Designing and Implementing a Data Science Solution on Azure — Question 41

You plan to use automated machine learning to train a regression model. You have data that has features which have missing values, and categorical features with few distinct values.
You need to configure automated machine learning to automatically impute missing values and encode categorical features as part of the training task.
Which parameter and value pair should you use in the AutoMLConfig class?

Answer options

• A. featurization = 'auto'
• B. enable_voting_ensemble = True
• C. task = 'classification'
• D. exclude_nan_labels = True
• E. enable_tf = True

Correct answer: A

Explanation

The correct answer is A, as setting featurization to 'auto' allows the automated machine learning process to handle missing values and categorical feature encoding without additional configuration. The other options do not pertain to handling missing values or encoding; for instance, B relates to ensemble methods, C specifies a classification task instead of regression, D concerns label handling, and E is about enabling TensorFlow, which is not relevant to the stated requirements.