Roles of biochemistry data, lifestyle, and inflammation in identifying abnormal renal function in old Chinese

Table 4 Area under receiver operating characteristic curve derived from five different machine learning methods of the three different models

Model/AUC	Model 1	Model 2	Model 3
MARS	0.633	0.693	0.760
XGboost	0.602	0.663	0.786
SGB	0.599	0.666	0.814
LightGBM	0.615	0.646	0.776
Catboost	0.623	0.663	0.744
Mean	0.6144	0.6662	0.776

AUC: Area under receiver operating characteristic curve, MARS: Multivariate adaptive regression splines; XGBoost: eXtreme Gradient Boosting; SGB: Stochastic gradient boosting; LightGBM: Light Gradient Boosting Machine; CATboost: Categorical Features + Gradient Boosting. Model 1: Demographic and biochemistry data; Model 2: Model 1 + lifestyle factors; Model 3: Model 2 + inflammation factors.