Answer-first summary for fast verification
Answer: Yes
The solution meets the goal because run.log_list() is the appropriate Azure ML method to log a list of values as run metrics. The community discussion shows 100% consensus for answer A ('Yes'), with multiple upvoted comments confirming this is correct. While one comment questioned whether unique() returns a list (it typically returns a numpy array), in Azure ML context, run.log_list() can handle various iterable types including arrays, and the official Microsoft documentation supports using log_list for this purpose. The code will successfully record the unique label values as metrics that can be reviewed later in the experiment run.
Author: LeetQuiz Editorial Team
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You are using a Python script for an Azure Machine Learning experiment. The script references the experiment run context, loads data, identifies the unique values for the label column, and completes the run. You need to log these unique label values as run metrics for later review.
You add the following code at the indicated point to achieve this:
run.log_list('Label Values', label_vals)
run.log_list('Label Values', label_vals)
Does this solution meet the goal?
A
Yes
B
No
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