Question

You are training a classification model in Azure Machine Learning using several experiment jobs, each logging accuracy, F1 score, and AUC through MLflow autologging. Your team lead asks you to identify which job produced the best-performing model and to visually compare the logged metrics side by side across all runs within the same experiment. Which approach should you use in the Azure Machine Learning studio?

Accepted Answer

Open the experiment, select multiple jobs, and use the Compare view to display their logged metrics and parameters together.

Answer

Register each job's model to the model registry and compare the version numbers in the Models page.

Answer

Download the outputs of each job individually and manually inspect the logged metric files.

Answer

Create a separate experiment for each job so that the studio automatically ranks them by accuracy.