Recidivism prediction on NLSY97 benchmark leaderboard · SOTA2 Research

Recidivism prediction on NLSY97

0.6559AUCExtra Trees Classifier

Evaluation Results

Method
Extra Trees Classifier2026.01	0.6559	75.51	75.51	71.07	—	70.25	0.1249	0.1438
CatBoost Classifier2026.01	0.6449	74.6	74.6	71.02	—	70.08	0.1295	0.1433
Random Forest Classifier2026.01	0.6448	76.06	76.06	70.2	—	69.29	0.0939	0.1142
TabPFN baseline2026.01	0.641	70.11	0	0	—	—	—	—
Gradient Boosting Classifier2026.01	0.6375	74.61	74.61	71.9	—	71.35	0.1695	0.1816
Ridge Classifier2026.01	0.612	61.87	61.87	64.42	—	70.8	0.1403	0.158
Linear Discriminant Analysis2026.01	0.6103	61.31	61.31	63.93	—	70.64	0.1324	0.1512
Logistic Regression2026.01	0.6088	62.98	62.98	65.38	—	70.98	0.1524	0.1672
Extreme Gradient Boosting2026.01	0.6015	73.68	73.68	70.24	—	69.19	0.1091	0.1211
AdaBoost Classifier2026.01	0.597	70.36	70.36	68.81	—	67.91	0.1016	0.0997
Naive Bayes2026.01	0.5854	29.1	29.1	23.28	—	64.25	-0.0029	-0.0069
Decision Tree Classifier2026.01	0.5299	64.45	64.45	65.27	—	66.38	0.0554	0.056
SVM (Linear Kernel)2026.01	0.5231	34.31	34.31	21.89	—	29.08	-0.0013	0.0014
Quadratic Discriminant Analysis2026.01	0.5167	27.63	27.63	20.3	—	62.67	-0.0065	-0.019
K Neighbors Classifier2026.01	0.4789	47.89	47.89	51.53	—	63.5	-0.0144	-0.0186