Thanks Alexandre,
I'm not sure that's the case for me. Our data is wavelength in rows and
time in columns. Say an experiment takes 500 timepoints. I'd like to run
PCA along the time variable (axis=1) and be able to represent my data as a
wavelength vs. k_components matrix, where n << k_timepoin
hi,
proper PCA is run on centered data (axis=0) otherwise it's a truncated SVD.
I seams you want a PCA on X.T (X transposed).
HTH
Alex
On Tue, Jul 22, 2014 at 3:14 AM, Adam Hughes wrote:
> Hi,
>
> I'm really enjoying scikit learn and looking to add a lite version of PCA to
> some programs I'm
Hi,
I'm really enjoying scikit learn and looking to add a lite version of PCA
to some programs I'm working on, derived mostly from the decomposition.PCA
class. I have a few quick questions, and really would appreciate some help
from the experts.
First, the PCA class is designed to operate on dat
