title: Is it OK if the false positive rate in a ROC curve does not end in 1.0?
body: <p>I have the following ROC Curve:</p>
  
  <p><img src="https://i.imgur.com/QoTKl.png" alt="ROC Curve"></p>
  
  <p>And it does not end in 1.0 because my predictions include zeros, for example</p>
  
  <p>prediction = [0.9, 0.1, 0.8, 0.0]</p>
  
  <p>For the ROC Curve, I take the top-k predictions, first {0.9}, then {0.9, 0.8} etc. And if there are no values > 0 in the prediction anymore, the prediction does not change anymore with increasing k.</p>
  
  <p>So I can´t get a true negative value of zero, and since the false positive rate is fp/(fp+tn), the curve ends before it reaches 1.</p>
  
  <p>Now, should I artificially use the zeros for predictions as well, or is it OK if the curve just ends like that? It feels wrong to use the zeros as well. Or am I missing something?</p>