Gaussian process regression

Newsgroups	comp.lang.python
Date	2015-02-26 09:59 -0800
Message-ID	<5d2cd3fd-9d63-4e79-af1c-965d50145801@googlegroups.com> (permalink)
Subject	Gaussian process regression
From	jaykim.huijae@gmail.com

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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

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Gaussian process regression jaykim.huijae@gmail.com - 2015-02-26 09:59 -0800
  Re: Gaussian process regression Peter Pearson <pkpearson@nowhere.invalid> - 2015-02-27 17:55 +0000
    Re: Gaussian process regression Fabien <fabien.maussion@gmail.com> - 2015-02-27 19:33 +0100

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