Data Science, Kernel Trick, Nonlinear Models, Machine Learning, Data Transformation.
the Nyström method Assuming 𝜅(𝑥,𝑦) to be a function resulting in a kernel-space where the number of kernel-dimensions 𝑑 is bigger than the number of samples 𝑛n, then the maximum rank of 𝐾 must be 𝑚𝑖𝑛(𝑛,𝑑)=𝑛. So, for 𝑛 independent samples in Φ, K is of full rank. Now let’s consider that not all 𝑑d