Precision  – True Positive / Total Positive
Recall  – True Positive / (True positive + False Negative)
F1- score – is the harmonic mean of precision and recall
Support – The support is the number of samples of the true response that lie in that class.
In other words precision tells you how good is your model at rejecting the wrong labels and recall tells you how good is your model at assigning correct labels to the true classes. To understand this better read this

  
      en.wikipedia.org
  
  
    

Sensitivity and specificity 8

Sensitivity and specificity are statistical measures of the performance of a binary classification test, also known in statistics as a classification function:
 Equivalently, in medical tests sensitivity is the extent to which actual positives are not overlooked (so false negatives are few), and specificity is the extent to which actual negatives are classified as such (so false positives are few). Thus a highly sensitive test rarely overlooks an actual positive (for example, showing "nothing bad...