On 01/18/2012 11:26 PM, Gael Varoquaux wrote:
> On Wed, Jan 18, 2012 at 11:28:52AM +0100, Lars Buitinck wrote:
>    
>> 2012/1/18 Andreas<[email protected]>:
>>      
>>> - Structured SVM / CRF learning
>>>      This is a big one. Not sure what other people think of it.
>>>      I think having a structured SVM would be great.
>>>        
>    
>> +100 on this one...
>>      
> For this, do we need to have our own SVM solver? This is a naive
> question, I have never looked at structured SVM.
>
> This seems to me as a fairly challenging project.
>
>    
This is quite definitely a challenging project.
This should only be given to someone with a fair understanding
of the topic.

There are several options, as I tried to say in my initial post:
1) bindings for an existing structured SVM.
2) bindings for a smart solver with structured svm code by us
3) using SGD for solving. This means "having our own SVM solver"
-- but we already got one in SGDClassifier.
4) write a solver using cutting plane or bundle methods (not quite
sure if this is a good idea)

 From my point of view 1) would be most desirable, though
it is not quite clear how possible it is.
2) and 3) are definitely good options.

4) is probably to much for a GSoC project.

Having this feature might get us a LOT of attention.
But this is really not a simple project.

>> One more thing one my wishlist is semisupervised meta-algorithms, like
>> self-training, co-training, co-boosting. These should not be
>> incredibly hard to implement, but they're still far from trivial.
>>      
> Yes, I think that having a good semi-supervised codebase (including model
> selection) would be a interesting project. What I like about it, is that
> it seems to me as having a gradual difficulty.
>
> Of course, other suggestions are welcome. Maybe we should start a wiki
> page.
>
>    
I would suggest resurrecting / updating the page from last year.

Cheers,
Andy

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