Hey team,
In RandomisedSearchCV or SuccessiveHalving, we can pass indexes in the fold
parameter, if we want to test the hyperparameters on specific folds.
Say I have a dataset of 12 rows, indexes 1 to 12, and I pass as fold to the
randomized search or SH the following folds:
[1,2] [9, 10, 11, 12]
[3, 10] [5,6,7,8]
[7, 11] [1,2,3,4]
It will use [1,2], [3,10] and [7,11] to train the model, and the second part
with the 4 rows as the test set.
My question is, when refit=True, what does it use to train the final model? X?
the sum of the training folds? the sum of the test folds? something else?
It's a follow up question to this reply on SO:
[https://stackoverflow.com/questions/79748461/how-to-pass-pre-computed-folds-to-successivehalving-in-sklearn](https://stackoverflow.com/questions/79748461/how-to-pass-pre-computed-folds-to-successivehalving-in-sklearn?noredirect=1#comment140703041_79748461)
Thanks a lot!
Best wishes,
Soledad Galli
https://www.trainindata.com/
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