Table 16.

From [23] original caption, “Iris recognition performances on the CASIA dataset, with the cross-validation performed after the over-sampling (SMOTE).”

Method	Accuracy	Precision	Recall	F1	AUC
All features
OneR	0.9982 ± 0.003	1.00 ± 0.01	0.99 ± 0.01	0.99 ± 0.01	1.00 ± 0.01
J48	0.9926 ± 0.006	0.99 ± 0.02	0.96 ± 0.04	0.98 ± 0.02	0.98 ± 0.02
SMO	0.9927 ± 0.005	0.99 ± 0.02	0.96 ± 0.03	0.98 ± 0.02	0.98 ± 0.01
SVC	0.9955 ± 0.004	0.97 ± 0.03	1.00 ± 0.01	0.98 ± 0.02	0.99 ± 0.00
RandomForest	0.9980 ± 0.003	1.00 ± 0.01	0.99 ± 0.02	0.99 ± 0.01	1.00 ± 0.00
MultiboostAB	0.9998 ± 0.001	1.00 ± 0.00	1.00 ± 0.00	1.00 ± 0.00	1.00 ± 0.00
CatBoost	0.9993 ± 0.001	1.00 ± 0.01	1.00 ± 0.00	1.00 ± 0.00	0.99 ± 0.00
RFE-16
OneR	0.9978 ± 0.003	1.00 ± 0.01	0.99 ± 0.02	0.99 ± 0.01	0.99 ± 0.01
J48	0.9947 ± 0.005	0.99 ± 0.01	0.97 ± 0.03	0.98 ± 0.02	0.99 ± 0.01
SMO	0.9966 ± 0.004	0.99 ± 0.01	0.98 ± 0.02	0.99 ± 0.01	0.99 ± 0.01
SVC	0.9951 ± 0.002	0.97 ± 0.02	0.99 ± 0.01	0.98 ± 0.01	0.99 ± 0.00
RandomForest	0.9983 ± 0.002	1.00 ± 0.01	0.99 ± 0.01	0.99 ± 0.01	1.00 ± 0.00
MultiboostAB	0.9988 ± 0.002	1.00 ± 0.01	0.99 ± 0.01	1.00 ± 0.01	1.00 ± 0.00
CatBoost	0.9979 ± 0.002	0.99 ± 0.01	1.00 ± 0.01	0.99 ± 0.01	0.99 ± 0.00
RRF-8
OneR	0.9971 ± 0.003	1.00 ± 0.01	0.98 ± 0.02	0.99 ± 0.01	0.99 ± 0.01
J48	0.9960 ± 0.004	1.00 ± 0.01	0.98 ± 0.02	0.99 ± 0.01	0.99 ± 0.01
SMO	0.9995 ± 0.002	1.00 ± 0.01	1.00 ± 0.00	1.00 ± 0.00	1.00 ± 0.00
SVC	0.9997 ± 0.001	1.00 ± 0.00	1.00 ± 0.01	1.00 ± 0.00	0.99 ± 0.00
RandomForest	0.9982 ± 0.003	1.00 ± 0.01	0.99 ± 0.01	0.99 ± 0.01	1.00 ± 0.00
MultiboostAB	0.9977 ± 0.003	1.00 ± 0.01	0.99 ± 0.02	0.99 ± 0.01	1.00 ± 0.00
CatBoost	0.9986 ± 0.002	0.99 ± 0.01	1.00 ± 0.01	1.00 ± 0.01	0.99 ± 0.00