Hello, I'm dealing with a problem without much data. As a solution, I'm training 10 estimators using a 10-Fold CV-Schema. Now, I wanted to persist those models. In order to avoid having to save 10 estimators, I was thinking about saving a single VotingRegressor with those pre-trained models or maybe writing a custom estimator to be used only for inference. Has anyone dealt with similar problems?
TLDR: Looking for an easy way to store multiple models created using cross-validation as a single model. More context: I'll be using mlflow sklearn autolog, so it will be waaay more convenient to log only a single model instead of multiple models in each experiment. Thanks!
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