[SciPy-dev] Hierarchical clustering package
Sat Nov 24 03:58:21 CST 2007
> > I don't know what the opinon of others are on this, but maybe this
> > package could be added to scikits (there is already a scikits.learn
> > packages for ML-related algorithms, ANN, Em for mixtures of Gaussian,
> > and SVM) ?
> I'm fine with maintaining it as a separate package (hcluster) on my
> website unless others find that including it in Scipy would be useful.
I think this package would fit great in a scikit (the learn one for
instance) but not it scipy directly. The cluster package stays in scipy for
compatibility reasons IIRC.
> The convention is to have the datasets in the package. I am not sure to
> > understand why it is messy: it is good to have self-contained regression
> > tests ?
> I am not making an argument against self-contained tests. Rather, I am
> simply stating that putting the data in Python programs is a bit messy,
> especially when the data are large. It gives unnecessary lines for SVN
> diff to process when a program containing a data set is changed, which
> is not as likely when the data sets are stored in separate text files.
> If the Scipy convention is to put testing data in test programs then so
> be it. What's the convention?
You put them in separate files. Fo rinstance, you can pickle them and save
them, and finally load them when you process the test.
David proposed an answer for a dataset interface, but I don't know where it
Java has a facility for loading resources like images, text and data
> files, which are all loaded in a similar way classes are loaded. Does
> Python have a similar facility?
Scipy does (the IO module) to some extent. But you do not need to load
images, text and data files, only preprocessed data ;)
French PhD student
Website : http://miles.developpez.com/
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