I'm not big on statistics, so please excuse my ignorance.
I have a video recording that I want to evaluate, I have an algorithm that can transform this video into a time series where I have 0 everywhere except for a couple of frames where an event (A) occurs.
Then I have manual annotations of another event (B) that I think is related to the 1st event (A) (i.e. event B appears shortly after event A).
I want to construct a confusion matrix like this:
- Event A is condition, event B is "test"
- True positive value is when there is an event A and within 50 frames there is also event B
- False positive is when A is not present, but B is
- False negative is when A is present, but B is not
Now my problem is about True Negatives. If you do vaccine testing, you have a total number of tests, and you can quantify True Negatives without issue. But what about my case? I either have event A or B but True Negative is by definition everything else in the time series?
Does it make sense to even use confusion matrix?