Cars — Performance Report

2026-10-26 05:13

LightGBM · Colombia

Model Metrics

CV scores per fold

CV Scores per Fold
	fold_1	fold_2	fold_3	fold_4	fold_5
mse	164,622,009,113,466	168,598,628,412,365	192,948,899,213,440	176,144,424,755,147	182,482,143,980,354
rmse	12,830,511	12,984,553	13,890,605	13,271,941	13,508,595
mae	6,967,885	7,060,273	7,092,769	7,025,352	7,229,680
mape	0.0785	0.0793	0.0790	0.0791	0.0797
median_ae	3,803,155	3,814,759	3,845,059	3,831,837	3,904,440
r2	0.9752	0.9737	0.9692	0.9720	0.9725
explained_variance	0.9752	0.9737	0.9692	0.9720	0.9725

CV summary statistics

CV Summary Statistics
	count	mean	std	min	25%	50%	75%	max
mse	5.0000	176,959,221,094,954	11,279,879,056,162	164,622,009,113,466	168,598,628,412,365	176,144,424,755,147	182,482,143,980,354	192,948,899,213,440
rmse	5.0000	13,297,241	422,197.1	12,830,511	12,984,553	13,271,941	13,508,595	13,890,605
mae	5.0000	7,075,192	97,975.6	6,967,885	7,025,352	7,060,273	7,092,769	7,229,680
mape	5.0000	0.0791	4.00e-04	0.0785	0.0790	0.0791	0.0793	0.0797
median_ae	5.0000	3,839,850	39,494.8	3,803,155	3,814,759	3,831,837	3,845,059	3,904,440
r2	5.0000	0.9725	2.20e-03	0.9692	0.9720	0.9725	0.9737	0.9752
explained_variance	5.0000	0.9725	2.20e-03	0.9692	0.9720	0.9725	0.9737	0.9752

Test-set metrics

Test Set Metrics
Metric	Test Score
mse	156,319,745,375,301
rmse	12,502,790
mae	6,870,144
mape	0.0771
median_ae	3,762,876
r2	0.9752
explained_variance	0.9752

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