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Author SHA1 Message Date
Khalim Conn-Kowlessar
7ca1f815f6 refactor(epc-prediction): PR review — rename ComparableProperty, relocate PredictionTarget
Two review points from @dancafc:

1) Rename the `Comparable` dataclass → `ComparableProperty` (it models one
   comparable *property*; the collection stays `ComparableProperties`). Applied
   across domain, repositories, orchestration, harness, scripts, and tests with a
   word-boundary rename so `ComparableProperties` is untouched.

2) Move `PredictionTarget` out of comparable_properties.py into prediction_target.py
   (where `PredictionTargetAttributes` + `build_prediction_target` already live).
   comparable_properties.py now imports it; no import cycle (prediction_target no
   longer depends on comparable_properties). Importers updated.

92 tests pass across the touched suites; pyright strict clean.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-16 13:34:44 +00:00
Khalim Conn-Kowlessar
fdc314c857 feat(epc-prediction): thread coordinates onto Comparable + target (#1227)
Adds coordinates: Optional[Coordinates] to Comparable and PredictionTarget
(data carriers — the pure predictor stays IO-free), and wires load_corpus to
read an optional _coordinates.json sidecar ({uprn: [lon, lat]}) and populate
each Comparable from its cert's uprn; iter_predictions threads the held-out
target's coordinates through. Absent sidecar -> geo-weighting stays off (no
behaviour change yet — weighting lands next slice). fetch_corpus_coordinates
now writes the sidecar into the corpus dir. load_corpus populates 99% of
corpus comparables.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-15 14:46:01 +00:00
Khalim Conn-Kowlessar
027ee1fba3 refactor(epc-prediction): extract shared leave-one-out scorer + corpus loader (ADR-0030)
"One scorer, two harnesses" (ADR-0030): the committed gate, the local script,
and the future battle-test must run the *same* scoring. Extract it:

- domain/epc_prediction/validation.py — `iter_predictions` (the single
  leave-one-out orchestration: latest-per-address hold-out, SAP-10.2 target
  filter, all-vintage source) + `evaluate_component_accuracy` (calculator-free
  ComponentAccuracy aggregation, the primary signal). Unit-tested.
- harness/epc_prediction_corpus.py — `load_corpus(dir)` IO: corpus dir ->
  Comparable cohorts (maps payloads, carries address + registration_date).

validate_epc_prediction.py now just loads + calls the scorer for the component
section and iterates iter_predictions for the calculator-floored end-to-end.
Identical numbers (181 targets, SAP MAE 6.34) — behaviour-preserving.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 09:12:08 +00:00