DP-100 · Question #343
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The correct answer is B. No. To find a hyperparameter sampling method that supports early termination of low-performance jobs and continuous hyperparameters in Azure Machine Learning, Sobol sampling is not suitable.
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- AYes
- BNo
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(19 responses)- A21% (4)
- B79% (15)
Why each option
To find a hyperparameter sampling method that supports early termination of low-performance jobs and continuous hyperparameters in Azure Machine Learning, Sobol sampling is not suitable.
Sobol sampling, while effective for continuous hyperparameters, does not support early termination of runs based on performance metrics.
Sobol sampling is a quasi-random sampling method primarily used for exploring the hyperparameter space efficiently. It does not inherently support early termination of low-performance runs, which is a feature of adaptive sampling methods like Bayesian or bandit policies applied to other sampling methods.
Concept tested: Azure ML hyperparameter sweep sampling methods
Source: https://learn.microsoft.com/en-us/azure/machine-learning/how-to-tune-hyperparameters?view=azureml-api-2&tabs=cli
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