[scikit-learn] Ordinary Least Square Regression Under-determined system.

[Andreas Mueller]

PLS is not the same as PCR, right? Why did you expect them to perform 
the same?
LinearRegression is just calling scipy.linalg.lstsq 
https://docs.scipy.org/doc/scipy/reference/generated/scipy.linalg.lstsq.html
as you can see here: 
https://github.com/scikit-learn/scikit-learn/blob/14031f6/sklearn/linear_model/base.py#L539
I expect that produces the minimum norm solution though I'm not familiar 
with the exact solver.



On 04/16/2017 01:15 PM, Joshua Mannheimer wrote:
> Hi all,
>
> So I am trying to write a Principle Components Regression 
> implementation in Python to match the PLS package in R. I am getting 
> better results in R so I am trying to figure out where the discrepancy 
> was. The data I am using is way undetermined where n_features ~ 50,000 
> and n_samples ~ 500 thus why PCR is necessary. Just to see what would 
> happen I used sklearn.LinearRegression on the original 500 X 50000 
> dataset. I expected I would get an error message stating the the 
> system was not solvable but it worked and I got an answer that was at 
> least on par with the PCR solution. So I am wondering how it is 
> possibly solving this system if anybody knows. Thanks
>
> -- 
> Joshua D. Mannheimer M.E.
> Biomedical Engineering Ph.d Student
> Flint Animal Cancer Research Center
> Office: A 259 CSU Veterinary Campus
> Colorado State University
> (970)-389-3951
> jmannhei at rams.colostate.edu <mailto:jmannhei at rams.colostate.edu>
>
>
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