Rank: 1374 based on 109 downloads (last 30 days) and 3 files submitted
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Hongdong Li

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Company/University
Central South University

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www.libpls.net

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Computing something interesting

 

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03 Mar 2014 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li statistics, modeling, model population anal..., variable selection, pls, chemometrics 66 5
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14 Apr 2013 Kennard-Stone algorithm (KS) for data partition A state-of-the-art algorithm for partitioning a data into a training set and a test set Author: Hongdong Li mathematics, chemometrics, selecting representit... 31 0
10 Jan 2011 Elastic Component Regression (ECR) for uncovering the path from PCR to PLS ECR is a newly developed method for high dimensional data compression and regression. Author: Hongdong Li statistics, chemometrics, ecr, pcr, pls, path 12 0
Comments and Ratings by Hongdong
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14 Apr 2013 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li

Hi,this package has been updated to the libPLS toolbox in my new submission here.

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14 Apr 2013 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li Li, Hongdong

Hi,this package has been updated to the libPLS toolbox in my new submission here.

24 Mar 2013 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li Luuk

Xiu: I stumbled on the code you're looking for. It's in plscvfold.m;

groups = 1+rem(0:Mx-1,K);
for group=1:K
testk = find(groups==group); calk = find(groups~=group);
Xcal=X(calk,:);ycal=y(calk);
Xtest=X(testk,:);ytest=y(testk);

23 Mar 2013 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li Luuk

@Xiu: I'm not familiar with Bayesian or FDA, but isn't the problem you're describing because the DM2 data is already pretreated/scaled?

Maybe by something like:

for II=1:size(OrinalXcal,1)
Xcal(II,:)=OiginalXcal(II,:)./OriginalYcal(II,1);
Ycal(II,1)=OriginalYcal(II,1)/OriginalYcal(II,1);

end

15 May 2012 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li Xiu

The code has been very helpful. However, I do have a question on the example you included. The test_package_functions.m calls data DM2 which contains two variables Xcal and ycal. The ycal only has numbers either +1 or -1, which works out nicely in the ldapinv.m (performs bayesian approximation or FDA). I don't quite understand it here since I'm not familiar with Bayesian approximation or FDA. When I have my own dataset, which means my y would have numbers other than +/-1, the formation of XX has dimensionality problem. I believe this is due to both B, kp, and kn are empty matrices (matrices of locations of +/-1 elements). The influence of this result extends further into the plslda.m. How should I fix this problem if I want to use my own data? Please help me with this.

Thanks

25 Apr 2011 libPLS: An Integrated Library for Partial Least Squares Regression and Discriminant Analysis chemometrics, metabolomics, model population analysis, variable selection, feature selection Author: Hongdong Li yuna

very helpful,thanks a lot

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