Databricks Certified Machine Learning - Associate
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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?
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?
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Explanation:
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.