use (as.factor(target) ~., data =your data, ...)





On Tue, May 4, 2010 at 12:07 PM, pdb <philb@philbrierley.com> wrote:

>
> Hi,
>
> I'm experimenting with random forests and want to perform a binary
> classification task.
> I've tried some of the sample codes in the help files and things run, but I
> get a message to the effect 'you don't have very many unique values in the
> target - are you sure you want to do regression?' (sorry, don't know exact
> message but r is busy now so can't check).
>
>
> In reading the help files I see 2 examples, one for classification and one
> for regression. To the uninformed - these don't seem much different to each
> other. How does rf know to do regression or classification?
>
> ## Classification:
> ##data(iris)
> set.seed(71)
> iris.rf <- randomForest(Species ~ ., data=iris, importance=TRUE,
>                        proximity=TRUE)
>
>
> ## Regression:
> ## data(airquality)
> set.seed(131)
> ozone.rf <- randomForest(Ozone ~ ., data=airquality, mtry=3,
>                         importance=TRUE, na.action=na.omit)
>
>
> My target variable only has 2 values - why does it want to do regression?
> I've entered code just like that in the classification example above. Also
> when it asks me 'are you sure you want to do regression' - how do I say
> 'NO,
> do classification please'?
>
>
>
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/randomforests-how-to-classify-tp2126166p2126166.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
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> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>



-- 
Sincerely,
Changbin
--

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