I've heard the expression "Gaussian kernel" in several contexts (e.g. in the kernel trick used in SVM). A Gaussian kernel usually refers to a Gaussian function (that is, a function similar to the probability density function of a Gaussian distribution) that is used to measure the similarity between two vectors (or numbers).

Why is this Gaussian function called a "kernel"? Why not just calling it a Gaussian (similarity) function? Does it have something to do with the kernel of a linear transformation?


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