pycaret.classification.get_metrics

pycaret.classification.get_metrics(reset: bool = False, include_custom: bool = True, raise_errors: bool = True) → DataFrame

Returns table of available metrics used in the experiment.

Example

>>> from pycaret.datasets import get_data
>>> juice = get_data('juice')
>>> from pycaret.classification import *
>>> exp_name = setup(data = juice,  target = 'Purchase')
>>> all_metrics = get_metrics()

reset: bool, default = False

When True, will reset all changes made using the add_metric and remove_metric function.

include_custom: bool, default = True

Whether to include user added (custom) metrics or not.

raise_errors: bool, default = True

If False, will suppress all exceptions, ignoring models that couldn’t be created.

Returns:

pandas.DataFrame