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Question 335

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

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You have an Azure Machine Learning workspace.

You plan to tune model hyperparameters by using a sweep job.

You need to find a sampling method that supports early termination of low-performance jobs and continuous hyperparameters.

Solution: Use the grid sampling method over the hyperparameter space.

Does the solution meet the goal?

    Correct Answer: B

    The grid sampling method is not suitable for the given scenario because it supports only discrete hyperparameters and not continuous hyperparameters. Additionally, while grid sampling supports early termination, it does not meet the requirement of supporting continuous hyperparameters. Therefore, the solution does not meet the goal.

Discussion
0ea0482Option: A

It should be yes. Random and Grid sampling methods support early termination.

VeraKoOption: B

The answer is No, because grid search supports early termination but does not support continuous hyperparameters. It supports only discrete ones https://learn.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters?view=azureml-api-2