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I'm using 10-fold cross validation on all models. Here you can see both plots:

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Since I am using k-fold cross validation, is it okay to name it "validation error vs training error" or "test error vs training error" would be better?

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The expression "validation error vs training error" is likely more appropriate because the data you use during cross validation that is not the training data is often considered the validation data.

The test data is the data you use to test your model after having performed e.g. cross-validation. The test dataset should be independent of both the training and validation datasets.

This is just a convention, and some people use the terms "validation data" and "test data" interchangeably, because, in a way, during cross-validation you are also "testing" (or, to disambiguate, "validating") the model.

See also this answer: https://stats.stackexchange.com/a/401702/82135.

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  • $\begingroup$ Thank you very much! I really appreciate it! $\endgroup$ – NaveganTeX May 16 at 0:52

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