pycaret.classification.models#

pycaret.classification.models(type: str | None = None, internal: bool = False, raise_errors: bool = True) → DataFrame[source]#

Returns table of models available in the model library.

Example

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

type: str, default = None

linear : filters and only return linear models
tree : filters and only return tree based models
ensemble : filters and only return ensemble models

internal: bool, default = False

When True, will return extra columns and rows used internally.

raise_errors: bool, default = True

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

Returns:: pandas.DataFrame