Answer-first summary for fast verification
Answer: Yes
The correct answer is 'Yes' (A) because random sampling in Azure ML sweep jobs supports both requirements: it works with continuous hyperparameters (unlike grid search which only supports discrete values) and supports early termination policies like Bandit, Median Stopping, or Truncation Selection. The community discussion shows strong consensus for A (71% of votes), with multiple comments citing Microsoft documentation confirming that random sampling supports both discrete and continuous hyperparameters and early termination of low-performance jobs. While some initial comments suggested Bandit policy, they were corrected with proper documentation references showing random sampling meets both criteria.
Author: LeetQuiz Editorial Team
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You plan to tune model hyperparameters using an Azure Machine Learning sweep job. You need to select a sampling method that supports both early termination for low-performance runs and the use of continuous hyperparameters.
Proposed solution: Use the random sampling method over the hyperparameter space.
Does this solution meet the goal?
A
Yes
B
No