Assume that some predictor $f$ is a kernel machine, but the kernel function $K(\cdot, \cdot)$ is unknown. Is there a way to recover the kernel $K(\cdot, \cdot)$ that "best approximates" $f$? is there an established notion of a "best-approximating kernel"?



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