1{2 "record_id": "2cdb6f374417590715ab5db24f593d17616b9ea2",3 "eligible": true,4 "short_ref": "Han, Woo & Lee (2025)",5 "country": "South Korea",6 "city": "Seoul",7 "property_type": "single-family houses",8 "price_type": "transaction price (log)",9 "n_obs": 13776,10 "sample_period": "2017-2019",11 "data_source": "Value Up Systems transaction platform (MOU); Google Street View panoramas (233,106) segmented with DeepLab V3+",12 "methods_compared": [13 "linear regression (hedonic)",14 "random forest",15 "XGBoost",16 "gradient boosting"17 ],18 "best_method": "gradient boosting",19 "metric": "R2",20 "best_value": 0.817,21 "hedonic_value": 0.66,22 "test_set": "holdout",23 "features_ai": "street-view CNN",24 "incremental_ai_gain": null,25 "incremental_ai_metric": "",26 "marginal_effects": "SHAP",27 "notes": "Table 2, 20% holdout (2,755 test obs): R2 0.660 (linear regression), 0.318 (RF), 0.765 (XGBoost), 0.817 (gradient boost); MSE 0.056 and MAE 0.169 for GB in log-price units. All models include the street-view segmentation shares (greenery, sky, buildings, etc.); no model without them is reported, so no incremental gain. SHAP global/local plots plus PDP for key variables.",28 "confidence": "high"29}