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.
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