Which of the following lines of code can be used to restore the model object so that feature_importances_ is available?

A data scientist has developed and logged a scikit-learn random forest model model, and then they ended their Spark session and terminated their cluster. After starting a new cluster, they want to review the feature_importances_ of the original model object.

Which of the following lines of code can be used to restore the model object so that feature_importances_ is available?
A . mlflow.load_model(model_uri)
B . client.list_artifacts(run_id)["feature-importances.csv"]
C . mlflow.sklearn.load_model(model_uri)
D . This can only be viewed in the MLflow Experiments UI
E . client.pyfunc.load_model(model_uri)

View Answer

Answer: A