Answers.Body: <p>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.</p>
  
  <p>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.</p>
  
  <p>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.</p>
  
  <p>See also this answer: <a href="https://stats.stackexchange.com/a/401702/82135">https://stats.stackexchange.com/a/401702/82135</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2019-05-16T00:50:33.237Z
Answers.LastActivityDate: 2019-05-16T00:50:33.237Z
Answers.UserDisplayName: nbro
Body: <p>I'm using 10-fold cross validation on all models. Here you can see both plots:</p>
  
  <p><a href="https://i.sstatic.net/Q4kwH.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/Q4kwH.png" alt="enter image description here"></a></p>
  
  <p><a href="https://i.sstatic.net/5pMek.png" rel="nofollow noreferrer"><img src="https://i.sstatic.net/5pMek.png" alt="enter image description here"></a></p>
  
  <p>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? </p>
  
Tags: <machine-learning><terminology><overfitting><cross-validation>
Title: Should I call the error "validation error" or "test error" during cross validation?
UserDisplayName: NaveganTeX
ThreadText: # Should I call the error "validation error" or "test error" during cross validation?
  
  (Asked by: username_0 on 2019-05-16)
  
  I'm using 10-fold cross validation on all models. Here you can see both plots:
  
  [![enter image description here](https://i.sstatic.net/Q4kwH.png)](https://i.sstatic.net/Q4kwH.png)
  
  [![enter image description here](https://i.sstatic.net/5pMek.png)](https://i.sstatic.net/5pMek.png)
  
  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?
  
  **Tags:** machine-learning, terminology, overfitting, cross-validation
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2019-05-16. Score: 1 | Accepted answer
  
  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>.
  
  
  ---
  
  