14:01:55,259:INFO:_master_model_container: 17 2024-11-25 14:01:55,259:INFO:_display_container: 2 2024-11-25 14:01:55,260:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=BayesianRidge(), sp=12, window_length=12) 2024-11-25 14:01:55,260:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:55,325:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:55,326:INFO:Creating metrics dataframe 2024-11-25 14:01:55,332:INFO:Initializing Huber w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:55,332:INFO:Total runtime is 0.18976535002390543 minutes 2024-11-25 14:01:55,333:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:55,333:INFO:Initializing create_model() 2024-11-25 14:01:55,333:INFO:create_model(self=, estimator=huber_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:55,333:INFO:Checking exceptions 2024-11-25 14:01:55,333:INFO:Importing libraries 2024-11-25 14:01:55,333:INFO:Copying training dataset 2024-11-25 14:01:55,334:INFO:Defining folds 2024-11-25 14:01:55,334:INFO:Declaring metric variables 2024-11-25 14:01:55,335:INFO:Importing untrained model 2024-11-25 14:01:55,336:INFO:Huber w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:55,339:INFO:Starting cross validation 2024-11-25 14:01:55,340:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:55,570:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,570:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,581:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,582:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,593:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,593:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,599:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,599:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,611:INFO:Calculating mean and std 2024-11-25 14:01:55,612:INFO:Creating metrics dataframe 2024-11-25 14:01:55,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:55,614:INFO:Uploading results into container 2024-11-25 14:01:55,614:INFO:Uploading model into container now 2024-11-25 14:01:55,614:INFO:_master_model_container: 18 2024-11-25 14:01:55,614:INFO:_display_container: 2 2024-11-25 14:01:55,615:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=HuberRegressor(), sp=12, window_length=12) 2024-11-25 14:01:55,615:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:55,681:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:55,681:INFO:Creating metrics dataframe 2024-11-25 14:01:55,686:INFO:Initializing Orthogonal Matching Pursuit w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:55,686:INFO:Total runtime is 0.19567695061365764 minutes 2024-11-25 14:01:55,687:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:55,688:INFO:Initializing create_model() 2024-11-25 14:01:55,688:INFO:create_model(self=, estimator=omp_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:55,688:INFO:Checking exceptions 2024-11-25 14:01:55,688:INFO:Importing libraries 2024-11-25 14:01:55,688:INFO:Copying training dataset 2024-11-25 14:01:55,689:INFO:Defining folds 2024-11-25 14:01:55,689:INFO:Declaring metric variables 2024-11-25 14:01:55,690:INFO:Importing untrained model 2024-11-25 14:01:55,691:INFO:Orthogonal Matching Pursuit w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:55,695:INFO:Starting cross validation 2024-11-25 14:01:55,695:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:55,942:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,943:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,956:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,956:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,966:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,967:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,976:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,976:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,996:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,996:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:55,999:INFO:Calculating mean and std 2024-11-25 14:01:55,999:INFO:Creating metrics dataframe 2024-11-25 14:01:56,000:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:56,001:INFO:Uploading results into container 2024-11-25 14:01:56,001:INFO:Uploading model into container now 2024-11-25 14:01:56,001:INFO:_master_model_container: 19 2024-11-25 14:01:56,001:INFO:_display_container: 2 2024-11-25 14:01:56,002:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=OrthogonalMatchingPursuit(), sp=12, window_length=12) 2024-11-25 14:01:56,002:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:56,067:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:56,067:INFO:Creating metrics dataframe 2024-11-25 14:01:56,073:INFO:Initializing K Neighbors w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:56,073:INFO:Total runtime is 0.2021206021308899 minutes 2024-11-25 14:01:56,074:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:56,074:INFO:Initializing create_model() 2024-11-25 14:01:56,074:INFO:create_model(self=, estimator=knn_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:56,074:INFO:Checking exceptions 2024-11-25 14:01:56,074:INFO:Importing libraries 2024-11-25 14:01:56,074:INFO:Copying training dataset 2024-11-25 14:01:56,075:INFO:Defining folds 2024-11-25 14:01:56,076:INFO:Declaring metric variables 2024-11-25 14:01:56,077:INFO:Importing untrained model 2024-11-25 14:01:56,078:INFO:K Neighbors w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:56,081:INFO:Starting cross validation 2024-11-25 14:01:56,082:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:56,636:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,636:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,636:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,636:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,636:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,637:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,644:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,644:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,653:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,653:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,667:INFO:Calculating mean and std 2024-11-25 14:01:56,668:INFO:Creating metrics dataframe 2024-11-25 14:01:56,669:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:56,669:INFO:Uploading results into container 2024-11-25 14:01:56,669:INFO:Uploading model into container now 2024-11-25 14:01:56,669:INFO:_master_model_container: 20 2024-11-25 14:01:56,669:INFO:_display_container: 2 2024-11-25 14:01:56,670:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=KNeighborsRegressor(n_jobs=-1), sp=12, window_length=12) 2024-11-25 14:01:56,670:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:56,736:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:56,736:INFO:Creating metrics dataframe 2024-11-25 14:01:56,741:INFO:Initializing Decision Tree w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:56,741:INFO:Total runtime is 0.2132603367169698 minutes 2024-11-25 14:01:56,743:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:56,743:INFO:Initializing create_model() 2024-11-25 14:01:56,743:INFO:create_model(self=, estimator=dt_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:56,743:INFO:Checking exceptions 2024-11-25 14:01:56,743:INFO:Importing libraries 2024-11-25 14:01:56,743:INFO:Copying training dataset 2024-11-25 14:01:56,745:INFO:Defining folds 2024-11-25 14:01:56,745:INFO:Declaring metric variables 2024-11-25 14:01:56,746:INFO:Importing untrained model 2024-11-25 14:01:56,747:INFO:Decision Tree w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:56,750:INFO:Starting cross validation 2024-11-25 14:01:56,750:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:56,981:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,982:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,982:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:56,982:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,001:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,001:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,011:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,011:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,049:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,049:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,055:INFO:Calculating mean and std 2024-11-25 14:01:57,056:INFO:Creating metrics dataframe 2024-11-25 14:01:57,056:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:57,057:INFO:Uploading results into container 2024-11-25 14:01:57,057:INFO:Uploading model into container now 2024-11-25 14:01:57,058:INFO:_master_model_container: 21 2024-11-25 14:01:57,058:INFO:_display_container: 2 2024-11-25 14:01:57,059:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=DecisionTreeRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:57,059:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:57,125:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:57,125:INFO:Creating metrics dataframe 2024-11-25 14:01:57,130:INFO:Initializing Random Forest w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:57,130:INFO:Total runtime is 0.21974596579869587 minutes 2024-11-25 14:01:57,132:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:57,132:INFO:Initializing create_model() 2024-11-25 14:01:57,132:INFO:create_model(self=, estimator=rf_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:57,132:INFO:Checking exceptions 2024-11-25 14:01:57,132:INFO:Importing libraries 2024-11-25 14:01:57,132:INFO:Copying training dataset 2024-11-25 14:01:57,133:INFO:Defining folds 2024-11-25 14:01:57,133:INFO:Declaring metric variables 2024-11-25 14:01:57,134:INFO:Importing untrained model 2024-11-25 14:01:57,136:INFO:Random Forest w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:57,138:INFO:Starting cross validation 2024-11-25 14:01:57,139:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:57,767:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,767:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,779:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,779:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,787:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,787:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,792:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,792:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,813:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,813:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:57,818:INFO:Calculating mean and std 2024-11-25 14:01:57,818:INFO:Creating metrics dataframe 2024-11-25 14:01:57,819:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:57,820:INFO:Uploading results into container 2024-11-25 14:01:57,820:INFO:Uploading model into container now 2024-11-25 14:01:57,820:INFO:_master_model_container: 22 2024-11-25 14:01:57,820:INFO:_display_container: 2 2024-11-25 14:01:57,822:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=RandomForestRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 14:01:57,822:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:57,889:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:57,889:INFO:Creating metrics dataframe 2024-11-25 14:01:57,893:INFO:Initializing Extra Trees w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:57,893:INFO:Total runtime is 0.2324606696764628 minutes 2024-11-25 14:01:57,895:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:57,895:INFO:Initializing create_model() 2024-11-25 14:01:57,895:INFO:create_model(self=, estimator=et_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:57,895:INFO:Checking exceptions 2024-11-25 14:01:57,895:INFO:Importing libraries 2024-11-25 14:01:57,895:INFO:Copying training dataset 2024-11-25 14:01:57,896:INFO:Defining folds 2024-11-25 14:01:57,896:INFO:Declaring metric variables 2024-11-25 14:01:57,897:INFO:Importing untrained model 2024-11-25 14:01:57,899:INFO:Extra Trees w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:57,901:INFO:Starting cross validation 2024-11-25 14:01:57,902:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:58,504:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,505:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,508:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,508:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,518:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,518:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,523:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,524:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,529:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,529:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,541:INFO:Calculating mean and std 2024-11-25 14:01:58,541:INFO:Creating metrics dataframe 2024-11-25 14:01:58,542:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:58,543:INFO:Uploading results into container 2024-11-25 14:01:58,543:INFO:Uploading model into container now 2024-11-25 14:01:58,543:INFO:_master_model_container: 23 2024-11-25 14:01:58,544:INFO:_display_container: 2 2024-11-25 14:01:58,545:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=ExtraTreesRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 14:01:58,545:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:58,611:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:58,611:INFO:Creating metrics dataframe 2024-11-25 14:01:58,616:INFO:Initializing Gradient Boosting w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:58,616:INFO:Total runtime is 0.24450560013453165 minutes 2024-11-25 14:01:58,617:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:58,617:INFO:Initializing create_model() 2024-11-25 14:01:58,617:INFO:create_model(self=, estimator=gbr_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:58,617:INFO:Checking exceptions 2024-11-25 14:01:58,618:INFO:Importing libraries 2024-11-25 14:01:58,618:INFO:Copying training dataset 2024-11-25 14:01:58,619:INFO:Defining folds 2024-11-25 14:01:58,619:INFO:Declaring metric variables 2024-11-25 14:01:58,620:INFO:Importing untrained model 2024-11-25 14:01:58,622:INFO:Gradient Boosting w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:58,624:INFO:Starting cross validation 2024-11-25 14:01:58,625:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:58,902:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,903:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,903:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,903:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,910:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,910:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,919:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,920:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,924:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,924:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:58,928:INFO:Calculating mean and std 2024-11-25 14:01:58,928:INFO:Creating metrics dataframe 2024-11-25 14:01:58,929:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:58,930:INFO:Uploading results into container 2024-11-25 14:01:58,930:INFO:Uploading model into container now 2024-11-25 14:01:58,930:INFO:_master_model_container: 24 2024-11-25 14:01:58,930:INFO:_display_container: 2 2024-11-25 14:01:58,931:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=GradientBoostingRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:58,931:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:58,996:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:58,996:INFO:Creating metrics dataframe 2024-11-25 14:01:59,002:INFO:Initializing AdaBoost w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:59,002:INFO:Total runtime is 0.2509408354759216 minutes 2024-11-25 14:01:59,003:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:59,003:INFO:Initializing create_model() 2024-11-25 14:01:59,004:INFO:create_model(self=, estimator=ada_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:59,004:INFO:Checking exceptions 2024-11-25 14:01:59,004:INFO:Importing libraries 2024-11-25 14:01:59,004:INFO:Copying training dataset 2024-11-25 14:01:59,005:INFO:Defining folds 2024-11-25 14:01:59,005:INFO:Declaring metric variables 2024-11-25 14:01:59,006:INFO:Importing untrained model 2024-11-25 14:01:59,007:INFO:AdaBoost w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:59,010:INFO:Starting cross validation 2024-11-25 14:01:59,011:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:59,313:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,313:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,316:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,317:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,328:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,328:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,338:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,338:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,339:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,339:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,343:INFO:Calculating mean and std 2024-11-25 14:01:59,343:INFO:Creating metrics dataframe 2024-11-25 14:01:59,344:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:59,345:INFO:Uploading results into container 2024-11-25 14:01:59,345:INFO:Uploading model into container now 2024-11-25 14:01:59,345:INFO:_master_model_container: 25 2024-11-25 14:01:59,345:INFO:_display_container: 2 2024-11-25 14:01:59,346:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=AdaBoostRegressor(random_state=42), sp=12, window_length=12) 2024-11-25 14:01:59,346:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:59,412:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:59,412:INFO:Creating metrics dataframe 2024-11-25 14:01:59,418:INFO:Initializing Light Gradient Boosting w/ Cond. Deseasonalize & Detrending 2024-11-25 14:01:59,418:INFO:Total runtime is 0.25786844889322913 minutes 2024-11-25 14:01:59,419:INFO:SubProcess create_model() called ================================== 2024-11-25 14:01:59,419:INFO:Initializing create_model() 2024-11-25 14:01:59,419:INFO:create_model(self=, estimator=lightgbm_cds_dt, fold=None, 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=, model_only=True, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:01:59,419:INFO:Checking exceptions 2024-11-25 14:01:59,419:INFO:Importing libraries 2024-11-25 14:01:59,419:INFO:Copying training dataset 2024-11-25 14:01:59,420:INFO:Defining folds 2024-11-25 14:01:59,421:INFO:Declaring metric variables 2024-11-25 14:01:59,422:INFO:Importing untrained model 2024-11-25 14:01:59,423:INFO:Light Gradient Boosting w/ Cond. Deseasonalize & Detrending Imported successfully 2024-11-25 14:01:59,426:INFO:Starting cross validation 2024-11-25 14:01:59,427:INFO:Cross validating with ExpandingWindowSplitter(fh=ForecastingHorizon([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], dtype='int64', is_relative=True), initial_window=62, step_length=24), n_jobs=-1 2024-11-25 14:01:59,578:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,587:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,589:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,595:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,597:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,600:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,603:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,605:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,607:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,607:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,610:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,612:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,614:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,615:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,617:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,619:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,622:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,622:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,625:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,627:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,629:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,629:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,632:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,634:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,637:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,638:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,640:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,642:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,646:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,647:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,649:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,649:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,651:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,654:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,656:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,657:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,658:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,663:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,663:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,664:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,665:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,667:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,671:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,671:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,673:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,674:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,677:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,679:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,680:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,683:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,683:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,686:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,689:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,689:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,691:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,692:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,695:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,697:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,698:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,701:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,701:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,704:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,706:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,707:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,708:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,712:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,712:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,715:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,716:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,717:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,719:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,722:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,724:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,724:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,725:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,730:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,731:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,732:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,734:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,739:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,739:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,740:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,741:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,745:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,747:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,747:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,749:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,750:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,754:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,755:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,756:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,757:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,760:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,761:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,765:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,766:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,767:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,769:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,769:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,773:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,773:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,774:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,775:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,776:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,780:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,782:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,782:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,783:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,786:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,788:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,790:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,790:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,795:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,797:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,798:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,801:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,801:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,802:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,805:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,808:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,808:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,809:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,816:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,823:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,830:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,836:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/lightgbm/basic.py:722: UserWarning: Usage of np.ndarray subset (sliced data) is not recommended due to it will double the peak memory cost in LightGBM. _log_warning( 2024-11-25 14:01:59,840:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,840:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/sklearn/metrics/_regression.py:483: FutureWarning: 'squared' is deprecated in version 1.4 and will be removed in 1.6. To calculate the root mean squared error, use the function'root_mean_squared_error'. warnings.warn( 2024-11-25 14:01:59,847:INFO:Calculating mean and std 2024-11-25 14:01:59,847:INFO:Creating metrics dataframe 2024-11-25 14:01:59,848:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/pycaret/time_series/forecasting/oop.py:2694: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation. model_results = pd.concat((model_results, model_avgs), axis=0) 2024-11-25 14:01:59,849:INFO:Uploading results into container 2024-11-25 14:01:59,849:INFO:Uploading model into container now 2024-11-25 14:01:59,849:INFO:_master_model_container: 26 2024-11-25 14:01:59,849:INFO:_display_container: 2 2024-11-25 14:01:59,849:INFO:BaseCdsDtForecaster(fe_target_rr=[WindowSummarizer(lag_feature={'lag': [12, 11, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1]}, n_jobs=1)], regressor=LGBMRegressor(n_jobs=-1, random_state=42), sp=12, window_length=12) 2024-11-25 14:01:59,849:INFO:create_model() successfully completed...................................... 2024-11-25 14:01:59,915:INFO:SubProcess create_model() end ================================== 2024-11-25 14:01:59,915:INFO:Creating metrics dataframe 2024-11-25 14:01:59,921:WARNING:/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/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)"]) 2024-11-25 14:01:59,924:INFO:Initializing create_model() 2024-11-25 14:01:59,924:INFO:create_model(self=, estimator=NaiveForecaster(), fold=None, 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={}) 2024-11-25 14:01:59,924:INFO:Checking exceptions 2024-11-25 14:01:59,925:INFO:Importing libraries 2024-11-25 14:01:59,926:INFO:Copying training dataset 2024-11-25 14:01:59,927:INFO:Defining folds 2024-11-25 14:01:59,927:INFO:Declaring metric variables 2024-11-25 14:01:59,927:INFO:Importing untrained model 2024-11-25 14:01:59,927:INFO:Declaring custom model 2024-11-25 14:01:59,927:INFO:Naive Forecaster Imported successfully 2024-11-25 14:01:59,927:INFO:Cross validation set to False 2024-11-25 14:01:59,927:INFO:Fitting Model 2024-11-25 14:01:59,931:INFO:NaiveForecaster() 2024-11-25 14:01:59,931:INFO:create_model() successfully completed...................................... 2024-11-25 14:02:00,012:INFO:_master_model_container: 26 2024-11-25 14:02:00,012:INFO:_display_container: 2 2024-11-25 14:02:00,012:INFO:NaiveForecaster() 2024-11-25 14:02:00,012:INFO:compare_models() successfully completed...................................... 2024-11-25 14:02:00,013:INFO:Initializing finalize_model() 2024-11-25 14:02:00,013:INFO:finalize_model(self=, estimator=NaiveForecaster(), fit_kwargs=None, groups=None, model_only=False, experiment_custom_tags=None) 2024-11-25 14:02:00,013:INFO:Finalizing NaiveForecaster() 2024-11-25 14:02:00,014:INFO:Initializing create_model() 2024-11-25 14:02:00,014:INFO:create_model(self=, estimator=NaiveForecaster(), fold=None, 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=False, metrics=None, display=None, model_only=False, return_train_score=False, error_score=0.0, kwargs={}) 2024-11-25 14:02:00,014:INFO:Checking exceptions 2024-11-25 14:02:00,014:INFO:Importing libraries 2024-11-25 14:02:00,014:INFO:Copying training dataset 2024-11-25 14:02:00,015:INFO:Defining folds 2024-11-25 14:02:00,015:INFO:Declaring metric variables 2024-11-25 14:02:00,015:INFO:Importing untrained model 2024-11-25 14:02:00,015:INFO:Declaring custom model 2024-11-25 14:02:00,015:INFO:Naive Forecaster Imported successfully 2024-11-25 14:02:00,016:INFO:Cross validation set to False 2024-11-25 14:02:00,016:INFO:Fitting Model 2024-11-25 14:02:00,020:INFO:ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', NaiveForecaster())]))]) 2024-11-25 14:02:00,020:INFO:create_model() successfully completed...................................... 2024-11-25 14:02:00,114:INFO:_master_model_container: 26 2024-11-25 14:02:00,114:INFO:_display_container: 2 2024-11-25 14:02:00,115:INFO:ForecastingPipeline(steps=[('forecaster', TransformedTargetForecaster(steps=[('model', NaiveForecaster())]))]) 2024-11-25 14:02:00,115:INFO:finalize_model() successfully completed...................................... 2024-11-25 14:02:00,187:WARNING:predict_model >> Prediction Indices do not match test indices. Metrics will not be displayed. 2024-11-25 14:30:29,707:INFO:Soft dependency imported: prophet: 1.1.6 2024-11-25 14:30:41,612:INFO:PyCaret TSForecastingExperiment 2024-11-25 14:30:41,612:INFO:Logging name: ts-default-name 2024-11-25 14:30:41,612:INFO:ML Usecase: MLUsecase.TIME_SERIES 2024-11-25 14:30:41,612:INFO:version 3.3.2 2024-11-25 14:30:41,612:INFO:Initializing setup() 2024-11-25 14:30:41,612:INFO:self.USI: 6850 2024-11-25 14:30:41,612:INFO:self._variable_keys: {'html_param', 'logging_param', 'approach_type', 'fold_generator', 'all_sps_to_use', 'enforce_pi', 'X_train', 'y_train_transformed', 'significant_sps_no_harmonics', 'exp_name_log', 'exogenous_present', 'exp_id', 'X_test', 'seed', 'gpu_param', 'data', 'significant_sps', 'y_test', 'model_engines', '_ml_usecase', 'y_transformed', 'X_transformed', 'memory', 'y', 'X_train_transformed', '_available_plots', 'index_type', 'y_test_transformed', 'X_test_transformed', 'n_jobs_param', 'fold_param', 'fh', 'idx', 'log_plots_param', 'primary_sp_to_use', 'gpu_n_jobs_param', 'strictly_positive', 'pipeline', 'y_train', 'USI', 'enforce_exogenous', 'X', 'candidate_sps', 'seasonality_present'} 2024-11-25 14:30:41,612:INFO:Checking environment 2024-11-25 14:30:41,612:INFO:python_version: 3.11.6 2024-11-25 14:30:41,612:INFO:python_build: ('v3.11.6:8b6ee5ba3b', 'Oct 2 2023 11:18:21') 2024-11-25 14:30:41,612:INFO:machine: arm64 2024-11-25 14:30:41,612:INFO:platform: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:30:41,613:INFO:Memory: svmem(total=17179869184, available=5650956288, percent=67.1, used=7597867008, free=55115776, active=5632655360, inactive=5591842816, wired=1965211648) 2024-11-25 14:30:41,613:INFO:Physical Core: 8 2024-11-25 14:30:41,613:INFO:Logical Core: 8 2024-11-25 14:30:41,613:INFO:Checking libraries 2024-11-25 14:30:41,613:INFO:System: 2024-11-25 14:30:41,613:INFO: python: 3.11.6 (v3.11.6:8b6ee5ba3b, Oct 2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] 2024-11-25 14:30:41,613:INFO:executable: /usr/local/bin/python3 2024-11-25 14:30:41,613:INFO: machine: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:30:41,613:INFO:PyCaret required dependencies: 2024-11-25 14:30:41,691:INFO: pip: 24.3.1 2024-11-25 14:30:41,691:INFO: setuptools: 75.5.0 2024-11-25 14:30:41,691:INFO: pycaret: 3.3.2 2024-11-25 14:30:41,691:INFO: IPython: 8.29.0 2024-11-25 14:30:41,691:INFO: ipywidgets: 8.1.5 2024-11-25 14:30:41,691:INFO: tqdm: 4.67.0 2024-11-25 14:30:41,691:INFO: numpy: 1.26.4 2024-11-25 14:30:41,691:INFO: pandas: 2.1.4 2024-11-25 14:30:41,691:INFO: jinja2: 3.1.4 2024-11-25 14:30:41,691:INFO: scipy: 1.11.4 2024-11-25 14:30:41,691:INFO: joblib: 1.3.2 2024-11-25 14:30:41,691:INFO: sklearn: 1.4.2 2024-11-25 14:30:41,692:INFO: pyod: 2.0.2 2024-11-25 14:30:41,692:INFO: imblearn: 0.12.4 2024-11-25 14:30:41,692:INFO: category_encoders: 2.6.4 2024-11-25 14:30:41,692:INFO: lightgbm: 4.5.0 2024-11-25 14:30:41,692:INFO: numba: 0.60.0 2024-11-25 14:30:41,692:INFO: requests: 2.32.3 2024-11-25 14:30:41,692:INFO: matplotlib: 3.7.5 2024-11-25 14:30:41,692:INFO: scikitplot: 0.3.7 2024-11-25 14:30:41,692:INFO: yellowbrick: 1.5 2024-11-25 14:30:41,692:INFO: plotly: 5.24.1 2024-11-25 14:30:41,692:INFO: plotly-resampler: Not installed 2024-11-25 14:30:41,692:INFO: kaleido: 0.2.1 2024-11-25 14:30:41,692:INFO: schemdraw: 0.15 2024-11-25 14:30:41,692:INFO: statsmodels: 0.14.4 2024-11-25 14:30:41,692:INFO: sktime: 0.26.0 2024-11-25 14:30:41,692:INFO: tbats: 1.1.3 2024-11-25 14:30:41,692:INFO: pmdarima: 2.0.4 2024-11-25 14:30:41,692:INFO: psutil: 6.1.0 2024-11-25 14:30:41,692:INFO: markupsafe: 2.1.5 2024-11-25 14:30:41,692:INFO: pickle5: Not installed 2024-11-25 14:30:41,692:INFO: cloudpickle: 3.1.0 2024-11-25 14:30:41,692:INFO: deprecation: 2.1.0 2024-11-25 14:30:41,692:INFO: xxhash: 3.5.0 2024-11-25 14:30:41,692:INFO: wurlitzer: 3.1.1 2024-11-25 14:30:41,692:INFO:PyCaret optional dependencies: 2024-11-25 14:30:42,799:INFO: shap: Not installed 2024-11-25 14:30:42,799:INFO: interpret: Not installed 2024-11-25 14:30:42,799:INFO: umap: 0.5.7 2024-11-25 14:30:42,799:INFO: ydata_profiling: Not installed 2024-11-25 14:30:42,799:INFO: explainerdashboard: Not installed 2024-11-25 14:30:42,799:INFO: autoviz: Not installed 2024-11-25 14:30:42,799:INFO: fairlearn: Not installed 2024-11-25 14:30:42,799:INFO: deepchecks: Not installed 2024-11-25 14:30:42,799:INFO: xgboost: Not installed 2024-11-25 14:30:42,799:INFO: catboost: Not installed 2024-11-25 14:30:42,799:INFO: kmodes: Not installed 2024-11-25 14:30:42,799:INFO: mlxtend: Not installed 2024-11-25 14:30:42,799:INFO: statsforecast: Not installed 2024-11-25 14:30:42,799:INFO: tune_sklearn: Not installed 2024-11-25 14:30:42,799:INFO: ray: Not installed 2024-11-25 14:30:42,799:INFO: hyperopt: Not installed 2024-11-25 14:30:42,799:INFO: optuna: 4.1.0 2024-11-25 14:30:42,799:INFO: skopt: Not installed 2024-11-25 14:30:42,799:INFO: mlflow: Not installed 2024-11-25 14:30:42,799:INFO: gradio: 5.6.0 2024-11-25 14:30:42,799:INFO: fastapi: 0.115.5 2024-11-25 14:30:42,799:INFO: uvicorn: 0.32.0 2024-11-25 14:30:42,799:INFO: m2cgen: Not installed 2024-11-25 14:30:42,799:INFO: evidently: Not installed 2024-11-25 14:30:42,799:INFO: fugue: Not installed 2024-11-25 14:30:42,799:INFO: streamlit: Not installed 2024-11-25 14:30:42,799:INFO: prophet: 1.1.6 2024-11-25 14:30:42,799:INFO:None 2024-11-25 14:30:57,051:INFO:PyCaret TSForecastingExperiment 2024-11-25 14:30:57,051:INFO:Logging name: ts-default-name 2024-11-25 14:30:57,051:INFO:ML Usecase: MLUsecase.TIME_SERIES 2024-11-25 14:30:57,051:INFO:version 3.3.2 2024-11-25 14:30:57,051:INFO:Initializing setup() 2024-11-25 14:30:57,051:INFO:self.USI: db33 2024-11-25 14:30:57,051:INFO:self._variable_keys: {'html_param', 'logging_param', 'approach_type', 'fold_generator', 'all_sps_to_use', 'enforce_pi', 'X_train', 'y_train_transformed', 'significant_sps_no_harmonics', 'exp_name_log', 'exogenous_present', 'exp_id', 'X_test', 'seed', 'gpu_param', 'data', 'significant_sps', 'y_test', 'model_engines', '_ml_usecase', 'y_transformed', 'X_transformed', 'memory', 'y', 'X_train_transformed', '_available_plots', 'index_type', 'y_test_transformed', 'X_test_transformed', 'n_jobs_param', 'fold_param', 'fh', 'idx', 'log_plots_param', 'primary_sp_to_use', 'gpu_n_jobs_param', 'strictly_positive', 'pipeline', 'y_train', 'USI', 'enforce_exogenous', 'X', 'candidate_sps', 'seasonality_present'} 2024-11-25 14:30:57,051:INFO:Checking environment 2024-11-25 14:30:57,051:INFO:python_version: 3.11.6 2024-11-25 14:30:57,051:INFO:python_build: ('v3.11.6:8b6ee5ba3b', 'Oct 2 2023 11:18:21') 2024-11-25 14:30:57,052:INFO:machine: arm64 2024-11-25 14:30:57,052:INFO:platform: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:30:57,052:INFO:Memory: svmem(total=17179869184, available=5741871104, percent=66.6, used=7518355456, free=118980608, active=5650595840, inactive=5594349568, wired=1867759616) 2024-11-25 14:30:57,052:INFO:Physical Core: 8 2024-11-25 14:30:57,052:INFO:Logical Core: 8 2024-11-25 14:30:57,052:INFO:Checking libraries 2024-11-25 14:30:57,052:INFO:System: 2024-11-25 14:30:57,052:INFO: python: 3.11.6 (v3.11.6:8b6ee5ba3b, Oct 2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] 2024-11-25 14:30:57,052:INFO:executable: /usr/local/bin/python3 2024-11-25 14:30:57,052:INFO: machine: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:30:57,052:INFO:PyCaret required dependencies: 2024-11-25 14:30:57,052:INFO: pip: 24.3.1 2024-11-25 14:30:57,052:INFO: setuptools: 75.5.0 2024-11-25 14:30:57,052:INFO: pycaret: 3.3.2 2024-11-25 14:30:57,052:INFO: IPython: 8.29.0 2024-11-25 14:30:57,052:INFO: ipywidgets: 8.1.5 2024-11-25 14:30:57,052:INFO: tqdm: 4.67.0 2024-11-25 14:30:57,052:INFO: numpy: 1.26.4 2024-11-25 14:30:57,052:INFO: pandas: 2.1.4 2024-11-25 14:30:57,052:INFO: jinja2: 3.1.4 2024-11-25 14:30:57,052:INFO: scipy: 1.11.4 2024-11-25 14:30:57,052:INFO: joblib: 1.3.2 2024-11-25 14:30:57,052:INFO: sklearn: 1.4.2 2024-11-25 14:30:57,052:INFO: pyod: 2.0.2 2024-11-25 14:30:57,052:INFO: imblearn: 0.12.4 2024-11-25 14:30:57,052:INFO: category_encoders: 2.6.4 2024-11-25 14:30:57,052:INFO: lightgbm: 4.5.0 2024-11-25 14:30:57,052:INFO: numba: 0.60.0 2024-11-25 14:30:57,052:INFO: requests: 2.32.3 2024-11-25 14:30:57,052:INFO: matplotlib: 3.7.5 2024-11-25 14:30:57,052:INFO: scikitplot: 0.3.7 2024-11-25 14:30:57,052:INFO: yellowbrick: 1.5 2024-11-25 14:30:57,052:INFO: plotly: 5.24.1 2024-11-25 14:30:57,052:INFO: plotly-resampler: Not installed 2024-11-25 14:30:57,052:INFO: kaleido: 0.2.1 2024-11-25 14:30:57,052:INFO: schemdraw: 0.15 2024-11-25 14:30:57,052:INFO: statsmodels: 0.14.4 2024-11-25 14:30:57,052:INFO: sktime: 0.26.0 2024-11-25 14:30:57,052:INFO: tbats: 1.1.3 2024-11-25 14:30:57,053:INFO: pmdarima: 2.0.4 2024-11-25 14:30:57,053:INFO: psutil: 6.1.0 2024-11-25 14:30:57,053:INFO: markupsafe: 2.1.5 2024-11-25 14:30:57,053:INFO: pickle5: Not installed 2024-11-25 14:30:57,053:INFO: cloudpickle: 3.1.0 2024-11-25 14:30:57,053:INFO: deprecation: 2.1.0 2024-11-25 14:30:57,053:INFO: xxhash: 3.5.0 2024-11-25 14:30:57,053:INFO: wurlitzer: 3.1.1 2024-11-25 14:30:57,053:INFO:PyCaret optional dependencies: 2024-11-25 14:30:57,053:INFO: shap: Not installed 2024-11-25 14:30:57,053:INFO: interpret: Not installed 2024-11-25 14:30:57,053:INFO: umap: 0.5.7 2024-11-25 14:30:57,053:INFO: ydata_profiling: Not installed 2024-11-25 14:30:57,053:INFO: explainerdashboard: Not installed 2024-11-25 14:30:57,053:INFO: autoviz: Not installed 2024-11-25 14:30:57,053:INFO: fairlearn: Not installed 2024-11-25 14:30:57,053:INFO: deepchecks: Not installed 2024-11-25 14:30:57,053:INFO: xgboost: Not installed 2024-11-25 14:30:57,053:INFO: catboost: Not installed 2024-11-25 14:30:57,053:INFO: kmodes: Not installed 2024-11-25 14:30:57,053:INFO: mlxtend: Not installed 2024-11-25 14:30:57,053:INFO: statsforecast: Not installed 2024-11-25 14:30:57,053:INFO: tune_sklearn: Not installed 2024-11-25 14:30:57,053:INFO: ray: Not installed 2024-11-25 14:30:57,053:INFO: hyperopt: Not installed 2024-11-25 14:30:57,053:INFO: optuna: 4.1.0 2024-11-25 14:30:57,053:INFO: skopt: Not installed 2024-11-25 14:30:57,053:INFO: mlflow: Not installed 2024-11-25 14:30:57,053:INFO: gradio: 5.6.0 2024-11-25 14:30:57,053:INFO: fastapi: 0.115.5 2024-11-25 14:30:57,053:INFO: uvicorn: 0.32.0 2024-11-25 14:30:57,053:INFO: m2cgen: Not installed 2024-11-25 14:30:57,053:INFO: evidently: Not installed 2024-11-25 14:30:57,053:INFO: fugue: Not installed 2024-11-25 14:30:57,053:INFO: streamlit: Not installed 2024-11-25 14:30:57,053:INFO: prophet: 1.1.6 2024-11-25 14:30:57,053:INFO:None 2024-11-25 14:31:33,705:INFO:PyCaret TSForecastingExperiment 2024-11-25 14:31:33,705:INFO:Logging name: ts-default-name 2024-11-25 14:31:33,705:INFO:ML Usecase: MLUsecase.TIME_SERIES 2024-11-25 14:31:33,705:INFO:version 3.3.2 2024-11-25 14:31:33,705:INFO:Initializing setup() 2024-11-25 14:31:33,705:INFO:self.USI: ca35 2024-11-25 14:31:33,705:INFO:self._variable_keys: {'html_param', 'logging_param', 'approach_type', 'fold_generator', 'all_sps_to_use', 'enforce_pi', 'X_train', 'y_train_transformed', 'significant_sps_no_harmonics', 'exp_name_log', 'exogenous_present', 'exp_id', 'X_test', 'seed', 'gpu_param', 'data', 'significant_sps', 'y_test', 'model_engines', '_ml_usecase', 'y_transformed', 'X_transformed', 'memory', 'y', 'X_train_transformed', '_available_plots', 'index_type', 'y_test_transformed', 'X_test_transformed', 'n_jobs_param', 'fold_param', 'fh', 'idx', 'log_plots_param', 'primary_sp_to_use', 'gpu_n_jobs_param', 'strictly_positive', 'pipeline', 'y_train', 'USI', 'enforce_exogenous', 'X', 'candidate_sps', 'seasonality_present'} 2024-11-25 14:31:33,705:INFO:Checking environment 2024-11-25 14:31:33,705:INFO:python_version: 3.11.6 2024-11-25 14:31:33,705:INFO:python_build: ('v3.11.6:8b6ee5ba3b', 'Oct 2 2023 11:18:21') 2024-11-25 14:31:33,705:INFO:machine: arm64 2024-11-25 14:31:33,706:INFO:platform: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:31:33,706:INFO:Memory: svmem(total=17179869184, available=5729435648, percent=66.7, used=7662452736, free=61505536, active=5702041600, inactive=5666471936, wired=1960411136) 2024-11-25 14:31:33,706:INFO:Physical Core: 8 2024-11-25 14:31:33,706:INFO:Logical Core: 8 2024-11-25 14:31:33,706:INFO:Checking libraries 2024-11-25 14:31:33,706:INFO:System: 2024-11-25 14:31:33,706:INFO: python: 3.11.6 (v3.11.6:8b6ee5ba3b, Oct 2 2023, 11:18:21) [Clang 13.0.0 (clang-1300.0.29.30)] 2024-11-25 14:31:33,706:INFO:executable: /usr/local/bin/python3 2024-11-25 14:31:33,706:INFO: machine: macOS-14.6.1-arm64-arm-64bit 2024-11-25 14:31:33,706:INFO:PyCaret required dependencies: 2024-11-25 14:31:33,706:INFO: pip: 24.3.1 2024-11-25 14:31:33,706:INFO: setuptools: 75.5.0 2024-11-25 14:31:33,706:INFO: pycaret: 3.3.2 2024-11-25 14:31:33,706:INFO: IPython: 8.29.0 2024-11-25 14:31:33,706:INFO: ipywidgets: 8.1.5 2024-11-25 14:31:33,706:INFO: tqdm: 4.67.0 2024-11-25 14:31:33,706:INFO: numpy: 1.26.4 2024-11-25 14:31:33,706:INFO: pandas: 2.1.4 2024-11-25 14:31:33,706:INFO: jinja2: 3.1.4 2024-11-25 14:31:33,706:INFO: scipy: 1.11.4 2024-11-25 14:31:33,706:INFO: joblib: 1.3.2 2024-11-25 14:31:33,706:INFO: sklearn: 1.4.2 2024-11-25 14:31:33,706:INFO: pyod: 2.0.2 2024-11-25 14:31:33,706:INFO: imblearn: 0.12.4 2024-11-25 14:31:33,706:INFO: category_encoders: 2.6.4 2024-11-25 14:31:33,706:INFO: lightgbm: 4.5.0 2024-11-25 14:31:33,706:INFO: numba: 0.60.0 2024-11-25 14:31:33,706:INFO: requests: 2.32.3 2024-11-25 14:31:33,706:INFO: matplotlib: 3.7.5 2024-11-25 14:31:33,706:INFO: scikitplot: 0.3.7 2024-11-25 14:31:33,706:INFO: yellowbrick: 1.5 2024-11-25 14:31:33,706:INFO: plotly: 5.24.1 2024-11-25 14:31:33,706:INFO: plotly-resampler: Not installed 2024-11-25 14:31:33,706:INFO: kaleido: 0.2.1 2024-11-25 14:31:33,706:INFO: schemdraw: 0.15 2024-11-25 14:31:33,706:INFO: statsmodels: 0.14.4 2024-11-25 14:31:33,706:INFO: sktime: 0.26.0 2024-11-25 14:31:33,706:INFO: tbats: 1.1.3 2024-11-25 14:31:33,706:INFO: pmdarima: 2.0.4 2024-11-25 14:31:33,706:INFO: psutil: 6.1.0 2024-11-25 14:31:33,706:INFO: markupsafe: 2.1.5 2024-11-25 14:31:33,706:INFO: pickle5: Not installed 2024-11-25 14:31:33,706:INFO: cloudpickle: 3.1.0 2024-11-25 14:31:33,706:INFO: deprecation: 2.1.0 2024-11-25 14:31:33,706:INFO: xxhash: 3.5.0 2024-11-25 14:31:33,706:INFO: wurlitzer: 3.1.1 2024-11-25 14:31:33,706:INFO:PyCaret optional dependencies: 2024-11-25 14:31:33,706:INFO: shap: Not installed 2024-11-25 14:31:33,706:INFO: interpret: Not installed 2024-11-25 14:31:33,706:INFO: umap: 0.5.7 2024-11-25 14:31:33,706:INFO: ydata_profiling: Not installed 2024-11-25 14:31:33,707:INFO: explainerdashboard: Not installed 2024-11-25 14:31:33,707:INFO: autoviz: Not installed 2024-11-25 14:31:33,707:INFO: fairlearn: Not installed 2024-11-25 14:31:33,707:INFO: deepchecks: Not installed 2024-11-25 14:31:33,707:INFO: xgboost: Not installed 2024-11-25 14:31:33,707:INFO: catboost: Not installed 2024-11-25 14:31:33,707:INFO: kmodes: Not installed 2024-11-25 14:31:33,707:INFO: mlxtend: Not installed 2024-11-25 14:31:33,707:INFO: statsforecast: Not installed 2024-11-25 14:31:33,707:INFO: tune_sklearn: Not installed 2024-11-25 14:31:33,707:INFO: ray: Not installed 2024-11-25 14:31:33,707:INFO: hyperopt: Not installed 2024-11-25 14:31:33,707:INFO: optuna: 4.1.0 2024-11-25 14:31:33,707:INFO: skopt: Not installed 2024-11-25 14:31:33,707:INFO: mlflow: Not installed 2024-11-25 14:31:33,707:INFO: gradio: 5.6.0 2024-11-25 14:31:33,707:INFO: fastapi: 0.115.5 2024-11-25 14:31:33,707:INFO: uvicorn: 0.32.0 2024-11-25 14:31:33,707:INFO: m2cgen: Not installed 2024-11-25 14:31:33,707:INFO: evidently: Not installed 2024-11-25 14:31:33,707:INFO: fugue: Not installed 2024-11-25 14:31:33,707:INFO: streamlit: Not installed 2024-11-25 14:31:33,707:INFO: prophet: 1.1.6 2024-11-25 14:31:33,707:INFO:None