NumPy / SciPy Recipes for Data Science: Kernel Least Squares Optimization (1)

Submitted by
christianbauckhage on 03 April 2015

In this note, we show that least squares optimization is amenable to the kernel trick. This provides great flexibility in model fitting and we consider examples that illustrate this. In particular, we will discuss how kernel functions can implicitly introduce non-linearity into the least squares method.

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