Table 2:

Numerical results (mean ± standard deviation) for 5 repeats of different methods on Alzheimer’s disease (AD) and Credit Card (CC) datasets regarding six measurements. Time is in the format of “hours:minutes:seconds”. FACIMS-I means FACIMS $(\beta =0)$, and FACIMS-II means FACIMS $(\beta =0,v=\overline{v})$. “$\uparrow$” indicates the larger the better while “$\downarrow$” indicates the smaller the better. The best one in each column is bold.

Data	Method	Balanced Accuracy ↑	Demographic Parity ↓	Equalized Odds ↓	Sufficiency Gap ↓	Recall 0 ↑	Recall 1 ↑	Time ↓
AD	EIIL	.8639±.0199	.0764±.0176	.1015±.0529	.1193±.0206	.9288±.0119	.7991±.0409	0:03:32
	FSCS	.8498±.0485	.0711±.0287	.1650±.1008	.1254±.0528	.9504±.0426	.7493±.1018	0:08:05
	FAMS	.8369±.0136	.0431±.0210	.1444±.0435	.1328±.0273	.7624±.0077	.9114±.0096	0:09:51
	ERM	.8687±.0136	.0550±.0196	.1143±.0390	.1701±.0387	.9883±.0053	.7491±.0430	0:00:51
	BERM	.8886±.0042	.0869±.0204	.0813±.0129	.1456±.0330	.9854±.0043	.7918±.0520	0:02:24
	FACIMS-II	.8839±.0079	.0747±.0182	.0868±.0130	.1167±.0139	.8456±.0148	.9222±.0043	0:09:58
	FACIMS-I	.8887±.0066	.0893±.0080	.0450±.0049	.1059±.0060	.8780±.0104	.8994±.0148	0:13:38
	FACIMS	.8897±.0098	.0765±.0208	.0616±.0142	.1052±.0197	.8832±.0072	.8962±.0054	0:15:26
CC	EIIL	.6357±.0267	.0834±.0200	.1723±.0515	.1266±.023	.7897±.0176	.4817±.0448	0:03:30
	FSCS	.5976±.0277	.0850±.0137	.2000±.0456	.2007±.0039	.8953±.0130	.3000±.0685	0:42:10
	FAMS	.6542±.0098	.0746±.0066	.1859±.0368	.1352±.0106	.8194±.0374	.4890±.0270	0:10:21
	ERM	.6104±.0111	.0599±.0173	.1577±.0175	.2760±.0710	.9919±.0233	.2289±.0820	0:02:07
	BERM	.6570±.0106	.1060±.0125	.1631±.0304	.2315±.0623	.8717±.0191	.4423±.0146	0:02:09
	FACIMS-II	.6446±.0163	.0707±.0073	.1973±.0358	.1340±.0147	.8002±.0374	.4890±.0270	0:10:03
	FACIMS-I	.6768±.0040	.0750±.0105	.1951±.0524	.1396±.0081	.8081±.0114	.5455±.0098	0:14:07
	FACIMS	.6799±.0374	.0593±.0070	.1567±.0230	.1264±.0145	.8136±.0054	.5462±.0017	0:14:18