On Sat, Nov 5, 2011 at 12:44 AM, Olivier Grisel <[email protected]> wrote: > I think it make sense to have a pure cython implementation in > scikit-learn without having runtime dependency on a compiler nor CUDA > / OpenCL and have advanced, theano based neural networks (with more > parameter auto-tuning and pluggable exotic objective functions) in > pylearn.
I'm +1 with having a Cython-based implementation in scikit-learn even if it's a little bit behind a Theanos-based implementation. Another possibility is to host a Theanos-based implementation as a side project on github and make the API scikit-learn compatible. # In general, I don't really buy the "why implement X if it already exists in Y" argument because it can be said of pretty much every module in scikit-learn. Since we came up with a quite rigorous review process, even if we reimplement something that already exists elsewhere, in the end we usually obtain a very high-quality module (in code and documentation). Think of the tree module :) Mathieu ------------------------------------------------------------------------------ RSA(R) Conference 2012 Save $700 by Nov 18 Register now http://p.sf.net/sfu/rsa-sfdev2dev1 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
