If I define my own method of determining the similarity between two input entities of my Support Vector Machine classifier, and thus define it as my kernel, how do I verify if it is indeed a valid kernel that I can use?
For example, if my inputs are strings, and the kernel I choose is lets say some kind of a string distance metric, how can I decide if I can use it or not for my SVM. I know there are some conditions for a valid SVM kernel. Can anyone tell me what they are and how does one go about verifying those conditions?
Kernel functions must satisfy Mercer’s condition You can also find answers to what you are asking on the stats forum.