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Intermediate · Evaluation

AUC

Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.

TL;DR. Area Under the ROC Curve — a threshold-independent measure of classifier quality.

Technical Definition

Area Under the ROC Curve — a threshold-independent measure of classifier quality.

How it works

AUC ranges from 0.5 (random) to 1.0 (perfect) and equals the probability that a random positive example scores higher than a random negative one. Useful for comparing models, less useful for picking an operating point in production.

Related Concepts

  • Precision & Recall — Complementary metrics measuring classifier accuracy on positive predictions (precision) and ability to find all positives (recall).
  • Accuracy — The fraction of predictions a model gets correct on a labeled dataset.
  • ROC Curve — A plot of true-positive rate against false-positive rate across all classification thresholds.