On 2012-05-24, at 10:27 AM, Ian Goodfellow <[email protected]> wrote:

> I think I've figured out what the problem is, but someone familiar
> with the code should confirm.
> I think SVC is always using a decision function based on support
> vectors, even though in the case of a linear kernel it is
> computationally cheaper to just do one dot product in feature space.

I think this is how libsvm will always behave, yes, though SKL's predict() 
could special case for kernel == "linear".
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