UnusedFeatures.run#
- UnusedFeatures.run(train_dataset: Dataset, test_dataset: Dataset, model: Optional[BasicModel] = None, feature_importance_force_permutation: bool = False, feature_importance_timeout: Optional[int] = None) CheckResult[source]#
Run the check.
- Parameters
- train_datasetDataset
dataset representing data an estimator was fitted on
- test_datasetDataset
dataset representing data an estimator predicts on
- modelBasicModel
A scikit-learn-compatible fitted estimator instance
- feature_importance_force_permutationbool , default: False
force calculation of permutation features importance
- feature_importance_timeoutint , default: None
timeout in second for the permutation features importance calculation
- Returns
- CheckResult
value is a dataframe with metrics as indexes, and scores per training and test in the columns. display data is a bar graph of the metrics for training and test data.
- Raises
- DeepchecksValueError
If neither train dataset nor test dataset exist, or either of the dataset objects are not a Dataset instance with a label.