In a nutshell:
What is the reason why people smooth ROC Curves?
When I plot a ROC Curve, the emperical data gives me always a parametric function which looks like stairs going up.
This is due to the fact that you either have:
- a non-continuous tests (e.g.: a medical test which can have 0 -10 full points) . So I could only calculate 10 differnt thresholds, because there are no values like "1.45" .
- even if the data is continuous, there is never a measurement for every value.
-> actually all ROC functions are parametric
During my research I found out that there are many different methods to smoothen the graphs (see Figure below). Apparently this is relevant in some cases, but unfortunately I could not find out why exactly?
Does anyone know why?
I want to do a ROCAUC analysis about a medical test with 0-7 full points.