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

[Nicolas Hug]

Hi Mahmood,

There are different pieces of info that you can get from PCA:

1. How important is a given PC to reconstruct the entire dataset -> This 
is given by explained_variance_ratio_ as Guillaume suggested

2. What is the contribution of each feature to each PC (remember that a 
PC is a linear combination of all the features i.e.: PC_1 = X_1 . 
alpha_11 + X_2 . alpha_12 + ... X_m . alpha_1m). The alpha_ij are what 
you're looking for and they are given in the components_ matrix which is 
a n_components x n_features matrix.

Nicolas

On 1/22/21 9:13 AM, Mahmood Naderan 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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