Turn Model Metrics Into a Decision

Rhea needs to turn classifier metrics into a release recommendation. Before: metrics are accurate but not decision-ready. After: the tradeoff is translated into release guidance. Metric names -> error types: precision and recall became false alerts and missed risky transactions. Scores -> stakes: the rewrite names which error costs more for this workflow. Observation -> recommendation: the message ends with a limited-release decision, not a pile of numbers. Model metrics need a ladder: score, error, stake, decision. Metric translation Turned abstract ML scores into a decision recommendation. For any metric, ask: what real-world mistake does this number represent?

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