Nov. 16, 2023, 8:36 a.m. | /u/Tigmib

Machine Learning

Often when I read ML papers the authors compare their results against a benchmark (e.g. using RMSE, accuracy, ...) and say "our results improved with our new method by X%". Nobody makes a significance test if the new method Y outperforms benchmark Z. Is there a reason why?
Especially when you break your results down e.g. to the anaylsis of certain classes in object classification this seems important for me. Or do I overlook something?

accuracy authors benchmark machinelearning reason significance statistical test

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