HOTSPOT
You write code to retrieve an experiment that is run from your Azure Machine Learning workspace.
The run used the model interpretation support in Azure Machine Learning to generate and upload a model explanation.
Business managers in your organization want to see the importance of the features in the model.
You need to print out the model features and their relative importance in an output that looks similar to the following.
How should you complete the code? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.
Answer: 
Explanation:
Box 1: from_run_id
from_run_id(workspace, experiment_name, run_id) Create the client with factory method given a run ID.
Returns an instance of the ExplanationClient.
Parameters
✑ Workspace Workspace An object that represents a workspace.
✑ experiment_name str The name of an experiment.
✑ run_id str A GUID that represents a run.
Box 2: list_model_explanations
list_model_explanations returns a dictionary of metadata for all model explanations available.
Returns
A dictionary of explanation metadata such as id, data type, explanation method, model type, and upload time, sorted by upload time
Box 3: explanation
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