Implement kernel ridge regression

CodingIntermediate⏱ 1 hourClassical MLkernel ridgeimplementationbandwidtheffective dof

Problem

Implement kernel ridge regression with a Gaussian kernel.

Fit a one-dimensional function and visualise the effect of $\sigma$ and $\lambda$ .
Plot the representer expansion term by term and check the terms sum to the fit.
Compute the effective degrees of freedom $\operatorname{tr}(\mathbf K(\mathbf K+n\lambda I)^{-1})$ and relate it to the visual smoothness.
Select $(\sigma,\lambda)$ by cross-validation and compare with the visually best fit.

Implement it, then check the implementation against something you can verify independently.

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