AI Glossary

Model Evaluation

Coverage in development

Model evaluation measures predictive quality, robustness, and fitness for purpose using held-out data, metrics, and sometimes human review.

Definition

Model evaluation measures predictive quality, robustness, and fitness for purpose using held-out data, metrics, and sometimes human review.

You check whether the model actually works on data it has not memorized—and whether the metric matches the real goal.

Cross-Validation Benchmark

2026-07-13

NIST AI Risk Management Framework — risk vocabulary context for AI systems
Brel Digital company and technology profiles — applied usage evidence where tagged

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