Table 2.

Detailed accuracy by class of the grapevine varietal classification using support vector machines and a 5-fold cross-validation (n = 159).

Class	True Positive Rate	False Positive Rate	Precision	AUC
Cabernet Sauvignon (CS)	1.000	0.007	0.941	0.997
Caladoc (CL)	0.938	0.014	0.882	0.997
Carmenere (CR)	0.938	0.007	0.938	0.998
White Grenache (WG)	0.800	0.007	0.923	0.985
Pedro Ximenez (PX)	0.813	0.021	0.813	0.980
Pinot Noir (PN)	0.875	0.014	0.875	0.976
Tempranillo (TE)	0.938	0.014	0.882	0.997
Treixadura (TR)	0.875	0.000	1.000	0.999
Viognier (VO)	0.750	0.028	0.750	0.992
Viura (VU)	0.938	0.014	0.882	0.992
Weighted average	0.887	0.013	0.888	0.991

AUC: area under the receiver operating characteristic (ROC) curve.