Why does preprocessed test data change when calibration dataset (and model based on that data) changes? I have spectral, normalized datasets, the preprocessing was 1. derivative + autoscale.
For example: I have 2 datasets: 100 samples with 400 variables each as calibration data; 20 samples for test data. preprocessing as above, data was cross-validated as well. the model for PLS-DA was calculated using pls toolbox in matlab. when I plot preprocessed test data I get different results compared to situation when I used e.g. half of those calibration-set samples to create a model. and I can't plot preprocessed test data without calculating the model. how is it connected?
I also tried to put my 20-sample test data as calibration data just to create model, and the preprocessed data plot was also different from plots obtained before.