[R--gR] Package for Discrete Bayesian Networks

[Kjell Konis]

If you have access to Hugin then you may find the RHugin package useful.

   http://rhugin.r-forge.r-project.org/

It provides an R API for the Hugin Decision Engine.

Cheers,
Kjell

On Mar 27, 2009, at 3:45 PM, Thomas Liebig wrote:

> Hi Matthias,
>
> I also want to utilise large discrete Bayesian Networks with R (for
> spatial applications). Actually I learn the networks outside R with  
> some
> selfmade tools and am looking for a package that offers me basic
> inference and sampling functions afterwards.
> Deal doesnt provide them. Claus Dethlefsen suggested to use Rhugs
> instead that provides an interface to hugin.
>
> Therefore, i'm currently implementing these two R functions  
> (inference,
> sampling) plus an additional import function. For your application you
> would also need a fast Network Search algorithm for large networks.
> Perhaps the 'Sparse Candidate Algorithm', 'Scalable Sparse Bayesian
> Network Search' or the 'Screen Based Network Search' as deal only
> provides the poor Greedy Search for Bayesian Networks.
>
> Feel free to contact me in case, you are interested in exchanging
> functions or experience. Your application sounds also very interesting
> to me, and i would be happy to learn more about your textmining  
> domain.
>
> regards,
> Thomas
>
> Mat_1 at gmx.net schrieb:
>> All,
>>
>> I would like to apply Bayesian networks to text-based information.  
>> That is, I would like to use Bayesian networks to extract  
>> 'sentiment' (say, 'good' vs. 'bad') form unstructured text.
>>
>>> From the CRAN Task View on gRaphical Models in R it seems that I  
>>> should use the combination of the two packages deal and gRain  
>>> (please correct me if I overlooked something). The package deal  
>>> can work both with discrete and continuous variables. For my  
>>> project I only need to work with discrete variables. Due to the  
>>> large amount of data that I potentially have to handle, I am  
>>> concerned that maybe deal will not run fast enough because it is  
>>> 'too general' for my purpose.
>>
>> In this sense, I would like to ask the following: is there an R  
>> package that I overlooked and that is tailored towards Bayesian  
>> networks with discrete variables?
>>
>> Many thanks,
>>
>> Matthias
>>
>
> -- 
> Thomas Liebig
> Fraunhofer-Institut für Intelligente Analyse- und
> Informationssysteme (IAIS)
>
> Schloss Birlinghoven, D-53754 Sankt Augustin, Germany
> Email:  thomas.liebig at iais.fraunhofer.de
> Phone:  +49 2241 142050
> Fax:    +49 2241 142072
>
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