[SciPy-User] scipy.interpolate.rbf sensitive to input noise ?
Mon Feb 22 10:23:22 CST 2010
On Mon, Feb 22, 2010 at 10:14, denis <firstname.lastname@example.org> wrote:
> On Feb 22, 3:08 pm, josef.p...@gmail.com wrote:
>> I still don't understand what you mean with "the caller doesn't know
>> A". A is the internally calculated kernel matrix (if I remember
> Yes that's right; how can the caller of Rbf() give a reasonable value
> of "smooth"
> to solve (A - smoothI) inside Rbf, without knowing A ? A is wildly
> different for gauss, linear ... too.
Ah! *That's* what you meant.
> Or do you just shut your eyes and try 1e-6 ?
Basically, yes. You can try different values while watching the
residuals if you want a more rigorous approach. But it really does
work. Try using 'multiquadric' and smooth=0.1.
"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
-- Umberto Eco
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