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You have trained and registered a machine learning model in Azure ML that predicts loan repayment likelihood. To ensure the model is compliant with government regulations and does not make decisions based on prohibited features like an applicant's location, you need to identify the contribution of each data feature to the model's predictions.
What should you do to determine the influence of each feature?
A
Enable data drift monitoring for the model and its training dataset.
B
Score the model against some test data with known label values and use the results to calculate a confusion matrix.
C
Use the Hyperdrive library to test the model with multiple hyperparameter values.
D
Use the interpretability package to generate an explainer for the model.
E
Add tags to the model registration indicating the names of the features in the training dataset.