A Dendritic Neuron Model with Adaptive Synapses Trained by Differential Evolution Algorithm

Table 13

Rate results for the five datasets.

Dataset	Method	Test accuracy	Sensitivity	Specificity	AUC
Iris	DE-DMAS	96.74  2.78	100	96.88	98.44
	BP-DNM	91.78  5.87	91.16	86.67	95.65
	BPNN	85.93  10.89	90.00	91.43	90.71
Liver	DE-DMAS	73.59  6.66	66.67	83.87	75.27
	BP-DNM	68.62  5.24	52.50	.79.69	66.09
	BPNN	59.94  6.33	57.89	72.73	65.31
Cancer	DE-DMAS	96.12  1.17	96.45	98.55	97.50
	BP-DNM	96.33  1.43	97.04	94.67	95.85
	BPNN	93.76  11.06	95.89	96.88	96.38
Glass	DE-DMAS	94.42  2.51	98.57	92.85	96..67
	BP-DNM	91.87  3.88	84.62	96.08	90.35
	BPNN	92.50  3.34	97.92	81.25	89.58
ACA	DE-DMAS	86.18  1.98	88.04	86.09	87.07
	BP-DNM	83.66  9.26	85.54	81.45	83.50
	BPNN	85.57  2.28	87.10	78.07	82.58