Table 6.

Prediction results of ELM based on fluorescence spectral data.

Feature extraction method	Number of feature variables	Number of hidden neurons	${\mathit{\text{R}}}_c^2$	RMSEC	${\mathit{\text{R}}}_p^2$	RMSEP	RPD
Boss	31	42	0.8805	0.6347	0.8329	0.5434	2.24
CARS	25	50	0.9034	0.5181	0.8784	0.5881	2.73
IVSO	23	47	0.8809	0.5768	0.8530	0.6427	2.45
IVISSA	41	44	0.9004	0.5556	0.8598	0.5275	2.52
MASS	29	55	0.9219	0.4493	0.8889	0.5957	2.88
CARS-Boss	21	54	0.8839	0.5679	0.8689	0.6107	2.62
MASS-Boss	21	59	0.9429	0.4229	0.8894	0.4824	2.88
IVISSA-Boss	20	65	0.9331	0.4542	0.8755	0.5802	2.67

The bold values represent the best performer in each table.