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Results +/- Error notation
Hi,
It's a bit a picky question but I wanted to make sure that I understood right.
In case of results of the binary classification performace operator, when crossvalidation is applied,
A result is for example denoted as AUC 0.569 +/- 0.074.
Are the errors noted after +/- the standard error or the 0.95-CI?
In a course I learned that both exists so thats why I am asking.
Best
Nora
0
Best Answer
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MartinLiebig Administrator, Moderator, Employee-RapidMiner, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 3,533 RM Data ScientistHi,it's 1sigma level, so 68.3% CL or something.Best,Martin- Sr. Director Data Solutions, Altair RapidMiner -
Dortmund, Germany1
Answers