[ML] Precision / Recall

For classification problem

Precision:
    True positives                            True positives
------------------------   =   ---------------------------------------
#predicted positives         True positives + False positives

Recall:
    True positives                            True positives
------------------------   =   ---------------------------------------
  #actual positives            True positives + False negative


There is a tradeoff between precision and recall.
One way to compute the precision and recall is using F_1 score
                           precision * recall
F_1 score = 2 * -----------------------
                           precision + recall

Reference: https://www.coursera.org/learn/machine-learning/lecture/tKMWX/error-metrics-for-skewed-classes