Hands-On Ensemble Learning with Python

Precision, recall, and the F1 score

Precision gauges how a model behaves by quantifying the percentage of instances correctly classified as a specific class, relative to all instances predicted as the same class. It is calculated as follows:

Recall is another name for sensitivity. The harmonic mean of precision and recall is called the F1 score and is calculated as follows:

The reason to use the harmonic mean instead of a simple average is that the harmonic mean is greatly affected by imbalances between the two values (precision and recall). ...