F1 score, PR or ROC curve for regression Due to my background as a pure biologist, I've been struggling with the comment acquired from a reviewer about the accuracy test used in my regression study. While I stick to MSE, MAE and R2 as the parameters to determine accuracy of my regression model (Support Vector Regression and Simple Linear Regression), one reviewer asks me to perform F1 score, PR or ROC curve with the data.
The reviewer has noted that "F1 score, PR or ROC curve are not specific to classification models only." With my limited knowledge, I cannot find any evidences of applying such parameters with regression study.
It would be very kind of you if anyone could provide me the source of such application. Either R or python packages for applying such test with regression study would be really appreciated.
Best regards,
Kaj
 A: 
F1 score, PR or ROC curve are not specific to classification models only.

I have never seen the F1 score or ROC used to evaluate a numerical prediction. I am unfamiliar with "PR".
The definition of the F1 score crucially relies on precision and recall, or positive/negative predictive value, and I do not see how it can reasonably be generalized to a numerical forecast.
The ROC curve plots the true positive rate against the false positive rate as a threshold varies. Again, it relies on a notion of "true positive" and "false positive", and I don't see how these can be applied to numerical predictions.
All that is not to say that efforts have not been made to apply these concepts to numerical forecasts.
It would feel a lot like hammering square pegs into round holes to me, though. I would say that there is a reason why I (we?) haven't seen this a lot: it's unintuitive, and it does not provide the information that standard error measures like the MAE or the MSE do. Honestly, if I got a paper for review that used F1/ROC to evaluate numerical predictions, I would recommend that they throw these out and use more standard error measures.
My recommendation: ask the editor to communicate to the reviewer that you need more information on applying F1 and ROC in your case. Maybe the reviewer can provide a reference or two? You may want to provide a link to this CV thread as an indication that you did do your homework and asked statistical experts (cough), and that the experts were similarly bewildered.
The best possible outcome would be if your reviewer posted their thoughts here.
