Another big difference is that the default loss function in Linear SVC is
quadractic with distance to the margin (loss='l2') while it is linear in
SVC.
2012/8/12 Mathieu Blondel <[email protected]>
>
>
> On Sun, Aug 12, 2012 at 6:53 PM, Andreas Mueller <[email protected]
> > wrote:
>
>> Does any one have an explanation for that?
>> Btw, I am using the sparse versions to do some text classification.
>>
>
> One difference is that SVC fits the intercept directly (without using the
> dummy feature trick). So the intercept is not penalized. Howerver, the
> intercept shouldn't change the results much with high dimensional data.
>
> Mathieu
>
>
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