Hi,
I have a question. Using PLS_Toolbox to do a plsda model, when I upload the calibration datasets X and Y, the toolbox can automatically select the numebr of latent variables. Is there a way to "translate" this in a matlab scritpt?
After the cross-validation, is there anyway to make the script select automatically the number of components? Is there any function? My Y dataset is made of 3 columns and for each column we have 1 or 0 dependent on whether or not that sample belongs to that class.
% Modello PLS-DA prima della cross_val
modello_in=evrimodel(‘plsda’);

% Calibrazione Modello PLS-DA prima della cross_val
modello_in.x=Xcal;
modello_in.y=Ycal;
modello_in.ncomp=5; % 5 LVs
modello_in.options.preprocessing={‘autoscale’ ‘autoscale’};
modello_in.options.display=’off’;
modello_in=modello_in.crossvalidate({‘vet’ 10}, 15);Hi,
I have a question. Using PLS_Toolbox to do a plsda model, when I upload the calibration datasets X and Y, the toolbox can automatically select the numebr of latent variables. Is there a way to "translate" this in a matlab scritpt?
After the cross-validation, is there anyway to make the script select automatically the number of components? Is there any function? My Y dataset is made of 3 columns and for each column we have 1 or 0 dependent on whether or not that sample belongs to that class.
% Modello PLS-DA prima della cross_val
modello_in=evrimodel(‘plsda’);

% Calibrazione Modello PLS-DA prima della cross_val
modello_in.x=Xcal;
modello_in.y=Ycal;
modello_in.ncomp=5; % 5 LVs
modello_in.options.preprocessing={‘autoscale’ ‘autoscale’};
modello_in.options.display=’off’;
modello_in=modello_in.crossvalidate({‘vet’ 10}, 15); Hi,
I have a question. Using PLS_Toolbox to do a plsda model, when I upload the calibration datasets X and Y, the toolbox can automatically select the numebr of latent variables. Is there a way to "translate" this in a matlab scritpt?
After the cross-validation, is there anyway to make the script select automatically the number of components? Is there any function? My Y dataset is made of 3 columns and for each column we have 1 or 0 dependent on whether or not that sample belongs to that class.
% Modello PLS-DA prima della cross_val
modello_in=evrimodel(‘plsda’);

% Calibrazione Modello PLS-DA prima della cross_val
modello_in.x=Xcal;
modello_in.y=Ycal;
modello_in.ncomp=5; % 5 LVs
modello_in.options.preprocessing={‘autoscale’ ‘autoscale’};
modello_in.options.display=’off’;
modello_in=modello_in.crossvalidate({‘vet’ 10}, 15); pls, plsda, pls_toolbox MATLAB Answers — New Questions

​