Machine Learning, Kernel, Hilbert Space, Mercer Theorem.
features nor a requirement of the mapping φ. We can now directly calculate the dot product in the higher dimension by our original features. This is known as the kernel trick. Example Suppose we have 2 vectors x = (1, 2, 3) and y = (4, 5, 6). We wish to compute their dot product in some higher