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I am making a dual process. I have an initial dataset in which I train (fit) a model, then I do cross validation to get results. Until now everything normal, but additional to that, I create a new data set as a new test set. I know that if I do cross validation with this new data set, the training and testing is done all over again, but I want to know if after I do this cross validation, the model instance remains with the cross validation fit (over the new data set, which I do not want). I know that I could just change the order, first do c-v and then fit on the old data and test on the new data, but I want to be clear about how the model gets affected when I do cross validation.

Thanks

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