Hello everyone,
Based on this discussion, i shall go ahead and craft a more detailed GSoC
proposal for Bayesian Networks in Scikits-learn over the next few days. In
the meanwhile, do keep your suggestions / concerns coming in :)
Also, i feel including structure learning as part of the GSoC proposal is a
bit too ambitious. Hence i will focus on inference from a
specified Bayesian network, and learning the parameters for a BN from data.
I want to continue my involvement beyond the summer, and hopefully after
the basic infrastructure for BNs is in place, i can incorporate the
structure learning stuff later...
regards,
shankar.
On Sun, Mar 18, 2012 at 8:35 PM, Andreas <[email protected]> wrote:
>
> > The idea was to give each node potential manually. So there will be
> > a dict of marginal distributions that is as big as the graph.
> > Given that, I don't think that the DAG representation will play such a
> > big role.
> >
> I meant to say dict of conditional distributions. My bad.
>
>
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