Artificial neural network not learning lower values of the training sample
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
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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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 <andrewholmes82@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@gmail.com <mailto:m.waseem.ahmad@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@python.org <mailto:scikit-learn@python.org> https://mail.python.org/mailman/listinfo/scikit-learn
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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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@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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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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@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@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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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I have tried Random forest (with gridseacrhCV) but did not get good results. On Tue, May 31, 2016 at 7:18 PM, Jacob Schreiber <jmschreiber91@gmail.com> wrote:
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@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@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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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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 <andrewholmes82@icloud.com> 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 <andrewholmes82@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
Is the training set unbalanced between high and low values? Ie, many more of the high ones? Best wishes Andrew @andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:00, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
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 <andrewholmes82@icloud.com <mailto:andrewholmes82@icloud.com>> 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 <andrewholmes82@icloud.com <mailto:andrewholmes82@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@gmail.com <mailto:m.waseem.ahmad@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@python.org <mailto:scikit-learn@python.org> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn>
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Please find below results for ANN . [image: Inline image 1] On Tue, May 31, 2016 at 8:00 PM, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
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 <andrewholmes82@icloud.com> 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 <andrewholmes82@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
I try to balance it out, the dataset is very periodic type (similar behaviour in an year) On Tue, May 31, 2016 at 8:01 PM, Andrew Holmes <andrewholmes82@icloud.com> wrote:
Is the training set unbalanced between high and low values? Ie, many more of the high ones?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:00, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
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 <andrewholmes82@icloud.com> 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 <andrewholmes82@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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A previous commenter asked about the published research you mentioned in which this was working ok. If you’re using the same data as them, could you try to replicate their results first? Best wishes Andrew @andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:05, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
I try to balance it out, the dataset is very periodic type (similar behaviour in an year)
On Tue, May 31, 2016 at 8:01 PM, Andrew Holmes <andrewholmes82@icloud.com <mailto:andrewholmes82@icloud.com>> wrote: Is the training set unbalanced between high and low values? Ie, many more of the high ones?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:00, muhammad waseem <m.waseem.ahmad@gmail.com <mailto:m.waseem.ahmad@gmail.com>> wrote:
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 <andrewholmes82@icloud.com <mailto:andrewholmes82@icloud.com>> 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 <andrewholmes82@icloud.com <mailto:andrewholmes82@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@gmail.com <mailto:m.waseem.ahmad@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@python.org <mailto:scikit-learn@python.org> https://mail.python.org/mailman/listinfo/scikit-learn <https://mail.python.org/mailman/listinfo/scikit-learn>
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It's not the same data (different locations) but I have tried to use same input and output variables. Thanks Waseem On Wed, Jun 1, 2016 at 12:02 PM, Andrew Holmes <andrewholmes82@icloud.com> wrote:
A previous commenter asked about the published research you mentioned in which this was working ok. If you’re using the same data as them, could you try to replicate their results first?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:05, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
I try to balance it out, the dataset is very periodic type (similar behaviour in an year)
On Tue, May 31, 2016 at 8:01 PM, Andrew Holmes <andrewholmes82@icloud.com> wrote:
Is the training set unbalanced between high and low values? Ie, many more of the high ones?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:00, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
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 <andrewholmes82@icloud.com
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 <andrewholmes82@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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Experienced machine learning people usually start by trying to exactly replicate what the paper did, using exactly the same data, and exactly the same methods, and if possible, even exactly the same software. It is very comforting if you can do this, because you can then go ahead and make changes, secure in the knowledge that the reasons for any changes in output are due to the changes you made, and not to small mistakes in data preparation, tool arguments or something. So it is a good plan to start by seeing whether you can arrange to have the same setup as the writers of the original paper. It is polite to try to do this on your own if you can (and the effort is a useful learning experience, usually) Maybe the data and/or software is publicly available. If not, authors are often willing and able to share material privately, so you could write to them and ask for help. Since you are showing interest in their work, they will want to help if they can. And if they do, you have the beginnings of a useful personal connection. The only pre-condition is that you should (again as matter of politeness) first make an honest attempt to replicate their work, and make sure you really understand it. After you have done that, asking for help is appropriate. Generally speaking, the time to ask questions on a public forum like scikit-learn is also after you have done all you can to solve your problem. Best wishes Chris On 1 June 2016 at 13:05, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
It's not the same data (different locations) but I have tried to use same input and output variables.
Thanks Waseem
On Wed, Jun 1, 2016 at 12:02 PM, Andrew Holmes <andrewholmes82@icloud.com> wrote:
A previous commenter asked about the published research you mentioned in which this was working ok. If you’re using the same data as them, could you try to replicate their results first?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:05, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
I try to balance it out, the dataset is very periodic type (similar behaviour in an year)
On Tue, May 31, 2016 at 8:01 PM, Andrew Holmes <andrewholmes82@icloud.com
wrote:
Is the training set unbalanced between high and low values? Ie, many more of the high ones?
Best wishes Andrew
@andrewholmes82 <http://twitter.com/andrewholmes82>
On 31 May 2016, at 20:00, muhammad waseem <m.waseem.ahmad@gmail.com> wrote:
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 < andrewholmes82@icloud.com> 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 <andrewholmes82@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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@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@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@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@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@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@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
_______________________________________________ scikit-learn mailing list scikit-learn@python.org https://mail.python.org/mailman/listinfo/scikit-learn
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participants (5)
-
Andrew Holmes -
Andrew Howe -
chris brew -
Jacob Schreiber -
muhammad waseem