New metric: LogAUC

CHANGELOG.md

@@ -15,6 +15,9 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Added `NormalizedRootMeanSquaredError` metric to regression subpackage ([#2442](https://github.com/Lightning-AI/torchmetrics/pull/2442))
 
 
+- Added `LogAUC` metric to classification package ([#2377](https://github.com/Lightning-AI/torchmetrics/pull/2377))
+
+
 - Added `NegativePredictiveValue` to classification metrics ([#2433](https://github.com/Lightning-AI/torchmetrics/pull/2433))
 
 

docs/source/classification/logauc.rst

@@ -0,0 +1,55 @@
+.. customcarditem::
+   :header: Log Area Receiver Operating Characteristic (LogAUC)
+   :image: https://pl-flash-data.s3.amazonaws.com/assets/thumbnails/tabular_classification.svg
+   :tags: Classification
+
+.. include:: ../links.rst
+
+#######
+Log AUC
+#######
+
+Module Interface
+________________
+
+.. autoclass:: torchmetrics.LogAUC
+    :exclude-members: update, compute
+    :special-members: __new__
+
+BinaryLogAUC
+^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.classification.BinaryLogAUC
+    :exclude-members: update, compute
+
+MulticlassLogAUC
+^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.classification.MulticlassLogAUC
+    :exclude-members: update, compute
+
+MultilabelLogAUC
+^^^^^^^^^^^^^^^^
+
+.. autoclass:: torchmetrics.classification.MultilabelLogAUC
+    :exclude-members: update, compute
+
+Functional Interface
+____________________
+
+.. autofunction:: torchmetrics.functional.logauc
+
+binary_logauc
+^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.classification.binary_logauc
+
+multiclass_logauc
+^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.classification.multiclass_logauc
+
+multilabel_logauc
+^^^^^^^^^^^^^^^^^
+
+.. autofunction:: torchmetrics.functional.classification.multilabel_logauc

docs/source/links.rst

@@ -177,4 +177,5 @@
 .. _Hausdorff Distance: https://en.wikipedia.org/wiki/Hausdorff_distance
 .. _averaging curve objects: https://scikit-learn.org/stable/auto_examples/model_selection/plot_roc.html
 .. _Procrustes Disparity: https://en.wikipedia.org/wiki/Procrustes_analysis
+.. _Log AUC: https://pubmed.ncbi.nlm.nih.gov/20735049/
 .. _Negative Predictive Value: https://en.wikipedia.org/wiki/Positive_and_negative_predictive_values

requirements/classification_test.txt

@@ -5,3 +5,4 @@ pandas >1.4.0, <=2.2.3
 netcal >1.0.0, <1.4.0 # calibration_error
 numpy <2.2.0
 fairlearn # group_fairness
+PyTDC ==0.4.1 # locauc

src/torchmetrics/__init__.py

@@ -61,6 +61,7 @@
     HammingDistance,
     HingeLoss,
     JaccardIndex,
+    LogAUC,
     MatthewsCorrCoef,
     NegativePredictiveValue,
     Precision,
@@ -189,6 +190,7 @@
     "JaccardIndex",
     "KLDivergence",
     "KendallRankCorrCoef",
+    "LogAUC",
     "LogCoshError",
     "MatchErrorRate",
     "MatthewsCorrCoef",

src/torchmetrics/classification/__init__.py

@@ -57,6 +57,7 @@
     MulticlassJaccardIndex,
     MultilabelJaccardIndex,
 )
+from torchmetrics.classification.logauc import BinaryLogAUC, LogAUC, MulticlassLogAUC, MultilabelLogAUC
 from torchmetrics.classification.matthews_corrcoef import (
     BinaryMatthewsCorrCoef,
     MatthewsCorrCoef,
@@ -223,6 +224,10 @@
     "MulticlassSensitivityAtSpecificity",
     "MultilabelSensitivityAtSpecificity",
     "SensitivityAtSpecificity",
+    "BinaryLogAUC",
+    "LogAUC",
+    "MulticlassLogAUC",
+    "MultilabelLogAUC",
     "BinaryNegativePredictiveValue",
     "MulticlassNegativePredictiveValue",
     "MultilabelNegativePredictiveValue",