Alternatively you could look at the output of "decision_function" in LinearSVC. These do not represent probabilities, though.
Andy ----- Ursprüngliche Mail ----- Von: "Gael Varoquaux" <[email protected]> An: [email protected] Gesendet: Donnerstag, 9. August 2012 05:50:14 Betreff: Re: [Scikit-learn-general] LinearSVC best match On Thu, Aug 09, 2012 at 01:02:21AM +0000, Abhi wrote: > I am using sklearn.svm.LinearSVC for document classification and I get a > good accuracy[98%] on predict. Is there a way to find the confidence of match > (like predict_proba() in SGDClassifier)? Not simply using LinearSVC: liblinear does not implement the mechanism need to estimate a confidence interval. You could use 'SVC(kernel="linear", probability=True)'. HTH, Gael ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general ------------------------------------------------------------------------------ Live Security Virtual Conference Exclusive live event will cover all the ways today's security and threat landscape has changed and how IT managers can respond. Discussions will include endpoint security, mobile security and the latest in malware threats. http://www.accelacomm.com/jaw/sfrnl04242012/114/50122263/ _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
