for that you could take a look at spams
http://spams-devel.gforge.inria.fr (it has python bindings) or use any
general analysis sparsity optimizer and choose the analysis operator to fit
your problem.
hth,
michael
On Tuesday, September 23, 2014, Pedro Cardoso <karudoso+skle...@gmail.com>
wrote:
> Thank you for the reference.
> Do you know of anything with overlapping groups ? This implementation
> seems for the non-overlapping case.
>
> Regards,
> Pedro
>
> 2014-09-23 18:16 GMT+02:00 Michael Eickenberg <
> michael.eickenb...@gmail.com
> <javascript:_e(%7B%7D,'cvml','michael.eickenb...@gmail.com');>>:
>
>> yes, but it hasn't been integrated in scikit learn. take a look at
>> fabian's coordinate descent implementation here
>> https://gist.github.com/fabianp/1423373
>>
>> i think a pr based on this would be very much welcomed
>>
>> michael
>>
>>
>> On Tuesday, September 23, 2014, Pedro Cardoso <karudoso+skle...@gmail.com
>> <javascript:_e(%7B%7D,'cvml','karudoso%2bskle...@gmail.com');>> wrote:
>>
>>> Hi there.
>>>
>>> Was any work been done for Group Lasso Linear classification.
>>>
>>> Thanks for any info.
>>>
>>> references :
>>>
>>> Jerome Friedman, Trevor Hastie, and Robert Tibshiran. 2010. A note on
>>> the group lasso and a sparse group lasso. Technical report, Stanford
>>> University.
>>> Yogatama, Dani, and Noah A. Smith. "Linguistic Structured Sparsity in
>>> Text Categorization." Proc. of ACL. 2014.
>>>
>>
>>
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