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As discussed in #13 (comment) audmetric should handle NaN the same way in all its functions. There are basically two options:
audmetric
NaN
The text was updated successfully, but these errors were encountered:
Related to https://gitlab.audeering.com/tools/audbenchmark/-/issues/104
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Basically there is also the problem when we have class labels in prediction that are not present in truth.
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As discussed in #13 (comment)
audmetric
should handleNaN
the same way in all its functions. There are basically two options:NaN
is detectedNaN
in the calculations, e.g. tread them as wrong labelThe text was updated successfully, but these errors were encountered: