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.
