# Faq how do I calculate scores from a PLS or PLSDA model

From Eigenvector Documentation Wiki

### Issue:

How do I calculate scores from a PLS or PLSDA model?

### Possible Solutions:

Because of the unique relationship between weights and loadings in a PLS model, the calculation of scores for new data does not simply involve a projection onto the loadings, as it does with PCR or PCA (i.e., Tnew = XnewP) . Given new data,`X`

, the scores for these new samples are instead calculated using:
_{new}

T_{new}= X_{new}W(P^{T}W)^{-1}

where `W`

is the matrix of PLS model weights and `P`

is the matrix of PLS model loadings.

In Matlab notation, this can be done using:

>> scores = x*W*pinv(P'*W)

where `x`

is the new data. Given a standard model structure from PLS_Toolbox named "model" the following defines `W`

and `P`

:

>> P = model.loads{2,1} >> W = model.wts

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