
Answer-first summary for fast verification
Answer: metrics = runs[0].data.metrics
In Databricks MLflow, to access the metrics of the most recent run retrieved from an experiment, you should use `runs[0].data.metrics`. This method returns a dictionary containing the metric keys and their respective values. For example, the run data might include metrics like `{'r2': 0.47510865824355775, 'rmse': 129.3982828726223}`, among other details such as parameters and tags associated with the run.
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After retrieving the most recent run from an experiment in Databricks MLflow using the MLflow client with the command runs = client.search_runs(experiment_id, order_by=["attributes.start_time desc"], max_results=1), how can you access the metrics of this run?
A
metrics = runs[0].fetch_metrics()
B
metrics = runs[0].get_metrics()
C
metrics = runs[0].data.metrics
D
metrics = runs[0].fetch_metrics()
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