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I am new to MATLAB and to LIBSVM. I got the fact that to use precomputed kernel, you must include sample serial number as the first column of the training and testing data. But importantly what I don't understand is: why would I use precomputed kernels? I am following the script described in LIBSVM and got results for linear and RBF but do not understand the need to use precomputed kernels.

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Whether you need precomputed kernels depends on your metrics of input vectors. Sometimes you may need a different similarity function other than the norm-2 Euclidean distance or the radial basis function between a given feature to all the features from training set.

It is also possible that you need a multiplicative kernel (for example the product of two different kernel functions), which is not feasible by choosing one kernel type from Libsvm. Then writing a precomputed kernel is a good option.

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