title: What is the threshold in AUC (Area under curve)
body: <p>Assume a binary classifier (say a random forest) <code>rfc</code> and I want to calculate the AUC. I struggle to understand how the threshold are being used in the calculation. I understand that you make a plot of TPR/FPR for different thresholds. I also understand the threshold is used as a threshold for predicting class 1 (else class 0), but how does the AUC algorithm predict classes?</p>
  
  <p>Say using <code>sklearn.metrics.roc_auc_score</code> you pass <code>y_true</code> and <code>y_rfc</code> (being the true value and the predicted value), but I do not see how the thresholds come into play in the AUC score/plot.</p>
  
  <p>I have read different guides/tutorials for AUC, but all of their explanation regarding the threshold and how it is used is kinda vague.</p>
  
  <p>I have also had a look at <a href="https://stackoverflow.com/questions/50014078/how-does-sklearn-actually-calculate-auroc">How does sklearn actually calculate AUROC?</a> .</p>