Measures of performance in machine learning
Precision and recall are the two basic measures and most of the other measures can be written in terms of them. If a model has both better precision and better recall, then it can be seen as strictly better than another model. If two models are incomparable in the sense that another has better precision and another has better recall, then it depends on the application which one is better. For some applications it is essential to avoid false positives, and for some applications it is essential to avoid false negatives.