Microsoft Certified Azure Data Scientist Associate - DP-100
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You are implementing hyperparameter tuning using Bayesian sampling for model training in an Azure Machine Learning notebook. The workspace uses a compute cluster with 20 nodes. The code uses a Bandit termination policy with a slack factor of 0.2 and a HyperDriveConfig instance with max_concurrent_runs set to 10.
To increase the effectiveness of the tuning process by improving sampling convergence, which sampling convergence method should you select?
A
Set the value of slack factor of early_termination_policy to 09.
B
Set the value of max_concurrent_runs of HyperDriveConfig to 4.
C
Set the value of slack factor of early_termination_policy to 0.1.
D
Set the value of max_concurrent_runs of HyperDriveConfig to 20.