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| Model | Output | Features |
|---|---|---|
| Cancel Probability | 0–1 | Lead time, order value, customer tier, fill feasibility |
| Supplier Delay | 0–1 | Urgency, order complexity, region risk |
| Production Lead Time | days | Quantity, production line load |
| Substitution Acceptance | 0–1 | Customer tier, substitutable line ratio |
| Metric | Value |
|---|---|
| Profit Uplift | +18.4% |
| Late Delivery Reduction | 32.1% |
| Order Fill Rate | 95.6% |
| Decision Regret | 0.082 |
| Cancel AUC | 0.847 |
| Delay AUC | 0.812 |
| Production MAE | 1.34 days |
| Substitution AUC | 0.789 |
1import json
2from pathlib import Path
3
4config = json.loads(Path("predictors.json").read_text())
5# Apply calibrated logistic regression coefficients at inference time