Hi Alexis. That must be it! Crazy. We should definitely point this out in the docs somewhere. Not sure how I overlooked that. Thanks a lot!
Andy On 08/21/2012 10:52 AM, Alexis Mignon wrote:
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] <mailto:[email protected]>>On Sun, Aug 12, 2012 at 6:53 PM, Andreas Mueller <[email protected] <mailto:[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 ------------------------------------------------------------------------------ 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] <mailto:[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
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