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I am trying to do a grid search for a polynomial kernel. I have used the normal grid search on polynomial kernels which is wrong. I only varied $c$ and $\gamma$... but I need to vary $a$ and $b$... Is there any fast method to do grid search for polynomial kernels?

Polynomial kernel: $K(x_i, x_j) = (\gamma x_i x_j + a)^b,\quad \gamma > 0$

Any suggestions or any corrections as well are welcome.

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What is c? There's no c in your equation. – onestop Mar 16 '12 at 17:58
C is the amount of misclassification.... it is for all kernels... – lakesh Mar 16 '12 at 18:00

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I woud recommend a grid search over integer values of b, and for each value of b perform a search for C, gamma and a using the Nelder-Mead simplex algorithm, which is a standard numerical optimiser that does not rely on gradient information and works fairly well (it is the fminsearch function in MATLAB).

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I have one suggestion, not sure whether correct or wrong? Why don't u find the best value for c and gamma first, then with that value, try different values for b? – lakesh Mar 16 '12 at 18:02
changing b changes the kernel induced feature space, you you can expect it to change the optimal value of the other hyper-parameters as well as they are often correlated. – Dikran Marsupial Mar 16 '12 at 18:06
if you show an example fo fminsearch using MATLAB, it would be really useful... thanks... – lakesh Mar 16 '12 at 18:15
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Without being familiar with the SVM package you are using I can't give any better information than the fminsearch help message. I use my own matlab software, which has model selection built in, but unfortunately has no manual, see theoval.cmp.uea.ac.uk/projects/gkm – Dikran Marsupial Mar 16 '12 at 18:25
i am using libsvm... – lakesh Mar 16 '12 at 18:26
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