pycaret.time_series.set_config#

pycaret.time_series.set_config(variable: str, value)[source]#

This function resets the global variables. Following variables are accessible:

  • X: Period/Index of X

  • y: Time Series as pd.Series

  • X_train: Period/Index of X_train

  • y_train: Time Series as pd.Series (Train set only)

  • X_test: Period/Index of X_test

  • y_test: Time Series as pd.Series (Test set only)

  • fh: forecast horizon

  • enforce_pi: enforce prediction interval in models

  • seed: random state set through session_id

  • prep_pipe: Transformation pipeline

  • n_jobs_param: n_jobs parameter used in model training

  • html_param: html_param configured through setup

  • _master_model_container: model storage container

  • _display_container: results display container

  • exp_name_log: Name of experiment

  • logging_param: log_experiment param

  • log_plots_param: log_plots param

  • USI: Unique session ID parameter

  • data_before_preprocess: data before preprocessing

  • gpu_param: use_gpu param configured through setup

  • fold_generator: CV splitter configured in fold_strategy

  • fold_param: fold params defined in the setup

  • seasonality_present: seasonality as detected in the setup

  • seasonality_period: seasonality_period as detected in the setup

Example

>>> from pycaret.datasets import get_data
>>> airline = get_data('airline')
>>> from pycaret.time_series import *
>>> exp_name = setup(data = airline,  fh = 12)
>>> set_config('seed', 123)
Returns:

None

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