If I understood correctly, PR Curve it's just the mean of F1 score computed multiple times with different thresholds.
In the task of outlier detection those are two suggested metrics given the fact that the datasets are highly inbalanced.
My question is, if I know in advance the contamination factor (the percetange of the anomalies) of a dataset, should I use directly the F1 Score instead of the PR Curve?
If I were to give my self an answer, I would say yes because knowing the contamination factor gives me the right threshold value and so it's useless to compute the PR Curve.
Does it make sense or am I wrong?
