Re:Clear animation on how the SVM "kernel trick" works
by jules on Wednesday April 28, 2010 @10:15AM
(#1301587)
Can you give a kernel function that would let you fit a circle with variable position and radius? The examples always use a fixed position.
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Re:Clear animation on how the SVM "kernel trick" works
by ajj on Wednesday April 28, 2010 @05:36PM
(#1302837)
The Radial Basis Function kernel K(x,y) = exp(-(x-y)^2/gamma) is a very general kernel function that can get you this.
Finally, whether you actually get such a classifier depends on your data, and as I had mentioned setting the parameters (like gamma) is not very straightforward. Typically you may have to try with various values and see what works for your data.
Train your SVM (or any kernel method) and see what classifier it gives (run the classifier on data points near the boundary you want to detect to see where the exact boundary lies). This would only be to see how the classification function looks like.