Hi, there:
I spent some time on this but I think I really cannot figure it out, maybe I
missed something here:

my data looks like this:
> dim(trn3)
[1] 7361 209
> dim(val3)
[1] 7427 209

> mg.rf2<-randomForest(x=trn3[,1:208], y=trn3[,209], data=trn3, xtest=val3[,
1:208], ytest=val3[,209], importance=T)

my test data has 7427 observations but after prediction,
> dim(mg.rf2$votes)
[1] 7361 2

which has the same length as my training data.

but if I use
mg.rf<-randomForest(x=trn3[,1:208], y=trn3[,209], data=trn3, importance=T)
followed by
> mg.pred<-predict(mg.rf, newdata=val3[,1:208])
> length(mg.pred)
[1] 7427

it works. But i need to know votes so I have to use the first way.
Please help.

Weiwei
--
Weiwei Shi, Ph.D

"Did you always know?"
"No, I did not. But I believed..."
---Matrix III

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