Table 3. Delong test, NRI, and IDI results of eight machine learning models based on the same test dataset (n=155).

Model1	Model2	Z for Delong	P for Delong	NRI	Z for NRI	P for NRI	IDI	Z for IDI	P for IDI
Naive Bayes	Logistic regression	−0.751	0.453	−0.033	−0.467	0.640	−0.057	−0.816	0.415
Naive Bayes	K-nearest neighbor	−0.777	0.437	−0.002	−0.034	0.973	−0.007	−0.114	0.909
Naive Bayes	Random forest	−0.386	0.699	−0.021	−0.316	0.752	−0.044	−0.658	0.511
Naive Bayes	Decision tree	2.114	0.035	0.122	1.606	0.108	0.079	1.203	0.229
Naive Bayes	Gradient boosting tree	0.800	0.424	0.059	0.789	0.430	0.040	0.594	0.553
Naive Bayes	Support vector machine	−0.675	0.500	0.842	5.496	<0.001	−0.019	−0.318	0.750
Naive Bayes	Multilayer perceptron	0.911	0.362	0.213	2.244	0.025	0.103	1.505	0.132
Logistic regression	K-nearest neighbor	−0.108	0.914	0.030	0.346	0.729	0.050	0.663	0.507
Logistic regression	Random forest	0.507	0.612	0.011	0.200	0.841	0.014	0.211	0.833
Logistic regression	Decision tree	2.688	0.007	0.155	1.666	0.096	0.136	1.832	0.067
Logistic regression	Gradient boosting tree	1.601	0.109	0.092	1.282	0.200	0.098	1.395	0.163
Logistic regression	Support vector machine	0.162	0.871	0.874	5.893	<0.001	0.038	0.559	0.576
Logistic regression	Multilayer perceptron	1.444	0.149	0.246	2.775	0.006	0.160	2.101	0.036
K-nearest neighbor	Random forest	0.606	0.545	−0.019	−0.225	0.822	−0.037	−0.503	0.615
K-nearest neighbor	Decision tree	2.944	0.003	0.124	1.842	0.065	0.086	1.377	0.169
K-nearest neighbor	Gradient boosting tree	1.583	0.113	0.061	0.766	0.444	0.047	0.694	0.488
K-nearest neighbor	Support vector machine	0.260	0.795	0.844	5.559	<0.001	−0.012	−0.197	0.844
K-nearest neighbor	Multilayer perceptron	1.755	0.079	0.216	2.033	0.042	0.110	1.579	0.114
Random forest	Decision tree	2.756	0.006	0.143	1.548	0.122	0.123	1.680	0.093
Random forest	Gradient boosting tree	1.628	0.104	0.080	1.121	0.262	0.084	1.206	0.228
Random forest	Support vector machine	−0.425	0.671	0.863	5.802	<0.001	0.024	0.359	0.720
Random forest	Multilayer perceptron	1.148	0.251	0.235	2.673	0.008	0.146	1.952	0.051
Decision tree	Gradient boosting tree	−1.388	0.165	−0.063	−0.708	0.479	−0.039	−0.583	0.560
Decision tree	Support vector machine	−2.696	0.007	0.720	4.981	<0.001	−0.099	−1.516	0.130
Decision tree	Multilayer perceptron	−0.946	0.344	0.091	0.829	0.407	0.023	0.357	0.721
Gradient boosting tree	Support vector machine	−1.554	0.120	0.783	5.338	<0.001	−0.060	−0.910	0.363
Gradient boosting tree	Multilayer perceptron	0.249	0.804	0.154	1.525	0.127	0.062	0.872	0.383
Support vector machine	Multilayer perceptron	1.458	0.145	−0.629	−4.759	<0.001	0.122	1.748	0.080

NRI, net reclassification improvement; IDI, integrated discrimination improvement.