Which Python code segment should you use?

Last Updated on October 21, 2021 by Admin

You run an automated machine learning experiment in an Azure Machine Learning workspace. Information about the run is listed in the table below:

DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 102

DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 102

You need to write a script that uses the Azure Machine Learning SDK to retrieve the best iteration of the experiment run.

Which Python code segment should you use?

  • DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 103

    DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 103

  • DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 104

    DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 104

  • DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 105

    DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 105

  • DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 106

    DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 106

  • DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 107

    DP-100 Designing and Implementing a Data Science Solution on Azure Part 06 Q06 107

Explanation:

The get_output method on automl_classifier returns the best run and the fitted model for the last invocation. Overloads on get_output allow you to retrieve the best run and fitted model for any logged metric or for a particular iteration.

In [ ]:
best_run, fitted_model = local_run.get_output()

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