Retrieve explanation from client on Azure

retrieve_explanation.py

from azureml.interpret import ExplanationClient

# Get model explanation data
client = ExplanationClient.from_run(run)
global_explanation = client.download_model_explanation()
local_importance_values = global_explanation.local_importance_values
expected_values = global_explanation.expected_values

# Or you can use the saved run.id to retrive the feature importance values
client = ExplanationClient.from_run_id(ws, experiment_name, run.id)
global_explanation = client.download_model_explanation()
local_importance_values = global_explanation.local_importance_values
expected_values = global_explanation.expected_values

# Get the top k (e.g., 4) most important features with their importance values
global_explanation_topk = client.download_model_explanation(top_k=4)
global_importance_values = global_explanation_topk.get_ranked_global_values()
global_importance_names = global_explanation_topk.get_ranked_global_names()