Hi, the best way to get this fixed is to send us a PR updating this file:
https://github.com/scikit-learn/scikit-learn/blob/master/doc/modules/model_evaluation.rst thanks for your help Alex On Sun, Aug 30, 2020 at 7:38 AM 최우정 <cwjbria...@gmail.com> wrote: > > To whom it may concern > > I am a good user of scikit-learn. First of all, I am grateful to scikit-learn > for providing a good service. The reason I write an email is to report some > typos. > > While studying about AUC, I think I found some typos in API documentation. As > it is written in > "https://scikit-learn.org/stable/modules/model_evaluation.html#roc-metrics"; > One-vs-one Algorithm, the multiclass macro AUC metric was defined in the > reference [HT2001]. But there is a double difference in macro ovo AUC between > the reference and documentation. Furthermore, under the macro AUC, there is > weighted AUC which is defined in the reference [FC2009] as it is written in > documentation. But there is no same metric in the documentation in the > reference however there is a similar one, AU1P. After reviewing the code > which includes the definition of roc_auc_score, I notice that it is different > from both of the expressions in the documentation and the reference. > Additionally, my scikit-learn version is 0.23.1. I hope this part will be > fixed well. Thank you for reading my email. > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn _______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
