Table 7.

The experimental results for comparison

Dataset	Our algorithm (BiR)		Literature [25]		Bayes net		Random forest		Decision tree
	Auc	Accuracy(%)	Auc	Accuracy(%)	Auc	Accuracy(%)	Auc	Accuracy(%)	Auc	Accuracy(%)
Acute inflammations	1	100	1	100	1	100	1	100	1	100
Breast cancer wisconsin	0.99	95.85	0.99	97.89	1	97.89	0.99	97.14	0.98	93.14
Breast cancer coimbra	0.77	77.45	0.72	72.45	0.64	62.07	0.68	58.62	0.70	62.07
Heart disease	0.88	84.59	0.78	80.26	0.88	82.89	0.84	76.32	0.81	78.95
Hepatitis	0.99	94.19	0.98	80.68	0.91	84.62	0.87	82.05	0.79	71.79
Lymphography	1	100	1	90.60	0	100	1	97.30	0.99	97.30
Spect heart	0.94	88.39	0.93	84.59	0.82	79.10	0.83	91.04	0.75	77.61

Bold entries represent better Auc and accuracy values