Hey Andreas,
thanks a lot for your quick reply. The gil-released functions are a bit
difficult to handle so I guess we should provide the most common functions.
Maybe it is possible to make an add-on to enable the on-demand
functionality?
One idea is to make a spin-off of the latest stable version and
implement the on-demand functionality with a set of the most common
functions to choose of. Thus, the user just need to implement
gil-released functions if he really tries new things.
Or is it possible to make a patch to add the functions? This would
probably be the most practical way to give easy access to new
functionality. The need to generate a new patch for every new release
version of sklearn is a disadvantage that should be mentioned.
As you can see I'm searching for a way to use the scikit-learn library
as a strong basis and add my functionality. Because I am just interested
in RDFs I wonder if there will be trouble when I just copy the "tree"
section of sklearn to add my new DecisionTreeClassifier and import the
rest of the scikit-learn library with respect to Cython? This way I get
a small library on its own.
Or is there another safe way to create such an add-on for scikit-learn?
Best,
Alex
PS: I hope this email will reach its aim, otherwise: I reply to this
<http://sourceforge.net/p/scikit-learn/mailman/message/33052675/>.
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