1{2 "record_id": "fe9b5a96e7007d52e9bebe9eaea418541aa3b090",3 "eligible": true,4 "short_ref": "Tajani, Di Liddo, Ranieri & Anelli (2021)",5 "country": "Italy",6 "city": "Milan, Turin, Rome, Naples, Catania (five separate samples)",7 "property_type": "residential units (rented)",8 "price_type": "rent (EUR per m2 per month)",9 "n_obs": 1100,10 "sample_period": "second half of 2019",11 "data_source": "rented properties collected with local market operators and real estate agents (220 per city)",12 "methods_compared": [13 "evolutionary polynomial regression (EPR, genetic-algorithm AVM)"14 ],15 "best_method": "evolutionary polynomial regression (EPR)",16 "metric": "R2",17 "best_value": 0.8869,18 "hedonic_value": null,19 "test_set": "k-fold",20 "features_ai": "none",21 "incremental_ai_gain": null,22 "incremental_ai_metric": "",23 "marginal_effects": "coefficients",24 "notes": "Single-method AVM (genetic-programming polynomial regression) estimated city by city; n_obs = 5 x 220. Coefficient of determination printed per city: Milan 88.69%, Turin 79.31%, Rome 86.87%, Naples 74.92%, Catania 67.06% (average about 80%); best_value is the Milan model. RMSE/MAPE/MaxAPE are mentioned but their values are not printed in the text layer; a ten-fold cross-validation is said to confirm stability without printed CV metrics. Marginal contributions derived from the polynomial terms (percentage variation of rent per variable).",25 "confidence": "medium"26}