If you are using the latest version (4.5-25), you will see in rfNews() that
that's the problem I need to fix. The package was able to handle ordered
factors, but some more stringent checks for factor levels consistency introduced
in 4.5-23 broke the support for ordered factors in prediction.
>From the code you've shown, it looks like you are just growing the
forest to evaluate variable importance or other things, instead of predicting
other data (since you set keep.forest=FALSE). If that's the case, you
should be fine, as the problem only happens when you try to call predict() with
models that contain ordered factors as predictors.
(Ordered factors are basically treated as numerics in RF: trees only make use of
ranks for numeric variables, so there's basically no difference between
ordered factors and numeric variables as predictors.)
Andy
From: Birgit Lemcke>
> Hello R-user!
>
> I am running R 2.7.0 on a Power Book (Tiger). (I am still R and
> statistics beginner)
>
> I try to find the most important variables to divide my dataset as
> given in a categorical variable.
>
> code:
>
> Test.rf4<-randomForest(Sex~.,na.action=na.roughfix, data=Subset4,
> importance=TRUE, proximity=TRUE, ntree=10000, do.trace=1000,
> keep.forest=FALSE)
>
> My dataset contains also ordered factors classified as such.
> Is randomForest able to deal with it, does it change anything or is
> there no difference in using factors or ordered factors?
>
> Many thanks in advance
>
> B.
>
> Birgit Lemcke
> Institut f?r Systematische Botanik
> Zollikerstrasse 107
> CH-8008 Z?rich
> Switzerland
> Ph: +41 (0)44 634 8351
> birgit.lemcke at systbot.uzh.ch
>
> 175 Jahre UZH
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> Campus Irchel, Winterthurerstrasse 190, 8057 Z?rich
> Weitere Informationen http://www.175jahre.uzh.ch/naturwissenschaft
>
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