There is a whole lot of literature on mapping data onto higher dimensional spaces. Another closely related and popular term is the kernel trick. See top publications of Prof. Bernhard Schölkopf for example. In this short entry, I start with a linearly non-separable data in 2D. I use a mapping to 3D for this data and visualize. … Continue reading Toy Kernels →