I use randomForest version 3.4-4, but yes, now I correctly omitted NA's it works. I should have made a mistake while removing them first time.

I was surprised that this method doesn't have another way to deal with NA's than omitting them. As Torsten Hothorn suggested, the associated predict function should then check for NA's in newdata, shouldn't it ?

Thank you both for your answers !

At 15:12 02/04/03, Liaw, Andy wrote:
Yves,

Which version of the package are you using? I get:

> soy <- na.omit(Soybean)
> ts <- sample(nrow(soy), 150, replace=FALSE)
> sb.rf <- randomForest(Class ~ ., data=soy[-ts,])
> table(predict(sb.rf, soy[ts,], type="class"))

               2-4-d-injury         alternarialeaf-spot
                          0                          37
                anthracnose            bacterial-blight
                         10                           3
          bacterial-pustule                  brown-spot
                          2                          29
             brown-stem-rot                charcoal-rot
                         11                           7
              cyst-nematode diaporthe-pod-&-stem-blight
                          0                           0
      diaporthe-stem-canker                downy-mildew
                          4                           8
         frog-eye-leaf-spot            herbicide-injury
                         17                           0
     phyllosticta-leaf-spot            phytophthora-rot
                          3                           5
             powdery-mildew           purple-seed-stain
                          4                           5
       rhizoctonia-root-rot
                          5

Cheers,
Andy

> -----Original Message-----
> From: Yves Brostaux [mailto:[EMAIL PROTECTED]
> Sent: Wednesday, April 02, 2003 4:46 AM
> To: [EMAIL PROTECTED]
> Subject: [R] randomForests predict problem
>
>
> Hello everybody,
>
> I'm testing the randomForest package in order to do some
> simulations and I
> get some trouble with the prediction of new values. The random forest
> computation is fine but each time I try to predict values
> with the newly
> created object, I get an error message. I thought I was
> because NA values
> in the dataframe, but I cleaned them and still got the same
> error. What am
> I doing wrong ?
>
>  > library(mlbench)
>  > library(randomForest)
>  > data(Soybean)
>  > test <- sample(1:683, 150, replace=F)
>  > sb.rf <- randomForest(Class~., data=Soybean[-test,])
>  > sb.rf.pred <- predict(sb.rf, Soybean[test,])
> Error in matrix(t1$countts, nr = nclass, nc = ntest) :
>          No data to replace in matrix(...)
>
> I did it the same way with rpart and all worked fine :
>  > library(rpart)
>  > sb.rp <- rpart(Class~., data=Soybean[-test,])
>  > sb.rp.pred <- predict(sb.rp, Soybean[test,], type="class")
>
> Thank you all for any advice you can give to me.
>
> --
> Ir. Yves Brostaux - Statistics and Computer Science Dpt.
> Gembloux Agricultural University
> 8, avenue de la Facult� B-5030 Gembloux (Belgium)
> T�l : +32 (0)81 62 24 69
> E-mail : [EMAIL PROTECTED]
> Web : http://www.fsagx.ac.be/si/
>
> ______________________________________________
> [EMAIL PROTECTED] mailing list
> https://www.stat.math.ethz.ch/mailman/listinfo/r-help
>

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