### Reading

Precision, recall, sensitivity, specificity Wikipedia page on precision and recall Scikit learn on classification metrics Receiver Operating Characteristic Area under curve (ROC)

### what is the relationship between F1 and Fß?

If you have found the metrics function in `sklearn`

that spits out your precision, recall, and F score, you might have found yourself asking: "What is Fß? Is it the same as F1?"

The answer is ... yes. F1 combines precision and recall. Fß does the same thing, but uses a weight so that you can weigh one of these two (precision or recall) more than the other when combining them. It is a way to tune your score if you care more about precision than recall, for example. F1 is the Fß for which ß = 1. In `sklearn`

, the default value for ß is 1.

Here is a screen cap from the wikipedia page describing this relationship: