Table 5.

Mean testing accuracy and the AUC of ensemble learning methods after 50 replicates with standard deviation in the brackets

Model	Accuracy	AUC
Two-step stacking (14 models)	$\mathbf{87.7}\%(\mathbf{0.023})$	0.904 (0.026)
Two-step stacking (3 models)	$79.4\%(0.028)$	0.822 (0.030)
Traditional stacking (14 models)	$81.8\%(0.033)$	0.854 (0.034)
Traditional stacking (3 models)	$76.7\%(0.038)$	0.798 (0.037)
Weighted voting (14 models)	$73.3\%(0.033)$	0.751 (0.040)
Weighted voting (3 models)	$71.7\%(0.035)$	0.728 (0.037)
Two-step stacking with GLPS only	$63.3\%(0.034)$	0.674 (0.047)

Best results are bolded