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 <anopheles123@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 <kevincorry123@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.
>

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