pycaret.time_series.save_model

pycaret.time_series.save_model(model, model_name: str, model_only: bool = False, verbose: bool = True)

This function saves the transformation pipeline and trained model object into the current working directory as a pickle file for later use.

Example

>>> from pycaret.datasets import get_data
>>> data = get_data('airline')
>>> from pycaret.time_series import *
>>> exp_name = setup(data = data, fh = 12)
>>> arima = create_model('arima')
>>> save_model(arima, 'saved_arima_model')

model: sktime compatible object

Trained model object

model_name: str

Name of the model.

model_only: bool, default = False

When set to True, only trained model object is saved instead of the entire pipeline.

verbose: bool, default = True

Success message is not printed when verbose is set to False.

Returns:

Tuple of the model object and the filename.