I have the following code for random forest:
set.seed(71)
rf = randomForest(Species~.,data=iris,ntree=200,mtry=2,sampsize=30,keep.forest=TRUE,replace=FALSE,keep.inbag=TRUE)
I would like to get the 200th decision tree, so I use:
> getTree (rf,200)
left daughter right daughter split var split point status prediction
1 2 3 3 2.50 1 0
2 0 0 0 0.00 -1 1
3 4 5 3 4.75 1 0
4 0 0 0 0.00 -1 2
5 6 7 3 5.05 1 0
6 8 9 1 6.45 1 0
7 0 0 0 0.00 -1 3
8 0 0 0 0.00 -1 3
9 0 0 0 0.00 -1 2
But I want to use the 200th tree as decision tree such as rpart. So it will have the format like:
> getTree (rf,200).rpart
n= 111
node), split, n, loss, yval, (yprob)
* denotes terminal node
1) root 111 35 other (0.68468468 0.31531532)
2) Petal.Length< 4.95 77 3 other (0.96103896 0.03896104) *
3) Petal.Length>=4.95 34 2 virginica (0.05882353 0.94117647) *
Is there a way to transform the getTree (rf,200) which is a dataframe:
> str(getTree (rf,200))
num [1:9, 1:6] 2 0 4 0 6 8 0 0 0 3 ...
- attr(*, "dimnames")=List of 2
..$ : chr [1:9] "1" "2" "3" "4" ...
..$ : chr [1:6] "left daughter" "right daughter" "split var" "split point" ...
into a real rpart decision tree object?
