Databricks Certified Machine Learning - Associate
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A data scientist is using MLflow Autologging to automatically monitor their machine learning experiments. After completing a series of experiment runs for a specific experiment_id, they aim to identify the run with the best root-mean-square error (RMSE). The following incomplete code snippet is initiated: mlflow._________(experiment_id, order_by = ["metrics.rmse"]) ["run_id"] [0]. What code should fill the blank to correctly complete this snippet and find the run with the best RMSE? Choose the ONE best answer.
Explanation:
The correct choice is search_runs. MLflow provides the search_runs function to query and sort experiment runs based on specified criteria like metrics, parameters, and tags. To find the run with the best RMSE, the data scientist should sort the runs by the RMSE metric in ascending order (assuming lower RMSE is better). The search_runs function allows filtering and ordering runs within an experiment, and selecting the first run's ID from the sorted list identifies the run with the best RMSE. The complete code snippet would be: mlflow.search_runs(experiment_id, order_by=["metrics.rmse ASC"])["run_id"][0]. The ASC specifies ascending order, which is the default but is often explicitly stated for clarity. Options A, C, D, and E do not correctly query and sort experiment runs based on a metric in MLflow's API.