[SciPy-dev] SciPy improvements

[Matthieu Brucher]

>
> > Don't scipy have SVMs already ? Perhaps not as modularized at it could
> be ?
>
> It might have something in sandbox, but as far as I'm concerned 'in
> scipy.sandbox' is synonymous with 'not in scipy'.



OK, I read David's answer - BTW, hello Gabou :) -. I'm looking forward to
this, I will probably use SVMs in a near future, as I'm moving toward
Python.

> PPCA is PCA IIRC (Tipping 97, it's part of my Phd thesis),
>
> Yes, pretty much so, just with some variances added into the diagonal
> of the matrix at the right place.


OK, what you want is in fact the implementation of the optimization
algorithm given at the end of the paper ? Because in the standard form of
PPCA, the error variance is isotropic, and in that case, it is tantamount to
simple PCA.

> KPCA is not a big
> > deal if kernels are in a module, and if they have a method taking 2
> > arguments.
>
> Right.  Low level kernel stuff in reusable lib makes a lot of sense.
> If there were a lib of functions with common kernels and their
> derivatives and possibly even 2nd derivatives, that would cover a lot
> of territory.  (I could use some 2nd derivatives right now...)


I would appreciate as well, for a modified mean-shift algorithm.
I'll probably port Isomap and LLE algorithms as well, they are widely used
for manifold learning (they can be expressed as KPCA algorithms with a
particular kernel).


Matthieu
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