Answer-first summary for fast verification
Answer: Bayesian sampling, Random sampling
The question requires selecting two sampling methods that can handle both continuous (learning_rate: 0.001 to 0.1) and discrete (batch_size: 16, 32, 64) hyperparameters without an early termination policy. Based on Azure ML documentation and community consensus (57% selected CD with upvoted comments): - C (Bayesian sampling) supports continuous and discrete parameters and does not require early termination policies. - D (Random sampling) supports both parameter types and can be used without early termination. - A (No sampling) is invalid as it would not sample from the defined ranges. - B (Grid sampling) only supports discrete parameters and cannot handle the continuous learning_rate range effectively without discretization, making it unsuitable as a complete solution.
Author: LeetQuiz Editorial Team
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You plan to use Azure Machine Learning's Hyperdrive to find the optimal hyperparameters for training a model. You need to test combinations of the following values without using an early termination policy:
learning_rate: any value between 0.001 and 0.1batch_size: 16, 32, or 64Which two sampling methods should you configure for the Hyperdrive experiment? Each correct answer presents a complete solution.
A
No sampling
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B
Grid sampling
C
Bayesian sampling
D
Random sampling