A Metabolomics Approach to Stratify Patients Diagnosed with Diabetes Mellitus into Excess or Deficiency Syndromes

Table 3

Parameters from KOPLS models.

KOPLS Parameters	Sigma	Ao	ACCV^a	R2X^b	R2Y^b	Q2Y^c	Total accuracy	Balance accuracy	AUC^d	AUC 95% confidence interval	sensitivity	specificity
Excess versus Deficency	2.5	3	0.860	0.425	1	0.944	0.949	0.968	0.968	0.950–0.987	1	0.937

^aAccuracy of classification of cross-validation (ACCV) produced from each combination of and Ao parameters after cross-validation. ^bR2Xcum and R2Ycum represent the cumulative sum of squares (SS) of all the X’s and Y’s explained by all extracted components. ^cQ2Ycum is an estimate of how well the model predicts the Y’s. ^dAUC in 0.5~0.7 has lower accuracy, AUC in 0.7~0.9 has certain accuracy (model can be accepted), and AUC in more than 0.9 has high accuracy. When AUC = 0.5, the model has no value.