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Two production fixes surfaced by the live run: - mapper.from_rdsap_schema_21_0_1 now sets the three ML target scalars (energy_rating_current, co2_emissions_current, energy_consumption_current). They were silently None for every cert before, leaving the only labels as the kWh fields from renewable_heat_incentive. - train_baseline coerces object-dtype columns to numeric (None -> NaN) and drops rows with null target per fit, so LightGBM accepts the frame. E2E on 500 real certs (~1s): sap_score R^2=0.604 MAPE=0.084 co2_emissions R^2=0.813 MAPE=0.130 peui_raw R^2=0.979 MAPE=0.026 space_heating_kwh R^2=0.823 MAPE=0.213 hot_water_kwh R^2=0.519 MAPE=0.115 peui_ucl excluded: UCL correction still needs wiring. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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| .. | ||
| epc | ||
| magicplan | ||
| __init__.py | ||
| datatypes.py | ||
| enums.py | ||