Per ADR-0008: the v15 baseline reports MAPE but optimises MSE, which
under-weights tail rows. Switching to objective='mape' applies gradient
proportional to 1/|y| and lets the model focus where MAPE penalises.
Targets co2_emissions, space_heating_kwh, hot_water_kwh, and peui_raw
retain the default 'regression' objective (some rows have ~zero CO2 from
heavy PV; MAPE objective destabilises near zero).
Sample weights deferred to slice 16i if slice 16h's per-decile residuals
still show tail bias after the objective switch.
Adds `_per_decile_residuals` and writes `residuals_<target>.json` next to
metrics.json. Buckets test-set rows by deciles of the true target value;
each bucket carries count + MAPE + MAE + mean residual + true_min/max.
Lets us tell whether errors concentrate in the tails of the true distribution
(e.g. SAP<40 / SAP>85) vs the mid-band — which the global MAPE alone hides.
Baseline for slice 16's MAPE-improvement ablations.
Bulk entries are NDJSON of wrapper records, not a JSON array. Each wrapper
carries certificate_number, assessment_type, and a stringified document with
the actual EPC schema payload. Filter to RdSAP, unwrap document, then map.
remote_bulk_fetcher: per-entry presigned-URL refresh (30s S3 TTL).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
ijson use_float fixes Decimal/float coercion when streaming JSON.
pyright extraPaths so the new pkg type-checks against domna-domain.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
