Answer-first summary for fast verification
Answer: You should make use of the featurization parameter with the 'auto' value pair.
The question requires ensuring automated machine learning handles missing value imputation and categorical feature encoding automatically. According to Azure ML documentation and the community consensus (94% selected A with upvoted comments), setting featurization to 'auto' enables AutoML to automatically perform preprocessing steps including imputing missing values and encoding categorical features. Option B ('off') would disable featurization entirely, preventing the required preprocessing. Option C ('on') is not a valid featurization parameter value in Azure AutoML. Option D (FeaturizationConfig) is for custom configurations, which is unnecessary here as the requirements can be met with automatic featurization.
Author: LeetQuiz Editorial Team
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You are preparing to train a regression model using automated machine learning. The dataset contains features with missing values and categorical features with a small number of distinct values.
You need to configure automated machine learning to meet the following requirements:
Which action should you take?
A
You should make use of the featurization parameter with the 'auto' value pair.
B
You should make use of the featurization parameter with the 'off' value pair.
C
You should make use of the featurization parameter with the 'on' value pair.
D
You should make use of the featurization parameter with the 'FeaturizationConfig' value pair.
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