Re: Gaussian process regression
On Thu, 26 Feb 2015 09:59:45 -0800 (PST), jaykim.hui...@gmail.com wrote: 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) [snip] I'm sorry you're not getting help from this normally very helpful group. I'd guess that's because nobody here uses sklearn. Where did you get sklearn? Is it possible that there's an sklearn forum somewhere? I've seen many of this group's regular participants go to great lengths to help people with specialized problems, but for one of those people to help with your problem, he or she would have to find and install sklearn and learn enough about it to generate data sets on which to exercise the code you've provided. That's a lot to ask. Can you lower the activation barrier? -- To email me, substitute nowhere-runbox, invalid-com. -- https://mail.python.org/mailman/listinfo/python-list
Re: Gaussian process regression
On 27.02.2015 18:55, Peter Pearson wrote: On Thu, 26 Feb 2015 09:59:45 -0800 (PST),jaykim.hui...@gmail.com wrote: 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) [snip] I'm sorry you're not getting help from this normally very helpful group. I'd guess that's because nobody here uses sklearn. Where did you get sklearn? Is it possible that there's an sklearn forum somewhere? http://blog.gmane.org/gmane.comp.python.scikit-learn Cheers, Fabien -- https://mail.python.org/mailman/listinfo/python-list
Gaussian process regression
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 -- https://mail.python.org/mailman/listinfo/python-list
