title: Macro VS Micro VS Weighted VS Samples F1 Score
body: <p>In sklearn.metrics.f1_score, the f1 score has a parameter called "average". What does macro, micro, weighted, and samples mean? Please elaborate, because in the documentation, it was not explained properly. Or simply answer the following:</p>
  
  <ol>
  <li>Why is "samples" best parameter for multilabel classification? </li>
  <li>Why is micro best for an imbalanced dataset? </li>
  <li>what's the difference between weighted and macro?</li>
  </ol>