pycaret.clustering.get_logs#

pycaret.clustering.get_logs(experiment_name: str | None = None, save: bool = False) → DataFrame[source]#

Returns a table of experiment logs. Only works when log_experiment is True when initializing the setup function.

Example

>>> from pycaret.datasets import get_data
>>> jewellery = get_data('jewellery')
>>> from pycaret.clustering import *
>>> exp_name = setup(data = jewellery,  log_experiment = True)
>>> kmeans = create_model('kmeans')
>>> exp_logs = get_logs()

experiment_name: str, default = None: When None current active run is used.
save: bool, default = False: When set to True, csv file is saved in current working directory.

Returns:: pandas.DataFrame