Machine Learning for Developers

Precision score, recall, and F-measure

Precision score is as follows:

Here, t_p is the number of true positives and f_p is the number of false positives. The precision is the ability of the classifier to not label as positive a sample that is negative. The best value is 1 and the worst value is 0.

Recall is as follows:

Here, t_p is the number of true positives and f_n is the number of false negatives. The recall can be described as the ability of the classifier to find all the positive samples. Its values range from 1 (optimum) to zero.

F measure ...