Particle Swarm Optimization Based Selective Ensemble of Online Sequential Extreme Learning Machine

Table 3

Comparison of algorithms for regression problems with sigmoid hidden nodes.

Datasets	Algorithm	Number of nodes	Number of networks	Training time (s)	RMSE or Accuracy		Testing dev.
					Training RMSE	Testing RMSE
Abalone	OS-ELM	25		0.1191	0.0758	0.0782	0.0049
	EOS-ELM	25	5	0.5942	0.0754	0.0775	0.0023
	SEOS-ELM (GASEN)	25	5	7.3864	0.0744	0.0760	0.0016
	SEOS-ELM (PSOSEN)	25	5	4.1528	0.0742	0.0758	0.0015
Mackey-Glass	OS-ELM	120		0.9827	0.0177	0.0185	0.0018
	EOS-ELM	120	5	4.8062	0.0176	0.0183	0.0007
	SEOS-ELM (GASEN)	120	5	37.4371	0.0172	0.0180	0.0005
	SEOS-ELM (PSOSEN)	120	5	25.1608	0.0173	0.0179	0.0006
California Housing	OS-ELM	50		0.6871	0.1276	0.1335	0.0035
	EOS-ELM	50	5	3.2356	0.1280	0.1337	0.0019
	SEOS-ELM (GASEN)	50	5	20.7635	0.1242	0.1321	0.0014
	SEOS-ELM (PSOSEN)	50	5	15.6326	0.1238	0.1323	0.0014