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 <module>
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
<https://www.linkedin.com/in/sahil-chaddha-a0a376b7/> | Github
<https://github.com/Sahil333>
On Sun, Aug 13, 2017 at 5:37 PM, sahil chaddha <[email protected]> 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
> <https://www.linkedin.com/in/sahil-chaddha-a0a376b7/> | Github
> <https://github.com/Sahil333>
>
> On Fri, Aug 11, 2017 at 1:34 AM, sahil chaddha <[email protected]>
> 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" <[email protected]>
>> 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 <[email protected]>:
>>>
>>>> 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
>>>> <https://www.linkedin.com/in/sahil-chaddha-a0a376b7/> | Github
>>>> <https://github.com/Sahil333>
>>>>
>>>> On Mon, Aug 7, 2017 at 1:56 PM, Fernando J. Iglesias García <
>>>> [email protected]> 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
>>>>> <https://github.com/shogun-toolbox/shogun/blob/develop/examples/undocumented/libshogun/splitting_standard_crossvalidation.cpp>).
>>>>> 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 <[email protected]> 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
>>>>>> <https://www.linkedin.com/in/sahil-chaddha-a0a376b7/> | Github
>>>>>> <https://github.com/Sahil333>
>>>>>>
>>>>>
>>>>>
>>>>
>>>
>
