getTree {randomForest} | R Documentation |
This function extract the structure of a tree from a
randomForest
object.
getTree(rfobj, k=1)
rfobj |
a randomForest object. |
k |
which tree to extract? |
For categorical predictors, the splitting point is represented by an integer, whose binary expansion gives the identities of the categories that goes to left or right. For example, if a predictor has three categories, and the split point is 5. The binary expansion of 5 is (1, 0, 1) (because 5 = 1*2^0 + 0*2^1 + 1*2^2), so cases with categories 1 or 3 in this predictor get sent to the left, and the rest to the right.
A matrix with six columns and number of rows equal to total number of nodes in the tree. The six columns are:
left daughter |
the row where the left daughter node is; 0 if the node is terminal |
right daughter |
the row where the right daughter node is; 0 if the node is terminal |
split var |
which variable was used to split the node; 0 if the node is terminal |
split point |
where the best split is; see Details for categorical predictor |
status |
is the node terminal (-1) or not (1) |
prediction |
the prediction for the node; 0 if the node is not terminal |
Andy Liaw andy_liaw@merck.com
data(iris) getTree(randomForest(Species ~ ., iris, ntree=10), 3)