from sklearn.preprocessing import OrdinalEncoder enc = OrdinalEncoder(handle_unknown=’use_encoded_value’, unknown_value=-1) enc.fit(X_train) enc.transform(X_test) What is the result of this configuration when encountering an unseen category in the test set?

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from sklearn.preprocessing import OrdinalEncoder enc = OrdinalEncoder(handle_unknown=’use_encoded_value’, unknown_value=-1) enc.fit(X_train) enc.transform(X_test) What is the result of this configuration when encountering an unseen category in the test set?

Key points

  • Default OrdinalEncoder behavior raises an error on unknown labels.
  • handle_unknown='use_encoded_value' allows custom mapping.
  • This is critical for robust production pipelines.

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