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

[Jacob Schreiber]

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.ahmad at 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 <jmschreiber91 at 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.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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>>>
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>>
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