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ed96df9315
The comparison only scored main wall_construction; everything else the predictor produces (by template-copy) went unmeasured. Extend compare_prediction to the rest of the ADR-0029 homogeneous categoricals — wall insulation type, construction age band, roof construction, floor construction — and aggregate per-categorical classification rates in the runner. A categorical hit is "not applicable" (None, excluded from the denominator) when the actual lodges no value, so absent-roof flats don't score free wins. Smoke corpus (29 leave-one-out, all but wall are template-copied today): wall_construction 93.1% wall_insulation_type 93.1% construction_age_band 55.2% <- loud; candidate for cohort-mode roof_construction 72.4% floor_construction 46.2% (n=13) These numbers drive the next slice (extend cohort-mode coverage). Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com> |
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| .. | ||
| eon | ||
| analyse_api_sap_clusters.py | ||
| decompose_api_cost_error.py | ||
| download_cotality_evidence.py | ||
| elmhurst_input_sheet.py | ||
| eval_api_sap_accuracy.py | ||
| fetch_2026_epc_sample.py | ||
| fetch_cohort2_api_jsons.py | ||
| fetch_epc_bulk_sample.py | ||
| fetch_epc_dump.py | ||
| fetch_epc_prediction_corpus.py | ||
| historic_epc_demo.py | ||
| init_db.py | ||
| profile_api_error.py | ||
| rename_sharepoint_files.py | ||
| run_audit_generator_local.py | ||
| run_modelling_cohort.py | ||
| run_modelling_e2e.py | ||
| run_property_report.py | ||
| sero_address_list.csv | ||
| validate_epc_prediction.py | ||