Fernando Quivira

2016-06-20 15:04:19 UTC

Hi

I'm trying to replicate some dimension reduction results computed with

Matlab's plsregress using sklearn's PLSRegression. However, I'm finding

that the output of the transform method in sklearn's PLSRegression differs

from Matlab results by a constant scale factor across each component

(constant across features but different across components).

I used some dummy data that I could load in Matlab to test this. I found

that if I normalized (with zscores) the sklearn and Matlab's outputs, I got

the same results (see attached figures). I have attached the code that can

replicate this. The whole test can be run from testPLS.m (you need matlab

2014+).

I'm using python3.5 64bit in Windows with the Anaconda environment and

sklearn 0.17.1-np110py35_1

Thanks

- Fernando

I'm trying to replicate some dimension reduction results computed with

Matlab's plsregress using sklearn's PLSRegression. However, I'm finding

that the output of the transform method in sklearn's PLSRegression differs

from Matlab results by a constant scale factor across each component

(constant across features but different across components).

I used some dummy data that I could load in Matlab to test this. I found

that if I normalized (with zscores) the sklearn and Matlab's outputs, I got

the same results (see attached figures). I have attached the code that can

replicate this. The whole test can be run from testPLS.m (you need matlab

2014+).

I'm using python3.5 64bit in Windows with the Anaconda environment and

sklearn 0.17.1-np110py35_1

Thanks

- Fernando