Bayesian Network Models in PyMC3 and NetworkX

pmml_bayesnet.ipynb

Hi Tbsexton thanks for your prompt reply! Much appreciated

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On Mon, 1 Jul 2019 at 15:52, Thurston Sexton ***@***.***> wrote: Wow, I had no idea there were comments here! Thanks to all for checking out the example. For those of you with issues/ideas (especially networkx v2 problems), check out the repository <https://github.com/usnistgov/pmml_pymcBN> that automates a lot of the underlying mechanical/boilerplate code in this example. This notebook was really just a proof-of-concept for that repository. I haven't gone back to the code for a while, but if there's interest I would be happy to update things to newer pymc3 features. Please see if your above issues persist in the more mature repository. Thanks! — You are receiving this because you commented. Reply to this email directly, view it on GitHub <https://gist.github.com/1349864212b25cce91dbe5e336d794b4?email_source=notifications&email_token=ABOR6SK332I4ZSCQAXDB63TP5ID3NA5CNFSM4H4SQIM2YY3PNVWWK3TUL52HS4DFVNDWS43UINXW23LFNZ2KUY3PNVWWK3TUL5UWJTQAFUS4U#gistcomment-2958794>, or mute the thread <https://github.com/notifications/unsubscribe-auth/ABOR6SJMJ2QGVZ5CUMO4BCLP5ID3NANCNFSM4H4SQIMQ> .

@NelisW certainly, and like I said, feel free to open an issue if something works unexpectedly on that repo (as I said, it's been a while).

If you are having issues with BN.edges['C3']['D4']['bin'], substitute for BN.edges['C3','D4']['bin'].

As described in the migration guide mentioned before

G.edge have been removed in favor of using G.nodes[n] and G.edges[u, v]

Do you have any example for dynamic BN simulated on PYMC3?