Errors in the function cross_validate in scikit-learn

Module 7. Evaluating model performance Regression metrics
#1

Excuse me, I have dificulties with the last question of the Quiz:
When errors are used in the function cross_validate in scikit-learn, one should:
, because the documentation of de cross_validate do not give me the information I need about the parameter scoring (possibilities). Could you please help me?

#2

The documentation of the scoring parameter refers as well to 3.3. Metrics and scoring: quantifying the quality of predictions — scikit-learn 0.24.2 documentation. It provides all details of the possibility of using an error as a metric instead of a score as a metric.

I just recall that an error means a lower value is better while a score means a higher value is better.

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