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
_______________________________________________
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
https://mail.python.org/mailman/listinfo/tutor
