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Does anybody know if this is true for other machine learning techniques?



The same arguments as in the original Cybenko paper, or the Stone-Weierstrass theorem, lend support to the idea that SVMs are universal approximators (with most typical kernels). This has been proven by a couple of authors.

I'm not aware of universal approximation results for random forests, but since they have the same general construction, this would not be surprising.




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