Question: I am doing a elasticnet tuning parameter search on python and need the information about each of the cross validation folds. My dataset is verylarge

I am doing a elasticnet tuning parameter search on python and need the information about each of the cross validation folds. My dataset is verylarge and therefore I am using optuna.

When tuning the hyperparameters with optuna and using the optuna.integration.OptunaSearchCV function it has no avalaible attributes to see the results of each of the cross validation folds and therefore the tabular summary cannot be done. Using another technique like creating an objective function and then running the optuna study to minimize the error for example is computationaly impossible because it takes too much time since the objective function depends on a normal cross validation function like cross_validate.I have been stuck in this step for a couple of days. Would you maybe give me a hint on how to continue or what build-in function I can use?

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