What is Area Under the ROC Curve (AUC) in Machine Learning?
Nestor Mayagma Jr.2025-07-01T02:38:28+00:00Area Under the ROC Curve (AUC) Cheat Sheet AUC, short for Area Under the Curve of the Receiver Operating Characteristic (ROC), is a metric that evaluates how well a model can differentiate between different classes. A performance metric primarily used for binary classification models. Ranges from 0 to 1: 1: Perfect model. 0.5: Model performs no better than random guessing. 0: Model inversely ranks positives and negatives. Accurate Outcomes True Positive (TP): The model predicted 1, which matches the actual result. True Negative (TN): The model predicted 0, and the real outcome was also 0. Misclassified Outcomes False Positive (FP): [...]









