[scikit-learn] Artificial neural network not learning lower values of the training sample

Andrew Matte andrew.matte at gmail.com
Tue May 31 12:42:11 EDT 2016


It sounds like you're right about the low values being connected between
night and clouds. Since there's no seasonality outside of recurrent NNs,
maybe try adding an hour of day variable.
On May 31, 2016 11:57 AM, "muhammad waseem" <m.waseem.ahmad at 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 at python.org
https://mail.python.org/mailman/listinfo/scikit-learn
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-learn/attachments/20160531/8e4705e9/attachment.html>


More information about the scikit-learn mailing list