Yes, it has poor performance (higher errors) on lower values. I have tried random forest but as I mentioned it did not give good results either, I can try SVR.
Kindest Regards Waseem On Tue, May 31, 2016 at 6:54 PM, Andrew Holmes <[email protected]> wrote: > When you say it’s not learning ‘lower values’, does that mean the model > has good predictions on high values in the test set, but poor performance > on the low ones? > > Have you tried simpler models like tree, random forest and svm as a > benchmark? > > Best wishes > Andrew > > @andrewholmes82 <http://twitter.com/andrewholmes82> > > > > > > > > > On 31 May 2016, at 16:59, Andrew Holmes <[email protected]> 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 <[email protected]> > 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 > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > > > > > _______________________________________________ > scikit-learn mailing list > [email protected] > https://mail.python.org/mailman/listinfo/scikit-learn > >
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