We have predicted the Test file scanned in Instrument 2 with the model developed with the Training file scanned in Instrument 1 (mod 1), and we have seen that the RMSEP is higher than the RMSEP obtained predicting the Test file scanned in Instrument 1 with the same model mod1. The X-Y plot will give us a better idea of what is going on.
This figure represents the predictions of the Test Set scanned in instrument 1 with the model mod1:
predplot(mod1,ncomp=3,newdata=data.frame(Y=I(Y.test),X=I(X1.test)),
asp=1,line=TRUE)
The next figure represents the predictions of the Test Set scanned in instrument 2 with the model mod1:
predplot(mod1,ncomp=3,newdata=data.frame(Y=I(Y.test),X=I(X2.test)),
asp=1,line=TRUE)
We can see that part of the RMSEP error is due to an important bias, and an increase of the random noise.
This shootout is probably the most famous so there is quite enough articles and documents and as far as we continue with this tutorial, we can see the results compared with other approaches.
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