[scikit-learn] Finding the PC that captures a specific variable

[Julio Antonio Soto]

Hi Mahmood,

I believe your question is answered here: https://stackoverflow.com/questions/22984335/recovering-features-names-of-explained-variance-ratio-in-pca-with-sklearn


> El 22 ene 2021, a las 10:26, Guillaume Lemaître <g.lemaitre58 at gmail.com> escribió:
> 
> 
> I am not really understanding the question, sorry.
> Are you seeking for the `explained_variance_ratio_` attribute that give you a relative value of the eigenvalues associated to the eigenvectors?
> 
>> On Fri, 22 Jan 2021 at 10:16, Mahmood Naderan <mahmood.nt at gmail.com> wrote:
>> Hi
>> I have a question about PCA and that is, how we can determine, a
>> variable, X,  is better captured by which factor (principal
>> component)? For example, maybe one variable has low weight in the
>> first PC but has a higher weight in the fifth PC.
>> 
>> When I use the PCA from Scikit, I have to manually work with the PCs,
>> therefore, I may miss the point that although a variable is weak in
>> PC1-PC2 plot, it may be strong in PC4-PC5 plot.
>> 
>> Any comment on that?
>> 
>> Regards,
>> Mahmood
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> 
> 
> -- 
> Guillaume Lemaitre
> Scikit-learn @ Inria Foundation
> https://glemaitre.github.io/
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