Table 2. Mean test AUC for different algorithms using BootRank.

Disease/algorithm	T1D	T2D	BD	CD	CAD	RA	HT
Support vector machine (SVM)	0.90	0.76	0.78	0.64	0.63	0.71	0.61
Random forest (RF)	0.88	0.76	0.77	0.65	0.68	0.71	0.64
Regularized logistic regression (RLR)	0.91	0.77	0.76	0.696	0.71	0.78	0.68
Naïve Bayes (NB)	0.77	0.83	0.83	0.67	0.72	0.71	0.68
Allele count (AC)	0.80	0.79	0.80	0.63	0.59	0.65	0.61
Log Odds (LO)	0.81	0.81	0.81	0.699	0.69	0.71	0.67
Robust adaboost (RAB)	0.89	0.78	0.78	0.695	0.75	0.75	0.71
Majority (all algorithms)	0.90	0.82	0.83	0.70	0.72	0.74	0.68
4-Majority (only RF, RLR, NB and RAB)	0.91	0.82	0.82	0.71	0.75	0.77	0.70

Shown are the average AUC values for test individuals for the different algorithms when using BootRank, or when combining all 7 algorithms (Majority), or only 4 algorithms (4-Majority).