I am running classification model. with normal training-test split I can check model accuracy and F1 score using MulticlassClassificationEvaluator. How can I do this with CrossValidation approach? Afaik, you Fit entire sample data in CrossValidator as you don't want to leave out any observation from either testing or training. But by doing so I don't have anymore unseen data on which I can run finalized model on. So is there a way I can get Accuracy and F1 score of a best model resulted from cross validation? Or should I still split sample data in to training and test before running cross validation against only training data? so later I can test it against test data.
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