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. |
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|---|---|---|
| .. | ||
| ara | ||
| ml_training_data | ||
| README.md | ||
Services
Each subdirectory is a deployable unit — typically a Lambda image. Own pyproject.toml, own Dockerfile, own deps. Lambda bundle contains only that service's deps + its workspace deps.
| Service | Purpose |
|---|---|
ara/ |
The Domna retrofit modelling backend — ingestion + modelling pipelines, all 9 services in PRD §9.2. |
Other Domna services (address2uprn, hubspot, pashub, ecmk, magicplan) live in the legacy backend/ and etl/ trees for now; they are slated to migrate here as their owners pick them up — see PRD §11. When that work starts, scaffold the service under services/<name>/ and add it to the workspace members in the root pyproject.toml.
Service boundary
A service can import domain.*, import repos.*, import fetchers.*, import utils.* (workspace deps). It cannot import another service's modules — they are separate distributions with no cross-import path. This is the structural enforcement of the modelling/ingestion separation (ADR-0003).