ROC-AUC

ROC-AUC, or Receiver Operating Characteristic Area Under the Curve, is a performance measurement for classification problems at various threshold settings. ROC is a probability curve that plots the True Positive Rate (TPR) against the False Positive Rate (FPR) at different threshold values. AUC measures the entire two-dimensional area underneath the entire ROC curve from (0,0) to (1,1). AUC provides an aggregate measure of performance across all possible classification thresholds.

Visit the following resources to learn more:

• @article@ROC-AUC score | scikit-learn
• @article@AUC and the ROC Curve in Machine Learning
• @article@Classification: ROC and AUC