On Jun 8, 2014, at 6:27 PM, Alexsandro Cândido de Oliveira Silva 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?
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