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Old 06-13-2013, 10:57 PM
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yaser yaser is offline
Join Date: Aug 2009
Location: Pasadena, California, USA
Posts: 1,478
Default Re: Q14 about linearly separable by SVM

You are right, but in the lectures we did not prove that for the RBF kernel, so it was worth exploring the question at least empirically.

In general, it is conceivable that a transformed infinite-dimensional space may still fail to separate a finite data set. For instance, take every dimension in the infinite-dimensional space to be a (possibly different) linear transformation of the original space. In this case, you would still be implementing just a linear classifier in the original space when you use a linear classifier in the transformed space, so you will fail to separate a set of points that is not linearly separable in the original space.
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