[ENH]: Warn when hyperparamater tuning is hapening and now explcit scoring is used for inner CV

[fraimondo]

Which feature do you want to include?

The default in scikit-learn's SearchCV is to use the learning algorithm's score function. E.g. SVM will use accuracy. This could be a problem if the data is imbalanced. It would be better to use balanced_accuracy.

To prevent this, ideally we should warn the user if:

1. Hyperparemeter tuning is happening
2. Scoring is implicit

Additionally, this should include an example

How do you imagine this integrated in julearn?

In the checks, if a SearchCV is used and the scoring is None

Do you have a sample code that implements this outside of julearn?

No response

Anything else to say?

No response