Microsoft Certified Azure Data Scientist Associate - DP-100
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You create an Azure Machine Learning workspace and are implementing hyperparameter tuning for a model training run from a notebook.
You must configure a Bandit termination policy with the following behavior:
If the primary metric (AUC) is 0.8 at the evaluation intervals, any run where the primary metric falls below 0.66 should be terminated.
Which Bandit termination policy configuration should you use?
You create an Azure Machine Learning workspace and are implementing hyperparameter tuning for a model training run from a notebook.
You must configure a Bandit termination policy with the following behavior: If the primary metric (AUC) is 0.8 at the evaluation intervals, any run where the primary metric falls below 0.66 should be terminated.
Which Bandit termination policy configuration should you use?
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