ROC analysis and perfcurve
4 次查看(过去 30 天)
显示 更早的评论
I am trying to perform ROC analysis. The function perfcurve is excellent. However, it assumes that larger values of score indicate stronger evidence for a positive state. This is exactly what you want to do if you are analysing the output of a classifier model.
In my case, I want to use raw data where smaller values indicate stronger evidence for a positive state. Reading through the documentation, I could not find a way to change the test direction for the perfcurve function.
Does anyone know if it is possible to do this? Or other similar functions that allow doing this?
0 个评论
回答(2 个)
Muge Karaman
2021-2-24
Hi Costanzo,
I have been having the same issue using perfcurve, and been manipulating the input by multiplying by -1. However, as you said, this is not ideal because the threshold values would then need to be manipulated in the same way if needed to be reported. Please update this post, if you have found a solution to this!
Thanks,
0 个评论
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Detection 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!