On 26/02/15 18:04, Huijae wrote:
Hi, I am trying to use Gaussian process regression for Near Infrared spectra. I
have reference data(spectra), concentrations of reference data and sample data,
and I am trying to predict concentrations of sample data. Here is my code.
from sklearn.gaussian_process import GaussianProcess gp = GaussianProcess()
gp.fit(reference, concentration) concentration_pred = gp.predict(sample) The
results always gave me the same concentration even though I used different
sample data. When I used some parts of reference data as sample data, it
predicted concentration well. But whenever I use different data than reference
data, it always gave me the same concentration. Can I get some help with this
problem? What am I doing wrong? I would appreciate any help. Thanks, Jay
As you can probably see, your code did not make it through
in readable form as HTML.
Can you please repost using plain text?
Also this list is aimed at beginners to Python using the standard library.
You are evidently using some kind of third party library - SciPy maybe?
If so you may get a better response on the SciPy support forums
where more people are likely to be familiar with your issues.
However, once we can see the code, some members here do use
Python in science/math so might be able to help.
--
Alan G
Author of the Learn to Program web site
http://www.alan-g.me.uk/
http://www.amazon.com/author/alan_gauld
Follow my photo-blog on Flickr at:
http://www.flickr.com/photos/alangauldphotos
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