Table 2.
Model | Amount of components | R 2 X | R 2 Y | Q 2 Y |
---|---|---|---|---|
PCA-X | 1 | 0.111 | 0.0165 | |
PLS-DA | 1 | 0.0592 | 0.507 | 0.0723 |
OPLS | 1 | 0.0592 | 0.508 | 0.0688 |
R 2 X cum and R 2 Y cum represent the cumulative sum of squares (SS) of all the X's and Y's explained by all extracted components.
Q 2 Y cum is an estimate of how well the model predicts the Y's.