more work on model training

todo.md

@@ -15,12 +15,12 @@ Priority key: `P0` = critical/blocking, `P1` = important, `P2` = later optimizat
 - [ ] [P1] Document known data issues and mitigation rules.
 
 ## 3) Dataset and Feature Engineering
-- [ ] [P1] Extract reusable dataset-builder logic from training script into a maintainable module/workflow.
-- [ ] [P1] Add lag/rolling features (means, stddev, deltas) for core sensor inputs.
-- [ ] [P1] Encode wind direction properly (cyclical encoding).
+- [x] [P1] Extract reusable dataset-builder logic from training script into a maintainable module/workflow.
+- [x] [P1] Add lag/rolling features (means, stddev, deltas) for core sensor inputs.
+- [x] [P1] Encode wind direction properly (cyclical encoding).
 - [ ] [P2] Add calendar features (hour-of-day, day-of-week, seasonality proxies).
-- [ ] [P1] Join aligned forecast features from `forecast_openmeteo_hourly` (precip prob, cloud cover, wind, pressure).
-- [ ] [P1] Persist versioned dataset snapshots for reproducibility.
+- [x] [P1] Join aligned forecast features from `forecast_openmeteo_hourly` (precip prob, cloud cover, wind, pressure).
+- [x] [P1] Persist versioned dataset snapshots for reproducibility.
 
 ## 4) Modeling and Validation
 - [x] [P0] Keep logistic regression as baseline.
@@ -53,5 +53,5 @@ Priority key: `P0` = critical/blocking, `P1` = important, `P2` = later optimizat
 ## 8) Immediate Next Steps (This Week)
 - [x] [P0] Run first full data audit and label-quality checks. (completed on runtime machine)
 - [x] [P0] Train baseline model on full available history and capture metrics. (completed on runtime machine)
-- [ ] [P1] Add one expanded feature set and rerun evaluation.
+- [ ] [P1] Add one expanded feature set and rerun evaluation. (feature-set plumbing implemented; rerun pending on runtime machine)
 - [x] [P0] Decide v1 threshold and define deployment interface.