single_dataset_integrity#

single_dataset_integrity(**kwargs) Suite[source]#

Create a suite that is meant to detect integrity issues within a single dataset (Deprecated).

Deprecated since version 0.7.0: single_dataset_integrity is deprecated and will be removed in deepchecks 0.8 version, it is replaced by data_integrity suite.

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) 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

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.

features_importance: Optional[pd.Series] , default: None

pass manual features importance .. deprecated:: 0.8.1

Use ‘feature_importance’ instead.

Returns
SuiteResult

All results by all initialized checks