Re: [shogun] ISSUE #3847

[sahil chaddha]

Python meta examples can't import WrappedObjectArray. I tried the build
from my feature branch as well as develop branch. I don't know why is it
happening.

test 691
Start 691:
generated_python-evaluation-cross_validation_mkl_weight_storage

691: Test command: /usr/bin/python
"/media/sahil333/MostlyHere/GSOC/shogun/build/examples/meta/python/evaluation/cross_validation_mkl_weight_storage.py"
691: Environment variables:
691:  GDB="gdb -x /media/sahil333/MostlyHere/GSOC/shogun/src/.gdb --args"
691:  PYTHON=/usr/bin/python
691:  PYTHONPATH=/usr/local/lib/python2.7/dist-packages:
691:  LD_LIBRARY_PATH=/usr/local/lib:
691: Test timeout computed to be: 1500
691: Traceback (most recent call last):
691:   File
"/media/sahil333/MostlyHere/GSOC/shogun/build/examples/meta/python/evaluation/cross_validation_mkl_weight_storage.py",
line 16, in 
691: from shogun import WrappedObjectArray
691: ImportError: cannot import name WrappedObjectArray


*Sahil Chaddha*
Fourth Year Undergraduate Student
Department of Metallurgy and Materials Engineering
IIT Kharagpur, West Bengal - 721302
+91-7872705997,  LinkedIn
 | Github


On Sun, Aug 13, 2017 at 5:37 PM, sahil chaddha  wrote:

> This is a follow-up regarding last mail.
>
> *Sahil Chaddha*
> Third Year Undergraduate Student
> Department of Metallurgy and Materials Engineering
> IIT Kharagpur, West Bengal - 721302
> +91-7872705997,  LinkedIn
>  | Github
> 
>
> On Fri, Aug 11, 2017 at 1:34 AM, sahil chaddha 
> wrote:
>
>> I wrote an implementation by choosing linear divide points, c[n/k], and a
>> member variable (h), to ensure test set have h(default 1) future from time
>> t.
>> But with these implementation, train set size becomes as low as [n/k].
>> Should I implement another variant to increase train set size?
>>
>>
>> PS : Heiko, can you please also elaborate or provide link for third
>> point?
>>
>> On Aug 8, 2017 10:25 PM, "Heiko Strathmann" 
>> wrote:
>>
>>> The splitting for the time series could be
>>>
>>> -deterministic, that is in increasing window sizes to the past: train
>>> set is everything up to point t, test set is everything from t.
>>> -there could be variants on this that are limiting the sizes of the folds
>>> -shuffling "blocks" that are approximately independent (i.e. the time
>>> series forgets its past after t observations), this should re-use existing
>>> code on shuffling
>>>
>>> 2017-08-08 16:34 GMT+01:00 sahil chaddha :
>>>
 I read the implementation of cross-validation splitting and
 cross-validation. The build_subset() implements a random process to build
 the subsets and thus, makes sense to run evaluate_one_run() several times
 in cross-validation. Does the time-series split also require random
 process? And also, generate_subset_indices() is like test set and
 generate_subset_inverse() is like train set. So, to respect the time, the
 subsets are bound to have a non-empty intersection. Am I right?

 *Sahil Chaddha*
 Third Year Undergraduate Student
 Department of Metallurgy and Materials Engineering
 IIT Kharagpur, West Bengal - 721302
 +91-7872705997 <+91%2078727%2005997>,  LinkedIn
  | Github
 

 On Mon, Aug 7, 2017 at 1:56 PM, Fernando J. Iglesias García <
 fernando.iglesi...@gmail.com> wrote:

> Welcome Sahil!
>
> Great that you have already successfully set up your dev environment.
>
> For this particular task, I think it will be useful to get familiar
> with Shogun's cross-validation. You could start by checking the related
> examples (like this one
> ).
> Then, you can get into understanding how the splitting strategy is
> implemented internally (you can find the implementation by following the
> appropriate include file from the example). You will also need to
> understand details about the time-series splitting strategy, the links in
> the github issue will be useful for this.
>
> After, you should be ready to start implementing the time-series
> splitting. Let us know how it goes.
>
> Hope that helps!
>
> Cheers,
> Fernando.
>
> On 5 August 2017 at 20:29, sahil chaddha  wrote:
>
>> Ma'am/Sir,
>>
>>I want to work on this https://github.com/shogun
>> -toolbox/shogun/issues/3847. But I have no idea where to start. I am
>> new to such big projects. Can anyone guide me through it? I have already
>> setup the environment, ran tests and examples successfully.

Re: [shogun] ISSUE #3847

[sahil chaddha]

I read the implementation of cross-validation splitting and
cross-validation. The build_subset() implements a random process to build
the subsets and thus, makes sense to run evaluate_one_run() several times
in cross-validation. Does the time-series split also require random
process? And also, generate_subset_indices() is like test set and
generate_subset_inverse() is like train set. So, to respect the time, the
subsets are bound to have a non-empty intersection. Am I right?

*Sahil Chaddha*
Third Year Undergraduate Student
Department of Metallurgy and Materials Engineering
IIT Kharagpur, West Bengal - 721302
+91-7872705997,  LinkedIn
 | Github


On Mon, Aug 7, 2017 at 1:56 PM, Fernando J. Iglesias García <
fernando.iglesi...@gmail.com> wrote:

> Welcome Sahil!
>
> Great that you have already successfully set up your dev environment.
>
> For this particular task, I think it will be useful to get familiar with
> Shogun's cross-validation. You could start by checking the related examples
> (like this one
> ).
> Then, you can get into understanding how the splitting strategy is
> implemented internally (you can find the implementation by following the
> appropriate include file from the example). You will also need to
> understand details about the time-series splitting strategy, the links in
> the github issue will be useful for this.
>
> After, you should be ready to start implementing the time-series
> splitting. Let us know how it goes.
>
> Hope that helps!
>
> Cheers,
> Fernando.
>
> On 5 August 2017 at 20:29, sahil chaddha  wrote:
>
>> Ma'am/Sir,
>>
>>I want to work on this https://github.com/shogun
>> -toolbox/shogun/issues/3847. But I have no idea where to start. I am new
>> to such big projects. Can anyone guide me through it? I have already setup
>> the environment, ran tests and examples successfully.
>>
>> *Sahil Chaddha*
>> Fourth Year Undergraduate Student
>> Department of Metallurgy and Materials Engineering
>> IIT Kharagpur, West Bengal - 721302
>> +91-7872705997 <+91%2078727%2005997>,  LinkedIn
>>  | Github
>> 
>>
>
>

Re: [shogun] ISSUE #3847

[Fernando J . Iglesias García]

Welcome Sahil!

Great that you have already successfully set up your dev environment.

For this particular task, I think it will be useful to get familiar with
Shogun's cross-validation. You could start by checking the related examples
(like this one
).
Then, you can get into understanding how the splitting strategy is
implemented internally (you can find the implementation by following the
appropriate include file from the example). You will also need to
understand details about the time-series splitting strategy, the links in
the github issue will be useful for this.

After, you should be ready to start implementing the time-series splitting.
Let us know how it goes.

Hope that helps!

Cheers,
Fernando.

On 5 August 2017 at 20:29, sahil chaddha  wrote:

> Ma'am/Sir,
>
>I want to work on this https://github.com/shogun-toolbox/shogun/issues/
> 3847. But I have no idea where to start. I am new to such big projects.
> Can anyone guide me through it? I have already setup the environment, ran
> tests and examples successfully.
>
> *Sahil Chaddha*
> Fourth Year Undergraduate Student
> Department of Metallurgy and Materials Engineering
> IIT Kharagpur, West Bengal - 721302
> +91-7872705997 <+91%2078727%2005997>,  LinkedIn
>  | Github
> 
>

[shogun] ISSUE #3847

[sahil chaddha]

Ma'am/Sir,

   I want to work on this
https://github.com/shogun-toolbox/shogun/issues/3847. But I have no idea
where to start. I am new to such big projects. Can anyone guide me through
it? I have already setup the environment, ran tests and examples
successfully.

*Sahil Chaddha*
Fourth Year Undergraduate Student
Department of Metallurgy and Materials Engineering
IIT Kharagpur, West Bengal - 721302
+91-7872705997,  LinkedIn
 | Github