sklearn.svm.SVC is based on libsvm so no need to compare the two.
sklearn.svm.LinearSVC is based on liblinear.
In theory, SVMs do what SVMs do: maximize a classification margin given
some tolerance for wrong classifications. Apart from numerical errors in
optimization, I don't see how accuracy scores can be different if the
algorithm has converged (with stress on that last word). The numerical
errors incurred shouldn't ever change a prediction that drastically.
On Tue, Mar 3, 2015 at 9:53 PM, Pagliari, Roberto <rpagli...@appcomsci.com>
wrote:
> Has anybody ever compared Matlab SVM vs sklearn or libsvm?
>
>
>
> It’d be interested to know about the difference in accuracy between them
> (using the same dataset and similar settings).
>
>
>
> Thank you,
>
>
>
>
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