title: How does predict_proba work with cross-validation?
body: <p>When using 5-fold cross-validation to create a model, 5 different models are created. The selection of the final model can vary:</p>
  <ol>
  <li>best-estimated (or other criteria) model out of the 5-fold created model or</li>
  <li>the model create when trained on all the datasets.</li>
  </ol>
  <p>I understand that cross-validation is used for model checking, not for model building. So when a <code>predict_proba</code> is used on the model, how is this probability defined? Could you share some papers or articles that talk about how the prediction works on caret in R and in <code>sklearn</code> in Python with cross-validation?</p>