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3095 Fix wrong doc-string of AUC metric #3096

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ericspod merged 6 commits into from
Oct 9, 2021
Merged

3095 Fix wrong doc-string of AUC metric #3096

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42a45e0
Merge pull request #19 from Project-MONAI/master
Nic-Ma Feb 1, 2021
cd16a13
Merge pull request #32 from Project-MONAI/master
Nic-Ma Feb 24, 2021
6f87afd
Merge pull request #180 from Project-MONAI/dev
Nic-Ma Jul 22, 2021
f398298
Merge pull request #214 from Project-MONAI/dev
Nic-Ma Sep 8, 2021
bd6a4ff
Merge pull request #240 from Project-MONAI/dev
Nic-Ma Oct 9, 2021
66f8c45
[DLMED] fix wrong doc-string
Nic-Ma Oct 9, 2021
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8 changes: 5 additions & 3 deletions monai/metrics/rocauc.py
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Expand Up @@ -104,9 +104,11 @@ def compute_roc_auc(

Args:
y_pred: input data to compute, typical classification model output.
it must be One-Hot format and first dim is batch, example shape: [16] or [16, 2].
y: ground truth to compute ROC AUC metric, the first dim is batch.
example shape: [16, 1] will be converted into [16, 2] (where `2` is inferred from `y_pred`).
the first dim must be batch, if multi-classes, it must be in One-Hot format.
for example: shape `[16]` or `[16, 1]` for a binary data, shape `[16, 2]` for 2 classes data.
y: ground truth to compute ROC AUC metric, the first dim must be batch.
if multi-classes, it must be in One-Hot format.
for example: shape `[16]` or `[16, 1]` for a binary data, shape `[16, 2]` for 2 classes data.
average: {``"macro"``, ``"weighted"``, ``"micro"``, ``"none"``}
Type of averaging performed if not binary classification.
Defaults to ``"macro"``.
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