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Hi @cgnorthcutt,
this PR is intended to fix the incorrect behaviour highlighted within this issue wrt the handling of the best estimator and whose solution was somehow suggested in the issue itself. Indeed, it can be noticed that also
sklearn
cross-validation functions (see here) do clone the estimators before fitting (thus training a clone on each fold so as to make sure all folds are independent).Eventually, it still does not solve the problem arising whenever
parallelize
parameter is set to True (default).