fixed typo in comment
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Shaunak Joshi 2023-03-31 16:51:59 -04:00 committed by GitHub
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@ -57,7 +57,7 @@ class AUROCWithMWU(torchmetrics.Metric):
This AUROC implementation is well suited to (non-zero) low-CTR. In particular it will return This AUROC implementation is well suited to (non-zero) low-CTR. In particular it will return
the correct AUROC even if the predicted probabilities are all close to 0. the correct AUROC even if the predicted probabilities are all close to 0.
Currently only support binary classification. Currently only supports binary classification.
""" """
def __init__(self, label_threshold: float = 0.5, raise_missing_class: bool = False, **kwargs): def __init__(self, label_threshold: float = 0.5, raise_missing_class: bool = False, **kwargs):