A data scientist wants to add a custom metric — the geometric mean of precision and recall — to an mlflow.evaluate() call. How should they accomplish this?
extra_metrics parameter to mlflow.evaluate()mlflow.log_metric() inside the mlflow.evaluate() call as a callbackmlflow.evaluate() first, then manually add the metric via MlflowClient().log_metric()mlflow.models.EvaluationMetric and register it globally before calling mlflow.evaluate()More Model Development Questions
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