[SciPy-user] local nonparametric regression, gauss process
Stéfan van der Walt
Tue Feb 24 00:01:23 CST 2009
> Last weekend, I was trying out spatial and sparse. I wrote some
> functions for kernel ridge regression, however I still have
> parameterization problems with the sparse version. But here is the
> dense version, which I tried out with 1000 training points and 2000
> points in total.
> It's not finished but produces some nice graphs to show the local
> regression. If there is interest, I can add this to scipy.
Really nice graphs! This would be very useful for class!
Some trivial comments about spacing in the code:
- Use spaces:
return ssp.minkowski_distance(x[:,np.newaxis,:], y[np.newaxis,:,:], p)
According to the Python PEP I think there should be spaces inside the
indexing brackets too, but that doesn't enhance readability much in
- Keywords do not take spaces
scale=0.5, ridgecoeff = 1e-10, **kwds ):
scale=0.5, ridgecoeff=1e-10, **kwds):
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