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

Table 5

Comparison of algorithms for regression problems with RBF 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		0.3445	0.0753	0.0775	0.0027
	EOS-ELM	25	25	8.5762	0.0752	0.0773	0.0023
	SEOS-ELM (GASEN)	25	25	54.2453	0.0742	0.0760	0.0016
	SEOS-ELM (PSOSEN)	25	25	49.3562	0.0741	0.0761	0.0017
Mackey-Glass	OS-ELM	120		1.6854	0.0181	0.0185	0.0092
	EOS-ELM	120	5	8.4304	0.0171	0.0171	0.0028
	SEOS-ELM (GASEN)	120	5	79.3216	0.0155	0.0158	0.0021
	SEOS-ELM (PSOSEN)	120	5	55.1469	0.0159	0.0156	0.0016
California Housing	OS-ELM	50		1.8329	0.1298	0.1317	0.0017
	EOS-ELM	50	5	9.0726	0.1296	0.1316	0.0011
	SEOS-ELM (GASEN)	50	5	69.8636	0.1216	0.1262	0.0008
	SEOS-ELM (PSOSEN)	50	5	64.9625	0.1202	0.1243	0.0009