Question

A data scientist is manually logging a scikit-learn model with MLflow and wants the Model Registry UI to display the expected input schema and a sample record so downstream consumers can understand how to call the model. Which addition to the mlflow.sklearn.log_model() call best accomplishes this?

Accepted Answer

Pass signature and input_example parameters, inferring the signature with mlflow.models.infer_signature() from the training features and predictions

Answer

Set the registered_model_name parameter so the schema is generated automatically during registration

Answer

Log the training DataFrame as a separate artifact using mlflow.log_artifact() alongside the model

Answer

Add the feature column names as tags on the run using mlflow.set_tags()