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🚀 Feature
Create the metric MulticlassAUROC to allow for the AUROC metric to be used in multi-class problem settings. Or,
Expand the AUROC metric to support multi-class data, which would also directly solve this AUROC bug that instead gives a random value when used in multi-class problems: https://github.com/PyTorchLightning/
这里的路由和server通信是否可以用一个长连接来维护更好
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Describe the issue linked to the documentation
Follows from #17387
Suggest a potential alternative/fix
Stop referencing preprocessing functions e.g. :
maxabs_scale
minmax_scale
normalize
quantile_transform
robust_scale
scale
power_transform
in the UG, and only add them e.g. in the "See Also" sections, or even just in the API ref.
In particular right now the first entr
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TestQuality
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Add quickselect algorithm. Quickselect is a selection algorithm to find the kth smallest element in an unordered list.