Kernel PCA Part 1: Polynomials without the Kernels
NIR news2015Vol. 26(5), pp. 20–21
Citations Over TimeTop 23% of 2015 papers
Abstract
T his is the first of two columns that will attempt to describe kernel PCA. This is a computationally efficient way of carrying out a nonlinear principal component analysis. The computationally efficient bit using the kernels requires some quite fancy mathematics, which I will attempt to explain in part 2, but for one kernel, the polynomial one, it is possible to get effectively the same results in a much simpler way, and this is what will be done here.
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