Suite.run#
- Suite.run(train_dataset: Optional[VisionData] = None, test_dataset: Optional[VisionData] = None, random_state: int = 42, with_display: bool = True, max_samples: Optional[int] = None, run_single_dataset: Optional[str] = None) SuiteResult[source]#
Run all checks.
- Parameters
- train_datasetOptional[VisionData] , default: None
VisionData object, representing data the model was fitted on
- test_datasetOptional[VisionData] , default: None
VisionData object, representing data the models predicts on
- random_stateint
A seed to set for pseudo-random functions
- with_displaybool , default: True
flag that determines if checks will calculate display (redundant in some checks).
- max_samplesOptional[int] , default: None
Each check will run on a number of samples which is the minimum between the n_samples parameter of the check and this parameter. If this argument is None then the number of samples for each check will be determined by the n_samples argument.
- run_single_dataset: Optional[str], default None
‘Train’, ‘Test’ , or None to run on both train and test.
- Returns
- SuiteResult
All results by all initialized checks