The Optimisation for Local Coupled Extreme Learning Machine Using Differential Evolution

Table 4

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

Dataset	Algorithm	Training (%)		Training time	Testing (%)		Testing time	Number of nodes/rules
		RMSE	SD		RMSE	SD
Abalone	ELM	0.0761	0.0012	0.0172	0.0776	0.0027	0.0016	25
	OSFuzzyELM	0.0741	0.0015	1.3026	0.0766	0.0023	0.0406	5
	LC-ELM	0.0754	0.0011	0.4524	0.0767	0.0018	0.2699	25
	ELC-ELM	0.0754	0.0013	537.1114	0.0743	0.0025	0.2278	25
Autoprice	ELM	0.0879	0.0101	0.0016	0.1205	0.0190	0.0009	15
	OSFuzzyELM	0.0401	0.0052	0.0624	0.1096	0.0078	0.0252	3
	LC-ELM	0.0757	0.0044	0.0031	0.0842	0.0087	0.0016	15
	ELC-ELM	0.0805	0.0059	37.1688	0.0769	0.0048	0.0025	15
Bodyfat	ELM	0.0678	0.0038	0.0062	0.1295	0.0191	0.0047	50
	OSFuzzyELM	0.0790	0.0038	0.0686	0.1264	0.0323	0.0031	2
	LC-ELM	0.0661	0.0038	0.0562	0.1243	0.0243	0.0218	50
	ELC-ELM	0.0680	0.0013	193.9529	0.1129	0.0115	0.0224	50
Computer	ELM	0.0339	0.0008	0.3354	0.0408	0.0044	0.0406	125
	OSFuzzyELM	0.0257	0.0006	83.6555	0.0346	0.0044	0.1950	15
	LC-ELM	0.0345	0.0016	2.2511	0.0407	0.0033	0.9812	125
	ELC-ELM	0.0279	0.0003		0.0288	0.0005	1.0868	125
CPU	ELM	0.0476	0.0066	0.0016	0.0865	0.0584	0.0008	10
	OSFuzzyELM	0.0284	0.0035	0.0499	0.0659	0.0339	0.0031	3
	LC-ELM	0.0416	0.0070	0.0047	0.0582	0.0203	0.0016	10
	ELC-ELM	0.0394	0.0069	29.3719	0.0360	0.0092	0.0025	10
Housing	ELM	0.0793	0.0047	0.0062	0.0929	0.0093	0.0016	50
	OSFuzzyELM	0.0645	0.0043	0.3011	0.0924	0.0163	0.0094	5
	LC-ELM	0.0711	0.0035	0.1076	0.0884	0.0091	0.0390	50
	ELC-ELM	0.0682	0.0040	281.3338	0.0807	0.0127	0.3768	50