R help - Nov 2013 - bnlearn and very large datasets (> 1 million observations)

Hi

Anyone have experience with very large datasets and the Bayesian Network
package, bnlearn?  In my experience R doesn't react well to very large
datasets.

Is there a way to divide up the dataset into pieces and incrementally learn
the network with the pieces?  This would also be helpful incase R crashes,
because I could save the network after learning each piece.

Thank you.

	[[alternative HTML version deleted]]

On 30/11/2013 04:52, Jejo Koola wrote:
> Hi
>
> Anyone have experience with very large datasets and the Bayesian Network
> package, bnlearn?  In my experience R doesn't react well to very large
> datasets.
Maybe, but a million is not 'very large': R handles billions of 
observations without problems on machines with commensurate resources.

Package bnlearn is not 'R'.  Your questions are not about R itself and 
should be addressed to the package maintainer.
> Is there a way to divide up the dataset into pieces and incrementally learn
> the network with the pieces?  This would also be helpful incase R crashes,
> because I could save the network after learning each piece.
>
> Thank you.
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
PLEASE do, including what it says about HTML mail and about 'crashes'.

-- 
Brian D. Ripley,                  ripley at stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595