[SciPy-Dev] SciPy Goal
Wed Jan 4 21:07:28 CST 2012
>> - 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 factorizations.
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.
> 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.
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