Question 24
Domain 3: Train and evaluate modelsYou need to configure the responsible AI dashboard in Azure Machine Learning. Which tool allows you to generate insights such as feature importance and error analysis?
Correct answer: A
Explanation
The "azureml.interpret" package provides model interpretability tools used by the responsible AI dashboard to generate insights like feature importance. It supports explanation and analysis of model behavior, which is why it is used for "feature importance and error analysis" in Azure Machine Learning.
Why each option is right or wrong
A. azureml.interpret package
The responsible AI dashboard in Azure Machine Learning relies on the model interpretability APIs exposed by the azureml.interpret package to compute explanations that surface feature importance and related diagnostics. In practice, this package is the Azure ML wrapper around interpretability tooling used to generate global and local explanations for the dashboard, including error analysis views tied to model predictions.
B. mlflow.interpret()
C. azureml.automl.core.analyze_model()
D. azureml.core.ResponsibleAI