Hi Ian.
The multi-class formulation is documented on the page you linked to in 
section
3.2.1.1 under "Multi-class classification".

It should be fairly easy to include an updated version.
I think we try to be pretty up to date with upstream.

Did that answer your questions?

Cheers,
Andy


Am 18.06.2012 17:23, schrieb Ian Goodfellow:
> Now that NIPS is over, does anyone have some time to answer this?
> Also, if I were to make the speedup in libsvm rather than in
> scikits-learn (to fix the problem at the source), how hard would it be
> to pull the new version of libsvm in scikits?
>
> On Fri, May 25, 2012 at 10:32 AM, Ian Goodfellow
> <[email protected]>  wrote:
>> OK. I think I see how to do this for binary classification. For the
>> multiclass one-vs-one classification, how do we map from the decision
>> function to an actual label prediction?
>>
>> The "mathematical formulation" section only documents the binary case
>> as far as I can tell:
>> http://scikit-learn.org/dev/modules/svm.html#svm-mathematical-formulation
>>
>> On Fri, May 25, 2012 at 4:31 AM, Olivier Grisel
>> <[email protected]>  wrote:
>>> 2012/5/25 Gael Varoquaux<[email protected]>:
>>>> On Fri, May 25, 2012 at 10:36:03AM +0900, Mathieu Blondel wrote:
>>>>>     +1 too for precomputing coef_ once for all in fit.
>>>> +1. It seems to simplify everything for little drawback. We'll need to
>>>> document it, of course.
>>> +1 too.
>>>
>>> --
>>> Olivier
>>> http://twitter.com/ogrisel - http://github.com/ogrisel
>>>
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