bot-backend
f999011b30
Review found the hedonic factor (≤1.30) was applied AFTER the estimate_expected_sold_le_asking clamp, so expected_sold could exceed the asking headline (median) by up to ~26% for new/small lots — an overpay risk that violated the default-True le_asking invariant. Fix: re-assert le_asking right after the hedonic block and before the calibrated-PI range block. Final order: ratio clamp -> hedonic factor -> le_asking re-clamp -> calibrated PI range (range still wraps the clamped point). round(median_ppm2) keeps expected_sold_per_m2 an int. The re-clamp does NOT materially erode the новостройка/бизнес benefit (бизнес bias -9.15->-10.19, MAPE held 12.87) and actually improves overall expected_sold MAPE on the frozen fixture (14.24->13.23) by capping over-corrections that overshot actual sold prices. Adds tests/test_estimator_hedonic.py (hermetic, no DB): factor magnitude vs OFF, both clamp boundaries, neutral year term for target_year=None, and the le_asking invariant under hedonic ON. Baseline regenerated; gate green. Also clarifies the config comment: the quoted held-out fit metrics (18.5->16.1 etc., n=2366) are distinct from the 277-deal backtest fixture (18.63->13.23).
154 lines
3.1 KiB
JSON
154 lines
3.1 KiB
JSON
{
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"calibration": {
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"high": {
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"coverage_pct": null,
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},
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"low": {
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"coverage_pct": 81.82,
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"n": 275,
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},
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"medium": {
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}
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},
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"confidence_order": [
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"high",
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"medium",
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"low"
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],
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"expected_sold": {
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"overall": {
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"mape_pct": 13.23,
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"median_bias_pct": -2.87,
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"n": 277,
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"n_no_analogs": 0,
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"p25_pct": -14.43,
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"p75_pct": 12.51
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},
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"per_rooms": {
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"0": {
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"label": "студия",
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"mape_pct": 19.38,
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"median_bias_pct": 18.1,
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"n": 37,
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"n_no_analogs": 0,
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"p25_pct": 1.66,
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"p75_pct": 33.53
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},
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"1": {
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"label": "1к",
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},
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"2": {
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"label": "2к",
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"median_bias_pct": -11.71,
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"p25_pct": -23.37,
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"p75_pct": -0.36
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},
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"3": {
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"label": "3к",
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"4": {
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"label": "4+",
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}
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},
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"per_segment": {
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"бизнес": {
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"p25_pct": -22.6,
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},
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"комфорт": {
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"p25_pct": -15.64,
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},
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"премиум": {
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"mape_pct": 68.92,
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"median_bias_pct": -68.92,
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"n": 1,
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"p25_pct": -68.92,
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"p75_pct": -68.92
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},
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"эконом": {
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"mape_pct": 15.17,
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"median_bias_pct": 4.28,
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"n": 120,
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"p25_pct": -6.59,
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"p75_pct": 26.09
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},
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"элит": {
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"mape_pct": 33.2,
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"median_bias_pct": -33.2,
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"n": 6,
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"p25_pct": -42.75,
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"p75_pct": -22.4
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}
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}
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},
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"headline": {
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"ask_median_ppm2": 147545.8502510892,
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"deal_median_ppm2": 125063.0,
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"spread_pct": 17.98
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},
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"range_coverage": {
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"overall": {
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"coverage_pct": 81.95,
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"n": 277,
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"n_covered": 227
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},
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"per_confidence": {
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"high": {
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},
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"low": {
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},
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"medium": {
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}
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}
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},
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"sharpness": {
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"median_rel_width": 0.743,
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"n": 277
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}
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}
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