[SciPy-Dev] SciPy Goal
Charles R Harris
Wed Jan 4 21:53:18 CST 2012
On Wed, Jan 4, 2012 at 8:07 PM, Travis Oliphant <email@example.com> wrote:
>> - cluster : low maintenance cost, small. not sure about usage, quality.
>> I think cluster overlaps with scikits-learn quite a bit. It basically
>> contains a K-means vector quantization code with functionality that I
>> suspect exists in scikits-learn. I would recommend deprecation and
>> removal while pointing people to scikits-learn for equivalent functionality
>> (or moving it to scikits-learn).
> I disagree. Why should I go to scikits-learn for basic functionality like
> that? It is hardly specific to machine learning. Same with various matrix
> What is basic and what is not basic is the whole point of the discussion.
> I'm not sure that the functionality in cluster.vq and cluster.hierarchy
> can be considered "basic". But, it will certainly depend on the kinds of
> problems you tend to solve. I also don't understand your reference to
> matrix factorizations in this context.
> But, this isn't a big-deal to me, either, so if there are strong opinions
> wanting to keep it, then great.
Clustering is pretty basic to lots of things. That said, K-means might not
be the one to keep.
There are various matrix factorizations beyond the basic svd that are less
common, but potentially useful, such as that in partial least squares and
positive matrix factorization. I think the scikits-learn folks use some of
these and they might have and idea as to how useful they have been. ISTR
someone posting about doing PLS for scipy a while back.
>> What are the needs of this package? What needs to be fixed / improved?
>> It is a broad field and I could see fixing scipy.signal with a few simple
>> algorithms (the filter design, for example), and then pushing a separate
>> package to do more advanced signal processing algorithms. This sounds
>> fine to me. It looks like I can put attention to scipy.signal then, as It
>> was one of the areas I was most interested in originally.
> Filter design could use improvement. I also have a remez algorithm that
> works for complex filter design that belongs somewhere.
> It seems like this should go into scipy.signal next to the remez algorithm
> that is already there.
I'd actually like it to replace the current one since it it is readable --
mostly python with a bit of Cython for finding extrema -- and does
hermitean filters, which covers both the symmetric and anti-symmetric
filters that the current version does.
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