tabensemb.trainer.Trainer.get_leaderboard#

method

Trainer.get_leaderboard(test_data_only: bool = False, dump_trainer: bool = True, cross_validation: int = 0, verbose: bool = True, load_from_previous: bool = False, split_type: str = 'cv', **kwargs) DataFrame[source]#

Run all model bases with/without cross validation for a leaderboard.

Parameters:
test_data_only

Whether to evaluate models only on testing datasets.

dump_trainer

Whether to save the Trainer.

cross_validation

The number of cross-validation. See cross_validation(). 0 to evaluate current trained models on the current dataset.

verbose

Verbosity.

load_from_previous

Load the state of a previous run (mostly because of an unexpected interruption).

split_type

The type of data splitting. “random” and “cv” are supported. Ignored when load_from_previous is True.

**kwargs

Arguments for tabensemb.model.AbstractModel.train()

Returns:
pd.DataFrame

The leaderboard.