PLSM Partial Least Squares Feature Extraction
W = PLSM
W = PLSM(,MAXLV,METHOD)
[W, INFORM] = PLSM(A,MAXLV,METHOD)
| A|| training dataset|
| MAXLV|| maximal number of latent variables (will be corrected if > rank(A)); MAXLV=inf means MAXLV=min(size(A)) -- theoretical maximum number of LV; by default = inf|
| METHOD|| 'NIPALS' or 'SIMPLS'; by default = 'SIMPLS' |
DESRIPTION PRTools Adaptation of PLS_TRAIN/PLS_TRANSFORM routines No preprocessing is done inside this mapping. It is the user responsibility to train preprocessing on training data and apply it to the test data.
| W|| PLS feature extraction mapping|
| INFORM|| extra algorithm output|
Crisp labels will be converted into soft labels which will be used as a target matrix.
pls_train, pls_transform, pls_apply,
|This file has been automatically generated. If badly readable, use the help-command in Matlab.|