[R] Questions on RandomForest

[Fucang Jia]

Hi, erveryone,

I show much thanks to Andy and Matthew on former questions. I now sample 
only a small segment of a image can segment the image into several classes 
by RandomForest successfully. Now I have some confusion on it:

1.  What is the internal component classifier in RandomForest? Are they the 
CART implemented in the rpart package?

2. I use training samples to predict new samples. But in the population, if 
I sample not the whole components, but several components I am interested, 
can randomforest not classify the non-similar components in the testing 
samples, that is to say, label them as outliers?

3. When random forest is used to predict, the testing samples should be no 
contribution to the classifiers(which should be done). So I think the memory 
usage should not increase much, but when I use RF to predict a 256*256*141 
samples by 1329 samples (3 variables), on a SGI Octane2 with 2Giga RAM, it 
runs out of memory. Then I have to segment the big dataset into two, one is 
256*256*70, and the other is 256*256*71. Why do RF consume so much memory in 
the prediction? Does it produce other things other than class label?


Thank you very much!

Fucang