train_test_leakage#
- train_test_leakage(**kwargs) Suite[source]#
Create a suite for detecting data leakage between the training dataset and the test dataset (Deprecated).
Deprecated since version 0.7.0: train_test_leakage is deprecated and will be removed in deepchecks 0.8 version, it is replaced by train_test_validation 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