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MLS-C01 · Question #367

A tourism company uses a machine learning (ML) model to make recommendations to customers. The company uses an Amazon SageMaker environment and set hyperparameter tuning completion criteria to MaxNumb

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ML Implementation and Operations

Question

A tourism company uses a machine learning (ML) model to make recommendations to customers. The company uses an Amazon SageMaker environment and set hyperparameter tuning completion criteria to MaxNumberOfTrainingJobs. An ML specialist wants to change the hyperparameter tuning completion criteria. The ML specialist wants to stop tuning immediately after an internal algorithm determines that tuning job is unlikely to improve more than 1% over the objective metric from the best training job. Which completion criteria will meet this requirement?

Options

  • AMaxRuntimeInSeconds
  • BTargetObjectiveMetricValue
  • CCompleteOnConvergence
  • DMaxNumberOfTrainingJobsNotImproving

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Topics

#Hyperparameter Tuning#SageMaker#Completion Criteria#Early Stopping
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