title: How to use k-fold cross validation in a neural network
body: <p>We are writing a small ANN which is supposed to categorize 7000 products into 7 classes based on 10 input variables.</p>
  
  <p>In order to do this we have to use k-fold cross validation but we are kind of confused.</p>
  
  <p>We have this excerpt from the presentation slide:</p>
  
  <p><a href="https://i.stack.imgur.com/aDaSc.png" rel="noreferrer"><img src="https://i.stack.imgur.com/aDaSc.png" alt="k-fold cross validation diagram"></a></p>
  
  <p><strong>What are exactly the validation and test sets?</strong> </p>
  
  <p>From what we understand is that we run through the 3 training sets and adjust the weights (single epoch). Then what do we do with the validation? Because from what I understand is that the test set is used to get the error of the network.</p>
  
  <p>What happens next is also confusing to me. When does the crossover take place?</p>
  
  <p>If it's not too much to ask, a bullet list of step would be appreciated</p>