Table 4.

Quality of PLS-DA model for the discrimination of two groups when different normalization approaches are applied on the data. The table is reproduced with permission from

(Saccenti 2017)

	Method	NMC	Q 2	DQ 2	AUROC
1	TSA	64	0.02	0.02	0.60
2	IS	77	− 0.33	0.005	0.37
3	UO	57	− 0.04	0.007	0.61
4	PQN	62	− 0.05	− 0.03	0.64
5	Loess	1	0.89	0.92	1
6	Contrast	23	0.41	0.56	0.99
7	Quantile	7	0.63	0.81	0.99
8	Linear	86	− 0.69	− 0.02	0.28
9	Li Wong	64	− 0.25	− 0.03	0.56
10	Spline	7	0.36	0.7	1
11	VSN	0	0.95	0.97	1
12	None	33	0.21	0.25	0.77

NMC Number of misclassifications, DQ² discriminant Q², AUROC area under the receiver operating curve. The measures are discussed in (Saccenti 2017)