On Feb 25, 2012, at 6:24 PM, kevin123 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,
What part of that error message is unclear? Have you looked at the
randomForest page? It tells you what the default behavior is na.fail.
I would greatly appreciate any help
I would seem that the way forward is to remove the cases with missing
values or to impute values.
--
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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