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Support Vector Machine refers to "a set of related supervised learning methods that analyze data and recognize patterns, used for classification and regression analysis."
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votes
The difference of kernels in SVM?
Relying on basic knowledge of reader about kernels.
Linear Kernel: $K(X, Y) = X^T Y$
Polynomial kernel: $K(X, Y) = (γ\cdot X^T Y + r)^d , γ > 0$
Radial basis function (RBF) Kernel: $K(X, Y) = \ex …