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DP-100 · Question #424

DP-100 Question #424: Real Exam Question with Answer & Explanation

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Question

You create an Azure Machine Learning workspace. You are implementing hyperparameter tuning for a model training from a notebook. You must configure a Bandit termination policy that provides the following outcome: If the value of the primary metric of AUC is 0.8 at the point of evaluation intervals, any run with the primary metric value below 0.66 will be terminated. You need to identify which Bandit termination policy configuration to use. What should you identify?

Options

  • ASet slack_amount to 0.2.
  • BSet slack_factor to 0.1.
  • CSet slack_factor to 0.2.
  • DSet slack_amount to 0.1.

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Topics

#Hyperparameter Tuning#Early Termination Policy#Azure Machine Learning#Bandit Policy
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