Model/services/ml_training_data
Khalim Conn-Kowlessar 1c0cb9ac07 tooling: per-end-use PEUI decomposition in parity probe
Adds primary-energy breakdown (space heating, hot water, lighting,
pumps, PV) per cert plus stratified bias reports by main_heating_
category, construction_age_band, and dwelling_type. Used to localise
the +51 kWh/m² PEUI bias to envelope-side over-prediction on pre-1996
fabric, which the bare SAP-residual ranking didn't surface.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-05-18 20:14:39 +00:00
..
src/ml_training_data tooling: per-end-use PEUI decomposition in parity probe 2026-05-18 20:14:39 +00:00
tests slice 16i: MAE + RMSE in metrics; sample_weight_fn + low_sap_tail_weight 2026-05-17 14:48:00 +00:00
pyproject.toml slice 14g: remote_bulk_fetcher extracts ZIP entries via HTTP Range (no full download) 2026-05-16 19:16:52 +00:00