PCA principal component analysis

[myk]

Don't really need a tool.  Just:

a)  "centre" your data (translate for zero mean and scale for unity 
variance);
b)  do svd (in NumPy I think) on the data set resulting from a);
c)  eigenvectors are columns of U and eigenvalues are diagonal of S.  
PCA scores are just the values in the columns of U i.e. 1st column is 
first PC scores, etc.

You have much more flexibility if you don't use a "package".  HTH

majb

sebastien wrote:

>Hi,
>
>Is there any PCA analysis tools for python ?
>If it does, do you have any idea on how well it would scale ?
>
>I have already seen PyClimate (but it is not available for Windows
>which will be one of the target). Is there some LAPACK like packages ?
>
>Thanks for reading this mail.
>
>Sebastien.
>  
>