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

[Andrew Howe]

What about adding a simple binary night / day flag?  While it's less
information than hour, it will provide a distinct cutoff for the network to
use.

Andrew

<~~~~~~~~~~~~~~~~~~~~~~~~~~~>
J. Andrew Howe, PhD
Editor-in-Chief, European Journal of Mathematical Sciences
Executive Editor, European Journal of Pure and Applied Mathematics
www.andrewhowe.com
http://www.linkedin.com/in/ahowe42
https://www.researchgate.net/profile/John_Howe12/
I live to learn, so I can learn to live. - me
<~~~~~~~~~~~~~~~~~~~~~~~~~~~>

On Tue, May 31, 2016 at 8:47 PM, muhammad waseem <m.waseem.ahmad at 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 <andrewholmes82 at 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.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
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