You create a binary classification model. The model is registered in an Azure Machine Learning workspace. You use the Azure Machine Learning Fairness SDK to assess the model fairness. You develop a tr

Question

Options

• AImplement the download_dashboard_by_upload_id function
• BImplement the function
• CImplement the upload_dashboard_dictionary function
• DUpload the training script

• A
  9% (2)
• B
  5% (1)
• C
  82% (18)
• D
  5% (1)

Explanation

You should implement the upload_dashboard_dictionary function from the azureml.contrib.fairness package. When model fairness metrics are computed locally using the Fairlearn SDK, the results are stored as a dashboard dictionary object. The upload_dashboard_dictionary() function serializes this dictionary and uploads it to the Azure ML workspace, making the fairness metrics visible in Azure ML Studio's Fairness dashboard. The download_dashboard_by_upload_id function (A) retrieves an already-uploaded dashboard rather than uploading new data. Uploading just the training script (D) does not transfer the computed fairness metrics to Studio.

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