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Old 02-22-2013, 11:25 AM is offline
Join Date: Jul 2012
Posts: 17
Default Re: Why not use soft margin SVM everytime?

Thank you very much, Professor. You are right, the QP solution would probably not return anything reasonable.
As I mentioned earlier, we don't know about the linear separability of the data, or at least, we can't know without looking, which would amount to snooping.
And it is in those cases that I feel that the technique of cross validation is invaluable, as it can help one choose among the different kinds of models.
In one of your earlier lectures, you had indicated that the linear models work surprisingly well in most real cases, and we even had a linear model (logistic regression) to handle noise. Do SVMs work well in noise, too? If they do, I wonder why anyone would use the traditional linear models when one can use the power of SVMs.
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