[SciPy-dev] BayesNet SciKit

Gouws, Almero <14366037@sun.ac.za> 14366037@sun.ac...
Tue Jun 24 05:57:19 CDT 2008


By starting from scratch we can guarantee comprehensive documentation and
tests. Similar projects such as OpenBayes weren't very well documented and
had very few tests. Looking at the functionality of OpenBayes when it was
abondoned (http://www.openbayes.org/features), the current project is basically 
at that point, plus we have a proper set of unit tests.

-Almero


-----Original Message-----
From: scipy-dev-bounces@scipy.org on behalf of Ed Rahn
Sent: Tue 24/06/2008 12:06
To: SciPy Developers List
Subject: Re: [SciPy-dev] BayesNet SciKit
 
What's the reasoning for starting from scratch on a port instead of 
using preexisting code that has the same exact objective?

- Ed

Gouws, Almero <14366037@sun.ac.za> wrote:
> Hi,
> 
> I am a masters student currently working on a port of Kevin P. Murphy's
> Matlab toolbox, FullBNT, to Python. The code is not yet available in a
> public repository, because I would like it to match or surpass 
> the functionality of the openbayes toolbox before making it available.
> 
> Here's a list of what is currently working:
> 
> -Static Bayesian Networks:
>  -Nodes:
>   - Mutinomial nodes:
>    - (Sequential) Bayesian parameter updating from complete data.
>    - Maximum liklihood parameter estimation from complete data.
>    - Maximum likelihood parameter estimation with missing values (EM)
>    - Greedy K2 structure learning.
> 
>   - Gaussian nodes:
>    - Maximum liklihood parameter estimation from complete data.
> 
>  - Inference Engines:
>   - Junction tree inference engine
>     - Works for Multinomial and Guassian nodes.
> 
> Thanks
> Almero Gouws
> 
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