Hi Andy,
Thanks for the fast response!
> Could you please say which version of sklearn you are using?
>
I am using sklearn version 0.11
About the nans, I have no idea.
>
Yep the nans is where the problem is.
> Have you tried to not do your own whitening, i.e. whiten=True?
>
Yes and in that case ICA works just fine.
Thanks,
Igor
On 06/27/2012 10:50 PM, Igor Nikolskiy wrote:
Hello all,
I've got a FastICA question. I am interested in doing my own whitening of
the data before feeding it to fastICA, but I'm running into trouble. Here's
the code:
from pylab import *
from pandas import *
from sklearn.decomposition import FastICA, PCA
ms2= read_csv('L-Glu.csv', index_col= 0)
ms2_centered= ms2-ms2.mean()
ms2_whitened= PCA().fit(ms2_centered.T).transform(ms2_centered.T)
ica= FastICA(n_components= 2, whiten= False)
fit= ica.fit(ms2_whitened)
sources= abs(ica.transform(ms2_whitened))
The ms2_whitened matrix looks good - it is the right shape, and looks
reasonable with imshow. The problem is when I look at fit.sources_ there
are more than 2 sources and all of the source values are nan.
Does anyone know what I could be doing wrong?
Thanks in advance,
Igor
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