[SciPy-dev] Scikit for manifold learning techniques
Zachary Pincus
zpincus@stanford....
Thu Dec 6 11:52:49 CST 2007
Attached is a relatively "full featured" implementation of basic PCA
that should be reasonably fast. Perhaps it will be of sue to someone.
Zach
(I hereby put this code in the public domain.)
-------------- next part --------------
A non-text attachment was scrubbed...
Name: pca.py
Type: text/x-python-script
Size: 4131 bytes
Desc: not available
Url : http://projects.scipy.org/pipermail/scipy-dev/attachments/20071206/882ceea0/attachment.bin
-------------- next part --------------
On Dec 6, 2007, at 12:02 PM, Matthieu Brucher wrote:
> (PS. Yes, PCA is easy to implement, but it is also easy to get subtly
> wrong -- I've seen several such -- or to implement in a way that is a
> lot slower than it needs to be. I've spent a while making my
> implementation correct and as fast as possible for both n_data >>
> n_dims and vice-versa. If anyone wants, I'll send the code.)
>
> I already have one with the Fukunaga modification, but I'll gladly
> compare both version to use the best one.
>
> Matthieu
> --
> French PhD student
> Website : http://miles.developpez.com/
> Blogs : http://matt.eifelle.com and http://blog.developpez.com/?
> blog=92
> LinkedIn : http://www.linkedin.com/in/matthieubrucher
> _______________________________________________
> Scipy-dev mailing list
> Scipy-dev@scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-dev
More information about the Scipy-dev
mailing list