Walk the evaluation stack
Choose evaluation checks that match the intended synthetic data release.
The one-number report The synthetic loan dataset has a 94 percent similarity score, but the team has not named the use case, attacker, subgroup risk, or schema release checks. A single score can hide both privacy and utility failures. Evaluation stack Map -> Measure -> Manage Context decides which metrics matter; metrics decide which release controls are defensible. One score Looks similar The release claim matches the evidence. Evaluation starts with the claims recipients will make. 01 Map 02 Measure 03 Manage Decision 1 The dataset is for a public hackathon, not internal model validation.
Sign up free — one personalized lesson every day, matched to your role and goals.
Already have an account? Sign in