On Thu, May 24, 2012 at 11:27 PM, 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.
>
>
Correct. I guess we just assumed that people would use LinearSVC when using
a linear kernel...
A PR implementing decision_function and predict based on coef_ would be
welcome.
Mathieu
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