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Author SHA1 Message Date
Khalim Conn-Kowlessar
718455e971 feat(epc-prediction): physical-similarity-weighted categorical mode (#1224)
ADR-0029 decision 5: survivors were treated equally; now each neighbour's
vote in the cohort mode decays with its distance from the cohort's physical
centre (floor area from the median, age band from the modal band), so the
mode leans on the most representative neighbours instead of being swayed by
size/era outliers. Scales (size 20 m^2, age weight 0.5) chosen on the
validation corpus; the tight size kernel is load-bearing (looser scales
regress floor_insulation on the fixture).

Corpus (181 SAP-10.2 targets): wall_insulation 83.4->86.2%,
roof_construction 86.2->87.3%, floor_construction 78.8->81.2%,
floor_insulation 92.9->94.1%; net +7.5pp gained vs -1.1pp (two 1-cert dips,
both held on the fixture). Geometry/residuals untouched (template unchanged).

Gate (36-target fixture): zero regression across all 24 floors/ceilings;
ratcheted wall_insulation_type 0.7778->0.8333, floor_construction
0.7500->0.8125, floor_insulation 0.9062->0.9375. Dead _mode/_int_mode
removed (superseded by the weighted variants).

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 10:46:51 +00:00
Khalim Conn-Kowlessar
ffaedd8d14 feat(epc-prediction): ±1-band age scoring + window_count cosmetic (#1222)
Measurement honesty so we optimise SAP-relevant accuracy, not SAP-neutral
misses (ADR-0030 Component Accuracy):
- Add construction_age_band_pm1: an exact-or-adjacent-band hit. Adjacent
  RdSAP age bands carry near-identical U-values, so an off-by-one is
  ~SAP-neutral. Full corpus: exact 78.5% but ±1-band 91.7% (fixture
  63.9% -> 83.3%) — most age misses are adjacent.
- Drop window_count from the gate's residual ceilings (cosmetic): the
  predicted picture clusters at a mapper-default 4 windows vs actuals 1-21,
  but total_window_area (the SAP-relevant signal) stays tight at ~3.4 m2.

Gate: + construction_age_band_pm1 floor 0.8333; window_count no longer gated.

Closes #1222

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 10:01:20 +00:00
Khalim Conn-Kowlessar
a5b7310911 feat(epc-prediction): recency-weighted mode for roof insulation (ADR-0029/0030)
Investigated recency-weighting (weight cohort votes by an exponential decay
in cert age). Key finding: it must be SELECTIVE. On the validation corpus it
HURTS permanent categoricals (wall 91.2->89.5, age 78.5->75.7 — discards
still-valid data) but clearly HELPS time-varying ones, where a recent
neighbour reflects the current physical state:
  roof_insulation_thickness  56.7 -> 60.7%  corpus   (+4pp)
                             29.4 -> 41.2%  fixture  (+12pp)

So apply a recency-weighted mode only to roof_insulation_thickness (loft
top-ups happen over time); keep the plain mode for permanent categoricals.
tau = 4yr (~2.8yr half-life); falls back to plain mode when no registration
dates are lodged. Gate floor ratcheted 0.2941 -> 0.4118.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 09:45:22 +00:00
Khalim Conn-Kowlessar
9dd23477ac feat(epc-prediction): cohort-mode roof + floor insulation (ADR-0030)
These independent fabric categoricals were template-copied; mode them like
the construction categoricals. Verified mode beats template before applying.
Big fixture win on roof insulation thickness (doubled), floor insulation
neutral-to-positive:
  roof_insulation_thickness  14.7% -> 29.4%  (gate floor ratcheted up)
  floor_insulation           90.6% (unchanged on the fixture)

Glazing type was tried too (+1.6pp on the 40-postcode corpus) but REGRESSED
the 36-target fixture (0.50 -> 0.44) — the gate caught it. Glazing moding is
marginal/noisy, so it's left on the template; revisit with a larger corpus.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 09:37:45 +00:00
Khalim Conn-Kowlessar
e3a2720e5c feat(epc-prediction): Tier-1 ratcheting Component Accuracy gate (ADR-0030)
The committed CI gate: run the calculator-free leave-one-out scorer over the
frozen anonymised fixture (36 SAP-10.2 targets) and assert each per-component
classification rate / geometry residual is no worse than a committed baseline.
Prediction is deterministic + the fixture frozen, so the numbers reproduce
exactly — a failure is a real regression, never sample noise.

- 19 rate floors + 5 residual ceilings, seeded at the currently-measured
  values; they only ever tighten (no-widening ethos on an aggregate).
- Calculator-FREE — component floors are the real gate; the end-to-end
  SAP/carbon/PE guards stay out (their floor is the separate API-path
  calculator workstream).
- Skips with a message when the fixture is absent.

25 parametrized assertions, all green.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-14 09:19:39 +00:00