full_suite

full_suite(**kwargs) → Suite

Create a suite that includes many of the implemented checks, for a quick overview of your model and data.

run(self, train_dataset: Optional[Union[Dataset, DataFrame]] = None, test_dataset: Optional[Union[Dataset, DataFrame]] = None, model: Optional[BasicModel] = None, feature_importance: Optional[Series] = None, feature_importance_force_permutation: bool = False, feature_importance_timeout: int = 120, with_display: bool = True, y_pred_train: Optional[ndarray] = None, y_pred_test: Optional[ndarray] = None, y_proba_train: Optional[ndarray] = None, y_proba_test: Optional[ndarray] = None, run_single_dataset: Optional[str] = None, model_classes: Optional[List] = None) → SuiteResult

Run all checks.

Parameters

train_dataset: Optional[Union[Dataset, pd.DataFrame]] , default None

object, representing data an estimator was fitted on

test_datasetOptional[Union[Dataset, pd.DataFrame]] , default None

object, representing data an estimator predicts on

modelOptional[BasicModel] , default None

A scikit-learn-compatible fitted estimator instance

run_single_dataset: Optional[str], default None

‘Train’, ‘Test’ , or None to run on both train and test.

feature_importance: pd.Series , default: None

pass manual features importance

feature_importance_force_permutationbool , default: False

force calculation of permutation features importance

feature_importance_timeoutint , default: 120

timeout in second for the permutation features importance calculation

y_pred_train: Optional[np.ndarray] , default: None

Array of the model prediction over the train dataset.

y_pred_test: Optional[np.ndarray] , default: None

Array of the model prediction over the test dataset.

y_proba_train: Optional[np.ndarray] , default: None

Array of the model prediction probabilities over the train dataset.

y_proba_test: Optional[np.ndarray] , default: None

Array of the model prediction probabilities over the test dataset.

model_classes: Optional[List] , default: None

For classification: list of classes known to the model

Returns

SuiteResult

All results by all initialized checks

previous

model_evaluation

next

datasets