F1-score

In theory a good model (one that makes the right predictions) will be one that has both high precision, as well as high recall. In practice however, a model has to make compromises between both metrics. Thus, it can be hard to compare the performance between a model with high recall and low precision versus a model with low recall and high precision.

F1-score is a metric that summarizes both precision and recall in a single value, by calculating their harmonic mean, which allows it to be used to compare the performance across different models. It’s defined as: