Gaussian process regression
jaykim.huijae at gmail.com
jaykim.huijae at gmail.com
Thu Feb 26 12:59:45 EST 2015
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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