# Approximating a predictor with a kernel

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"?

Thanks.