Machine Learning, Kernel, Hilbert Space, Mercer Theorem.
. xₙ and we are using a kernel k to evaluate the dot product in feature space with feature map ψ than we define gram matrix as G_ {i,j} = Dot Product(φ(xᵢ ), φ(xⱼ ))= k(xᵢ , xⱼ) This matrix is also called the kernel matrix. This matrix is symmetric, and it contains all the information needed to