Closed stefaniamagg closed 5 years ago
PLSDA funnily enough is like that, see:
explained_variance (as seen in axes): amount of variance explained per component (note that contrary to PCA, this amount may not decrease as the aim of the method is not to maximise the variance, but the covariance between X and the dummy matrix Y).
Ahh, right!
The PCA plot that was created by the PLSDA showes PC2 with a higher percentage than PC1.