title: What is 'mean' f1 score in machine learning?
body: <p>I know f1 score which uses precision and recall.
  But, what is 'mean' in mean f1 score?
  When we use it and how to calculate 'mean'?</p>
  
  <p>EDIT for explicitly explain my problem : 
  I know the f1 score is the harmonic mean of precision and recall.
  And when we calculate f1 score, multiple classification result are needed to calculate precision and recall.</p>
  
  <p>For example, if we have a data set consists of 1000 instances, we can get 1000 classification result. Then we put it into contingency table, so we can calculate f1 score.</p>
  
  <p>Now it is the point what i'm confused with 'mean' f1 score. We calculate f1 score from the contingency table, but what is 'mean'? Only I can calculate is f1 score, then what is 'mean' and how to calculate 'mean' f1 score?</p>