The Optimisation for Local Coupled Extreme Learning Machine Using Differential Evolution

Table 6

Classification results of ELM, OSFuzzyELM, LC-ELM, and ELC-ELM.

Dataset	Algorithm	Training (%)		Training time	Testing (%)		Testing time	Number of nodes/rules
		Accy	SD		Accy	SD
Ecoli	ELM	89.78	0.90	0.0062	85.71	1.68	0.0031	20
	OSFuzzyELM	90.04	1.53	0.1045	86.79	2.72	0.0047	5
	LC-ELM	89.29	1.17	0.0218	87.14	4.23	0.0156	20
	ELC-ELM	90.89	0.74	312.5917	89.29	4.29	0.0162	20
Glass	ELM	72.25	3.82	0.0047	63.47	5.36	0.0016	20
	OSFuzzyELM	92.04	1.88	0.1529	63.33	4.05	0.0062	10
	LC-ELM	74.79	2.97	0.0172	63.75	6.56	0.0062	20
	ELC-ELM	73.59	3.31	21.9727	66.39	6.98	0.0074	20
Ionosphere	ELM	91.70	1.69	0.0078	83.51	3.12	0.0031	40
	OSFuzzyELM	95.88	3.29	0.1357	80.91	4.98	0.0031	3
	LC-ELM	93.86	2.05	0.0359	86.49	2.68	0.0218	40
	ELC-ELM	93.53	1.70	121.4764	86.84	3.51	0.0236	40
Iris	ELM	98.30	0.67	0.0031	96.60	2.50	0.0016	15
	OSFuzzyELM	98.50	0.71	0.0296	96.00	2.11	0.0031	5
	LC-ELM	97.90	1.29	0.0078	96.40	2.07	0.0047	15
	ELC-ELM	97.40	0.52	11.8374	97.20	2.70	0.0054	15
Sonar	ELM	88.70	2.92	0.0031	75.57	3.95	0.0016	40
	OSFuzzyELM	97.46	3.35	0.2558	67.00	8.21	0.0062	3
	LC-ELM	89.42	4.06	0.0343	76.29	6.25	0.0187	40
	ELC-ELM	89.78	2.95	117.0569	78.00	6.61	0.0178	40
Wisconsin	ELM	97.71	0.55	0.0047	96.36	1.42	0.0031	40
	OSFuzzyELM	97.54	0.38	0.1934	96.45	1.10	0.0094	5
	LC-ELM	97.49	0.43	0.0874	96.97	1.06	0.0406	40
	ELC-ELM	97.41	0.53	250.2381	97.54	1.59	0.0397	40