Model Evaluation, Limits & Responsible Use: How It Works

Model evaluation asks whether a system performs well enough for its intended use, on data representative of deployment, with known uncertainty and failure modes.

Metrics summarize specific properties and therefore reward different behavior.

Confusion matrices, precision/recall, ROC or precision-recall curves, calibration plots, residual analysis, subgroup metrics, stress tests, drift measures, and real-world outcomes reveal distinct dimensions of system performance.