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RestockIQ v1: M5 quantile forecasting + reorder decision dashboard
- prepare_data: melt/merge/downcast 3 M5 CSVs into a 46.9M-row feature table
- baselines: seasonal-naive (WAPE 0.862) + Prophet on 12 sampled series
- 3 global LightGBM quantile models (P10/P50/P90), d_1000+ scope,
recursive 28-day forecast with P50 feedback (P50 WAPE 0.679, band coverage 80.6%)
- decision layer: z*std*sqrt(lead) safety stock from the quantile spread, 20 unit tests
- backtest: naive 15.52% stockout / 2.93 holding vs recommended 12.42% / 4.46
- FastAPI + Chart.js dashboard, Dockerfile for HF Space (port 7860)
