From 66f8c4519b87375c5283f0a219eebe0627d154e9 Mon Sep 17 00:00:00 2001 From: Nic Ma Date: Sat, 9 Oct 2021 23:06:55 +0800 Subject: [PATCH] [DLMED] fix wrong doc-string Signed-off-by: Nic Ma --- monai/metrics/rocauc.py | 8 +++++--- 1 file changed, 5 insertions(+), 3 deletions(-) diff --git a/monai/metrics/rocauc.py b/monai/metrics/rocauc.py index c2679cc2ea..d331f01707 100644 --- a/monai/metrics/rocauc.py +++ b/monai/metrics/rocauc.py @@ -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"``.