On Apr 7, 2012, at 03:22 , xinfan meng wrote: > > > On Sat, Apr 7, 2012 at 1:18 AM, Vlad Niculae <[email protected]> wrote: > Hi Shankar > > I am also following the PGM class and I would like to stress out that the way > they implement all the factor operations feels to me to be by no means > efficient, way too much random memory indexing. However the class seems very > insightful, maybe after it ends we will be illuminated as to how to design > some PGM algorithms to fit inside scikit-learn. > > In this case there seems to be a clear tradeoff between generality and > efficiency. Maybe you could instead focus some attention on the HMM module > inside scikit-learn. > > Also, there was some interest in wrapping CRFSuite [1] [2] by Jake. I will > need to use CRFs for my research in a short time, so I might be putting some > effort into this as well. Currently the effort has hit some design issues, > specifically the problem that CRFsuite does input/output via text files in > the filesystem. > > Great, as a nlper, I use CRF a lot. Glad to see someone are planing for this > integration. I would like to join the discussion in that case.
Cool, interest is growing! Jake's effort is here: https://github.com/jakevdp/pyCRFsuite > > Good luck on the class and looking forward to your contributions. > > Best, > Vlad > > On Apr 6, 2012, at 19:25 , Gael Varoquaux wrote: > > > Hey Shankar, > > > > I respect your decision: it is better for everyone to have less > > applications, but well-though out. What you are learning as you go could > > help setting up a serious application for next year, hopefully. > > > > Thanks for keeping us updated. > > > > Gael > > > > On Fri, Apr 06, 2012 at 09:41:40PM +0800, Shankar Satish wrote: > >> Hello everyone, > > > >> I was supposed to prepare a proposal for bayesian networks in sklearn. > >> However as i researched the details further, i realized out that doing a > >> python implementation will be harder than i thought, primarily due to the > >> need of many customized data structures. > > > >> I have also been following the stanford PGM course > >> (www.*pgm*-*class*.org/<http://www.pgm-class.org/>). > >> They use Matlab for the assignments, and Matlab provides many useful > >> operations on sets that are necessary for operations on bayes nets. I think > >> i will have a much clearer idea of how to go about about implementing a > >> python version at the end of the course. > > > >> So for these reasons, combined with the fact that i don't want to risk > >> putting in a proposal that i might not be able to complete within the > >> summer deadline, i have decided to drop the idea of a GSoC proposal for > >> bayes nets. I will instead finish the course first and code the sklearn > >> version at liesure. > > > >> I would like to thank you all for your comments and feedback, and i would > >> especially like to thank Andy for offering to mentor me :). > > > >> regards > >> shankar. > > > > > > -- > > Gael Varoquaux > > Researcher, INRIA Parietal > > Laboratoire de Neuro-Imagerie Assistee par Ordinateur > > NeuroSpin/CEA Saclay , Bat 145, 91191 Gif-sur-Yvette France > > Phone: ++ 33-1-69-08-79-68 > > http://gael-varoquaux.info > > > > ------------------------------------------------------------------------------ > > For Developers, A Lot Can Happen In A Second. > > Boundary is the first to Know...and Tell You. > > Monitor Your Applications in Ultra-Fine Resolution. Try it FREE! > > http://p.sf.net/sfu/Boundary-d2dvs2 > > _______________________________________________ > > Scikit-learn-general mailing list > > [email protected] > > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > ------------------------------------------------------------------------------ > For Developers, A Lot Can Happen In A Second. > Boundary is the first to Know...and Tell You. > Monitor Your Applications in Ultra-Fine Resolution. Try it FREE! > http://p.sf.net/sfu/Boundary-d2dvs2 > _______________________________________________ > Scikit-learn-general mailing list > [email protected] > https://lists.sourceforge.net/lists/listinfo/scikit-learn-general > > > > -- > Best Wishes > -------------------------------------------- > Meng Xinfan（蒙新泛） > Institute of Computational Linguistics > Department of Computer Science & Technology > School of Electronic Engineering & Computer Science > Peking University > Beijing, 100871 > China ------------------------------------------------------------------------------ For Developers, A Lot Can Happen In A Second. Boundary is the first to Know...and Tell You. Monitor Your Applications in Ultra-Fine Resolution. Try it FREE! http://p.sf.net/sfu/Boundary-d2dvs2 _______________________________________________ Scikit-learn-general mailing list [email protected] https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
