Hi, Thanks for your help,
This worked very well: na.action=na.roughfix Kevin On Sun, Feb 26, 2012 at 3:10 PM, Weidong Gu <anopheles...@gmail.com> wrote: > Hi, > > You can set na.action=na.roughfix which fills NAs with the mean or > mode of the missing variable. > > Other option is to impute missing values using rfImpute, then run > randomForest on the complete data set. > > Weidong Gu > > On Sat, Feb 25, 2012 at 6:24 PM, kevin123 <kevincorry...@gmail.com> wrote: > > I am using the package Random Forrest to test and train a model, > > I aim to predict (LengthOfStay.days),: > > > >> library(randomForest) > >> model <- randomForest( LengthOfStay.days~.,data = training, > > + importance=TRUE, > > + keep.forest=TRUE > > + ) > > > > > > *This is a small portion of the data frame: * > > > > *data(training)* > > > > LengthOfStay.days CharlsonIndex.numeric DSFS.months > > 1 0 0.0 8.5 > > 6 0 0.0 3.5 > > 7 0 0.0 0.5 > > 8 0 0.0 0.5 > > 9 0 0.0 1.5 > > 11 0 1.5 NaN > > > > > > > > *Error message* > > > > Error in na.fail.default(list(LengthOfStay.days = c(0, 0, 0, 0, 0, 0, : > > missing values in object, > > > > I would greatly appreciate any help > > > > Thanks > > > > Kevin > > > > > > -- > > View this message in context: > http://r.789695.n4.nabble.com/How-to-deal-with-missing-values-when-using-Random-Forrest-tp4421254p4421254.html > > Sent from the R help mailing list archive at Nabble.com. > > > > ______________________________________________ > > 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. > [[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.
