Alexasandro, just for your information the catnet package can handle missing data, as well as perturbed data. it deals with discrete data only which is not a problem for you.
peter On Sun, Jun 8, 2014 at 9:27 PM, Alexsandro Cândido de Oliveira Silva < a...@dpi.inpe.br> wrote: > Hello, > > I am using the bnlearn package in R to handle large amounts of data in > Bayesian networks. The variables are discrete and have more than 3 million > observations. > With bn.fit function I could easily get the conditional probability > distribution. However, some variables have unobserved values ??(i.e., NA or > NaN). In some variables, unobserved values ??are almost 1 million. This is > a lot to just delete them. > > In tests, I've got this: > > nw.fit <-bn.fit (nw, date, method = 'bayes') >> > Error in check.data (date): the data set contains null / NaN / NA values??. > > So, how could I deal with the data and get the conditional probability > distribution? > Could someone help me? > > > Regards. > Alexsandro Cândido de Oliveira Silva > > ______________________________________________ > R-help@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. > -- Peter Salzman, PhD Department of Biostatistics and Computational Biology University of Rochester [[alternative HTML version deleted]]
______________________________________________ R-help@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.
