I have tried Random forest (with gridseacrhCV) but did not get good results.
On Tue, May 31, 2016 at 7:18 PM, Jacob Schreiber <jmschreibe...@gmail.com> wrote: > Using the same feature set? How well do other estimators work? (Linear > regression, gradient boosting, etc...) > > On Tue, May 31, 2016 at 11:10 AM, muhammad waseem < > m.waseem.ah...@gmail.com> wrote: > >> This problem has been solved in the literature before, I can post papers. >> >> On Tue, May 31, 2016 at 7:07 PM, Jacob Schreiber <jmschreibe...@gmail.com >> > wrote: >> >>> Do you have any other baselines which you can compare to? It might be >>> helpful in seeing if this is a problem which can be learned. >>> >>> On Tue, May 31, 2016 at 10:47 AM, muhammad waseem < >>> m.waseem.ah...@gmail.com> wrote: >>> >>>> Thanks for your reply. I have day, month, hour, temp, relative >>>> humidity, Wind speed as my input variables. I can't think of any other >>>> dependant variables. It is quite strange to me that I don't get results >>>> after using these input variables. >>>> >>>> On Tue, May 31, 2016 at 4:59 PM, Andrew Holmes < >>>> andrewholme...@icloud.com> wrote: >>>> >>>>> If the problem is that it’s confusing day and night, are you including >>>>> time of day as a parameter? >>>>> >>>>> Best wishes >>>>> Andrew >>>>> >>>>> @andrewholmes82 <http://twitter.com/andrewholmes82> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On 31 May 2016, at 16:55, muhammad waseem <m.waseem.ah...@gmail.com> >>>>> wrote: >>>>> >>>>> Hi All, >>>>> I am trying to train an ANN but until now it is not learning the lower >>>>> values of the training sample. I have tried using different python >>>>> libraries to train ANN. The aim is to predict solar radiation from other >>>>> weather parameters (regression problem). I think the ANN is confusing >>>>> lower >>>>> values (winter/cloudy days) with the night-time values (probably). I have >>>>> tried the following but none of them worked; >>>>> >>>>> 1. Scaling data between different values e.g. [0,1],[-1,1] >>>>> 2. Standardising data to have zero mean and unit variance >>>>> 3. Shuffling the data >>>>> 4. Increasing the training samples (from 3 years to 10 years) >>>>> 5. Using different train functions >>>>> 6. Trying different transfer functions >>>>> 7. Using few input variables >>>>> 8. Varying hidden layers and hidden layers' neurons >>>>> >>>>> Any idea what could be wrong or any directions to try? >>>>> >>>>> Thanks >>>>> Kindest Regards >>>>> Waseem >>>>> _______________________________________________ >>>>> scikit-learn mailing list >>>>> scikit-learn@python.org >>>>> https://mail.python.org/mailman/listinfo/scikit-learn >>>>> >>>>> >>>>> >>>>> _______________________________________________ >>>>> scikit-learn mailing list >>>>> scikit-learn@python.org >>>>> https://mail.python.org/mailman/listinfo/scikit-learn >>>>> >>>>> >>>> >>>> _______________________________________________ >>>> scikit-learn mailing list >>>> scikit-learn@python.org >>>> https://mail.python.org/mailman/listinfo/scikit-learn >>>> >>>> >>> >>> _______________________________________________ >>> scikit-learn mailing list >>> scikit-learn@python.org >>> https://mail.python.org/mailman/listinfo/scikit-learn >>> >>> >> >> _______________________________________________ >> scikit-learn mailing list >> scikit-learn@python.org >> https://mail.python.org/mailman/listinfo/scikit-learn >> >> > > _______________________________________________ > scikit-learn mailing list > scikit-learn@python.org > https://mail.python.org/mailman/listinfo/scikit-learn > >
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