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Library/ Machine Learning (Supervised + Unsupervised)/ Supervised Learning by Building/ S02 · Build: An Evaluation Harness (used for every model)

subtopic

Thresholds, costs and calibration

10 min applied10 min research2 curated resources

Choose the threshold by minimising cost on cross-validated predictions; check calibration with a reliability curve. Concepts: Decision threshold; cost curve; probability calibration; Brier score Project A: Expect the cost-optimal threshold well below 0.5 (≈ 0.2–0.35) because missing a Bad costs 5×. Project B: Not applicable (classification-only method).

Builds on: E01 · Build: Problem Framing Brief (one page per project), E13 · Build: Training-Ready Dataset Hand-off

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Thresholds, costs and calibration · 1x1labs.ai