Intermediate · Evaluation
Area under the ROC curve
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. Area under the ROC curve (AUC) evaluates a classifier's ability to distinguish between classes across all possible thresholds.
Technical Definition
Area under the ROC curve (AUC) evaluates a classifier's ability to distinguish between classes across all possible thresholds.
How it works
The Area Under the Receiver Operating Characteristic Curve (AUC) is a performance measurement for classification models. It represents the degree or effectiveness of the model's ability to distinguish between classes. An AUC of 1 represents a perfect classifier, while an AUC of 0.5 represents a model with no discriminative ability.
Related Concepts
- Classification — A supervised learning task where the model assigns inputs to discrete categories.
- ROC Curve — A plot of true-positive rate against false-positive rate across all classification thresholds.
- AUC — Area Under the ROC Curve — a threshold-independent measure of classifier quality.
- Evaluation Metrics — Quantitative measures used to assess the performance, accuracy, and quality of AI models for specific tasks.