Module 3 · Building systems · Lesson 8
Evaluating Jev on your data
Building a labelled eval set from real decisions and measuring what matters for a decision model, accuracy, confusion, calibration, thresholds, consistency, latency and cost, then reading vendor benchmarks critically and testing for regressions when the model version changes.
By the end of this lesson you can
- Build a labelled, balanced eval set with a dev/test split and size it with a confidence interval
- Compute accuracy, a confusion matrix, ECE and the Brier score on your own data, and interpret a reliability table
- Choose a confidence threshold from a risk–coverage table on dev data and confirm it on test data
- Measure consistency under option reordering, paraphrase and repetition, and latency and cost per decision against an LLM baseline
- Identify the caveats in a vendor benchmark, and design a pinned-version regression check with a paired comparison