Is there a way to project the F1-score on the precision-recall curve for a such binary classifier? Is there a relationship between the area under the precision-recall curve and F1-score?
Mathematically, I know that F1-score is the double of the multiplication of recall and precision divided by the summation of recall and precision. But I need to know if there is a clear representation of F1-score on the precision-recall curve?