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Topic: Principal Component Analysis Alternatives for low sample to
dimensions ratio

Replies: 5   Last Post: Apr 11, 2013 11:26 PM

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Ray Koopman

Posts: 3,383
Registered: 12/7/04
Re: Principal Component Analysis Alternatives for low sample to
dimensions ratio

Posted: Apr 11, 2013 11:26 PM
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On Apr 10, 8:44 pm, Krevin <kbro...@gmail.com> wrote:
> Anyone know of good alternative methods to PCA when you have too many
> dimensions compared to samples?
>
> If I have 2000 variables and 300 samples, I cannot properly use PCA.
>
> I'm looking for something that can minimize false positive separation
> of sample points without needing to reduce my number of variables.
>
> Thanks,
> Krevin


There is a variant of Partial Least Squares that does Structural
Equation Modeling that probably could be adapted to look like PCA.
See http://users.stat.umn.edu/~sandy/courses/8801/articles/pls.pdf



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