1{2 "task_id": "F3-conf-03",3 "n_origins": 60,4 "first_origin": "2021-09-01",5 "last_origin": "2026-08-01",6 "lambda": 50.0,7 "normalisation_window": "expanding",8 "n_features": 8,9 "rmse_naive": 0.8830699166753823,10 "mae_naive": 0.6989594000000001,11 "rmse_mean": 0.5439355781141625,12 "mae_mean": 0.42929777256194207,13 "rmse_ridge": 0.5607989303521244,14 "mae_ridge": 0.45141289074453916,15 "rel_improvement_vs_naive": 0.3649439078805412,16 "rel_improvement_vs_mean": -0.031002480654837017,17 "feasibility": "complete",18 "feasibility_reason": null,19 "data_issues": [20 {21 "issue": "missing values: neworder_chg 2 (1992-01/02); other columns 0",22 "handling": "outside every training window (training starts 1992-03, lags reach back to 1992-01 only for ip_growth); no imputation"23 },24 {25 "issue": "README says the first month of each change series is empty, but ip_growth (and other change columns) for 1992-01 are populated",26 "handling": "values kept as given; ip_growth 1992-01 is used only as the second lag of the 1992-03 training row, as the task specification implies"27 },28 {29 "issue": "extreme COVID-19 observations in 2020 (ip_growth range -14.14 to 6.35)",30 "handling": "kept in all training windows as specified (no outlier treatment); they influence standardisation statistics and coefficients"31 }32 ],33 "n_input_rows": {34 "ip_predictors.csv": 41735 },36 "n_analysed": 413,37 "random_seed": 1234538}