Machine Learning, Kernel, Hilbert Space, Mercer Theorem.
easy to observe the trick in a higher dimension. Original points in 1D Transformed points in 2D We will consider an embedding map φ. The choice of the map φ aims to convert the nonlinear relations into linear ones. After mapping it to the higher dimensions, what we need is the dot product between