[R] Random Forest prediction questions

[Liaw, Andy]

From: Dror
> 
> Hi,
> I need help with the randomForest prediction. i run the folowing code:
>  
> > iris.rf <- randomForest(Species ~ ., data=iris,
> > importance=TRUE,keep.forest=TRUE, proximity=TRUE)
> > pr<-predict(iris.rf,iris,predict.all=T)
> > iris.rf$votes[53,]
>     setosa versicolor  virginica 
>  0.0000000  0.8074866  0.1925134 
> > table(pr$individual[53,])/500
> 
> versicolor  virginica 
>      0.928      0.072 
> > 
> 
> why the voting is not the same for the same data? what do i do wrong?

It's because the $votes components reflects the OOB predictions, whereas
predict() gives you predictions based on all of the trees in the forest.
 
> another 2 questions:
> 1. i tries to debug another problem in which the individual vector was
> smaller the tree number in the forest.
>    i noticed that in this row of code:
> 
>    treepred <- matrix(object$classes[t1$treepred], nrow = 
> length(keep), 
>                 dimnames = list(rn[keep], NULL))
> the t1$treepred has values of 0 (i have 2 classes) and they 
> droped from the
> results
> what does this 0 mean?

Not sure why you're debugging that portion of the code.  That is just to
dimension the array passed back from C into a matrix.  What is "t1"?

> 2. how can i drop a tree from the forest?

Look at the $forest component of the randomForest object, and subset the
dimension that correspond to ntree in all of its components.  Change
$ntree accordingly.

Andy
 
> Thanks,
> Dror
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