pycaret.clustering.get_metrics

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

Returns table of metrics available.

Example

>>> from pycaret.datasets import get_data
>>> jewellery = get_data('jewellery')
>>> from pycaret.clustering import *
>>> exp_name = setup(data = jewellery)
>>> all_metrics = get_metrics()

reset: bool, default = False

If True, will reset all changes made using add_metric() and get_metric().

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