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

[muhammad waseem]

@Chris: Thanks for your reply, I will try to contact them.

@Andrew Howe: I think I will try to add number of sunshine hours as another
variable, which will be the same value for the whole day.

Thanks
Kindest Regards
Waseem


On Wed, Jun 1, 2016 at 2:01 PM, Andrew Howe <ahowe42 at gmail.com> wrote:

> 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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>>
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