I'm looking at the results of an ML model I made and I've calculated the PPV, TPR, NPV and TNR. As is expected, there is a tradeoff between the PPV and TPR (from which the F1 score can be calculated) but I was wondering if a similar relationship exists between NPV and TNR, as I have observed that in my results - if so, is there a similar metric to the F1 score for these measurements?
Edit: is it even necessary to look at the NPV and TNR? Wikipedia (I know, not a great source) says that a perfect precision eliminates false positives and a perfect recall eliminates false negatives, so what does knowing the NPV and TNR bring to the table? Because surely a perfect NPV eliminates false negatives and a perfect TNR eliminates false positives, so they don't really add any insight into the model.