Cars — Performance Report

2026-06-29 05:12

LightGBM · Colombia

Model Metrics

CV scores per fold

CV Scores per Fold
	fold_1	fold_2	fold_3	fold_4	fold_5
mse	177,315,548,966,026	168,563,599,351,834	165,733,363,819,724	198,772,537,659,059	163,637,526,749,212
rmse	13,315,988	12,983,205	12,873,747	14,098,671	12,792,088
mae	6,792,750	6,884,071	6,697,490	6,976,485	6,894,147
mape	0.5435	0.0824	0.0820	0.3065	0.1951
median_ae	3,676,869	3,754,846	3,687,312	3,635,258	3,720,199
r2	0.9669	0.9720	0.9718	0.9650	0.9719
explained_variance	0.9669	0.9720	0.9718	0.9650	0.9719

CV summary statistics

CV Summary Statistics
	count	mean	std	min	25%	50%	75%	max
mse	5.0000	174,804,515,309,171	14,376,263,772,447	163,637,526,749,212	165,733,363,819,724	168,563,599,351,834	177,315,548,966,026	198,772,537,659,059
rmse	5.0000	13,212,740	533,873.9	12,792,088	12,873,747	12,983,205	13,315,988	14,098,671
mae	5.0000	6,848,989	106,817.6	6,697,490	6,792,750	6,884,071	6,894,147	6,976,485
mape	5.0000	0.2419	0.1926	0.0820	0.0824	0.1951	0.3065	0.5435
median_ae	5.0000	3,694,897	45,203.4	3,635,258	3,676,869	3,687,312	3,720,199	3,754,846
r2	5.0000	0.9695	3.30e-03	0.9650	0.9669	0.9718	0.9719	0.9720
explained_variance	5.0000	0.9695	3.30e-03	0.9650	0.9669	0.9718	0.9719	0.9720

Test-set metrics

Test Set Metrics
Metric	Test Score
mse	163,474,708,694,939
rmse	12,785,723
mae	6,765,212
mape	0.3611
median_ae	3,605,427
r2	0.9723
explained_variance	0.9723

Regression Quality

Actual vs Predicted

Error magnitude

Residuals

Residuals vs Predicted

Residual distribution

Distributions

Actual vs Predicted distribution

Cumulative Error

Cumulative absolute error

Feature Importance

Feature importance