title: Does GridSearchCV use predict or predict_proba, when using auc_score as score function?
body: <p>Does GridSearchCV use predict or predict_proba, when using auc_score as score function?</p>
  
  <p>The predict function generates predicted class labels, which will always result in a triangular ROC-curve. A more curved ROC-curve is obtained using the predicted class probabilities. The latter one is, as far as I know, more accurate. If so, the area under the 'curved' ROC-curve is probably best to measure classification performance within the grid search. </p>
  
  <p>Therefore I am curious if either the class labels or class probabilities are used for the grid search, when using the area under the ROC-curve as performance measure. I tried to find the answer in the code, but could not figure it out. Does anyone here know the answer?</p>
  
  <p>Thanks</p>