You run an automated machine learning experiment in an Azure Machine Learning workspace. Information about the run is listed in the table below: You need to write a script that uses the Azure Machine

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Exhibits

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• Afrom azureml.core import Workspace from azureml.train.automl import AutoMLRun ws = Workspace.from_config() automl_ex = ws.experiments.get('auto_ml_classification') best_iter = automl_ex.archived_time.find('11/11/2019 11:00:00 AM')
• Bfrom azureml.core import Workspace from azureml.train.automl import AutoMLRun ws = Workspace.from_config() automl_ex = ws.experiments.get('auto_ml_classification') automl_run = AutoMLRun(automl_ex, 'AutoML_1234567890-123') best_iter = automl_run.current_run
• Cfrom azureml.core import Workspace from azureml.train.automl import AutoMLRun ws = Workspace.from_config() automl_ex = ws.experiments.get('auto_ml_classification') best_iter = automl_ex.list_automl_ex.get_runs()[0]
• Dfrom azureml.core import Workspace from azureml.train.automl import AutoMLRun ws = Workspace.from_config() automl_ex = ws.experiments.get('auto_ml_classification') automl_run = AutoMLRun(automl_ex, 'AutoML_1234567890-123') best_iter = automl_run.get_output()[0]
• Efrom azureml.core import Workspace from azureml.train.automl import AutoMLRun ws = Workspace.from_config() automl_ex = ws.experiments.get('auto_ml_classification') best_iter = automl_ex.get_runs('AutoML_1234567890-123')

• A
  4% (1)
• B
  4% (1)
• D
  85% (23)
• E
  7% (2)

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. best_run, fitted_model = local_run.get_output() https://notebooks.azure.com/azureml/projects/azureml-getting-started/html/how-to-use- azureml/automated-machine-learning/classification-with-deployment/auto-ml-classification-with- deployment.ipynb

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